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/image_component_labeling_and_feature_extraction/trunk/test_LabelOperation.vhd
0,0 → 1,135
--------------------------------------------------------------------------------
-- Company:
-- Engineer:
--
-- Create Date: 16:39:28 05/13/2008
-- Design Name: mean3x3Operation
-- Module Name: C:/Documents and Settings/bentho/Mina dokument/VHDL/Pegasus/studentVideo/test_mean3x3Operation.vhd
-- Project Name: studentVideo
-- Target Device:
-- Tool versions:
-- Description:
--
-- VHDL Test Bench Created by ISE for module: mean3x3Operation
--
-- Dependencies:
--
-- Revision:
-- Revision 0.01 - File Created
-- Additional Comments:
--
-- Notes:
-- This testbench has been automatically generated using types std_logic and
-- std_logic_vector for the ports of the unit under test. Xilinx recommends
-- that these types always be used for the top-level I/O of a design in order
-- to guarantee that the testbench will bind correctly to the post-implementation
-- simulation model.
--------------------------------------------------------------------------------
LIBRARY ieee;
USE ieee.std_logic_1164.ALL;
USE ieee.std_logic_unsigned.all;
USE ieee.numeric_std.ALL;
 
ENTITY test_labelOperation IS
END test_labelOperation;
 
ARCHITECTURE behavior OF test_labelOperation IS
 
 
SIGNAL clk : std_logic := '0';
SIGNAL fsync_in : std_logic := '0';
SIGNAL rsync_in : std_logic := '0';
SIGNAL pdata_in : std_logic_vector(7 downto 0) := (others=>'0');
SIGNAL outputCodes : std_logic_vector(9 downto 0);
SIGNAL componentCnt : std_logic_vector(9 downto 0);
SIGNAL fsync_out : std_logic;
SIGNAL rsync_out : std_logic;
SIGNAL pdata_out : std_logic_vector(7 downto 0);
SIGNAL pdata_inter : std_logic_vector(7 downto 0);
SIGNAL reset : std_logic;
SIGNAL fsync_inter, rsync_inter, bindata : std_logic;
SIGNAL features : std_logic_vector(34 downto 0);
SIGNAL featureDataStrobe, commReady : std_logic;
SIGNAL x_cog, y_cog : std_logic_vector(16 downto 0);
SIGNAL RX_DATA, RTS_IN, DSR_OUT, TX_DATA, CTS_OUT : std_logic := '0';
 
BEGIN
-- Instantiate the Unit Under Test (UUT)
uut: entity work.label8Operation
port map(
pclk => clk,
reset => reset,
fsync_in => fsync_inter,
rsync_in => rsync_inter,
data_in => pdata_inter,
pbin_in => bindata,
fsync_out => fsync_out,
rsync_out => rsync_out,
pdata_out => outputCodes,
featureDataStrobe => featureDataStrobe,
acknowledge => commReady,
cntObjects => componentCnt,
x_cog_out => x_cog,
y_cog_out => y_cog
);
features <= '0' & x_cog & y_cog; -- x and y coordinates are merged into one single vector
-- for transmission over the serial link
transmit: entity work.SendFeatures
PORT MAP (
features => features,
fsync => fsync_out,
wstrobe => featureDataStrobe,
ready => commReady,
clk => clk,
reset => reset,
RX_DATA => RX_DATA,
RTS_IN => RTS_IN,
DSR_OUT => DSR_OUT,
TX_DATA => TX_DATA,
CTS_OUT => CTS_OUT
);
RX_DATA <= TX_DATA;
 
 
fsync_inter <= fsync_in;
rsync_inter <= rsync_in;
pdata_inter <= "11111111" - pdata_in;
bindata <= '1' when pdata_in < 110 else '0';
-----------------------------------------------------------------
img_read : entity work.img_testbench
port map (
pclk_i => clk,
reset_i => reset,
fsync_i => fsync_out,
rsync_i => rsync_out,
pdata_i => pdata_out,
cols_o => open,
rows_o => open,
col_o => open,
row_o => open,
fsync_o => fsync_in,
rsync_o => rsync_in,
pdata_o => pdata_in);
 
clock_generate: process (clk)
constant T_pw : time := 37 ns; -- Clock frequency is 27/2 MHz
begin -- process img
if clk = '0' then
clk <= '1' after T_pw, '0' after 2*T_pw;
end if;
end process clock_generate;
pdata_out <= outputCodes(7 downto 0);
-- pdata_out <= bindata&bindata&bindata&bindata&bindata&bindata&bindata&bindata;
reset <= '1', '0' after 60 ns;
 
END;
/image_component_labeling_and_feature_extraction/trunk/labelOperation.vhd
0,0 → 1,127
 
-- Company:
-- Engineer:
--
-- Create Date:
-- Design Name:
-- Module Name:
-- Project Name:
-- Target Devices:
-- Tool versions:
-- Description:
--
-- Dependencies:
--
-- Revision:
-- Revision 0.01 - File Created
-- Additional Comments:
--
----------------------------------------------------------------------------------
library IEEE;
use IEEE.STD_LOGIC_1164.ALL;
--use IEEE.STD_LOGIC_ARITH.ALL;
use IEEE.STD_LOGIC_UNSIGNED.ALL;
 
---- Uncomment the following library declaration if instantiating
---- any Xilinx primitives in this code.
--library UNISIM;
--use UNISIM.VComponents.all;
 
entity label8Operation is
generic (
CODE_WIDTH : integer := 10;
NO_OF_COLS : integer := 640;
NO_OF_ROWS : integer :=480;
NO_BITS_CC : integer := 11;
NO_BITS_RC : integer := 10
);
port(
pclk : in std_logic;
reset : in std_logic;
fsync_in : in std_logic;
rsync_in : in std_logic;
data_in : in std_logic_vector(7 downto 0):= (others=>'0');
pbin_in : in std_logic;
fsync_out : out std_logic;
rsync_out : out std_logic;
pdata_out : out std_logic_vector( CODE_WIDTH-1 downto 0 );
featureDataStrobe : out std_logic;
acknowledge : in std_logic;
cntObjects : out std_logic_vector(9 downto 0);
x_cog_out : out std_logic_vector(16 downto 0);
y_cog_out : out std_logic_vector(16 downto 0)
);
end label8Operation;
 
architecture Behavioral of label8Operation is
 
 
signal pointer : std_logic_vector(NO_BITS_CC-1 downto 0) := (others=>'0');
signal fsynch,rsynch : std_logic := '0';
signal Hbuffer_in, Lbuffer_in : std_logic_vector(7 downto 0);
signal Hbuffer_out, Lbuffer_out : std_logic_vector(7 downto 0);
signal outputCodes : std_logic_vector( CODE_WIDTH-1 downto 0 ):= (others=>'0');
signal ip6,ip7,ip8,ip9 : std_logic_vector( CODE_WIDTH-1 downto 0 );
 
begin
 
pdata_out <= outputCodes;
rsync_out <= rsynch;
fsync_out <= fsynch;
ip6 <= outputCodes;
lineBuffer : entity work.line_buffer_Xb
generic map (CODE_WIDTH => CODE_WIDTH, ADDRESS_BITS => NO_BITS_CC)
port map(
idata => outputCodes,
odata => ip7,
pointer => pointer,
ena => rsynch,
clk => pclk );
lblKernel : entity work.label8AndFeatures
generic map( CODE_BITS => CODE_WIDTH, row=> NO_OF_ROWS,col=> NO_OF_COLS)
port map (
ip9 => ip9,
ip8 => ip8,
ip7 => ip7,
ip6 => ip6,
ibin => pbin_in,
pdata_in => data_in,
fsync_in => fsync_in,
fsync_out => fsynch,
pdata_o => outputCodes,
rsync_in => rsync_in,
rsync_out => rsynch,
Reset => reset,
pclk => pclk,
featureDataStrobe => featureDataStrobe,
acknowledge => acknowledge,
cntObjects => cntObjects,
y_cog => y_cog_out,
x_cog => x_cog_out
);
 
process(pclk)
begin
if pclk'event and pclk = '1' then
if rsynch = '1' then
if pointer < NO_OF_COLS-4 then
pointer <= pointer + 1;
else
pointer <= (others=>'0');
end if;
end if;
ip8 <= ip7;
ip9 <= ip8;
end if;
end process;
 
end Behavioral;
 
/image_component_labeling_and_feature_extraction/trunk/ram_denom.vhd
0,0 → 1,55
------------------------------------------------------------------------------------
---- Company:
---- Engineer:
----
---- Create Date: 10:00:30 11/27/2008
---- Design Name:
---- Module Name: ram1w2r - Behavioral
---- Project Name:
---- Target Devices:
---- Tool versions:
---- Description:
----
---- Dependencies:
----
---- Revision:
---- Revision 0.01 - File Created
---- Additional Comments:
----
 
library IEEE;
use IEEE.STD_LOGIC_1164.ALL;
use IEEE.STD_LOGIC_ARITH.ALL;
use IEEE.STD_LOGIC_UNSIGNED.ALL;
 
---- Uncomment the following library declaration if instantiating
---- any Xilinx primitives in this code.
--library UNISIM;
--use UNISIM.VComponents.all;
 
entity ram_denom is
Port ( addrW : in STD_LOGIC_VECTOR (9 downto 0);
din : in STD_LOGIC_VECTOR (18 downto 0);
we : in STD_LOGIC;
addrR : in STD_LOGIC_VECTOR (9 downto 0);
dout : out STD_LOGIC_VECTOR (18 downto 0);
clk : in STD_LOGIC);
end ram_denom;
 
architecture Behavioral of ram_denom is
 
type ram_type is array(1023 downto 0) of std_logic_vector(18 downto 0);
signal ram_array : ram_type:=(others=>(others=>'0'));
 
begin
process(clk) --,ramreset)
begin
if clk'event and clk ='1' then
if we='1' then
ram_array(conv_integer(addrW)) <= din;
end if;
dout <= ram_array(conv_integer(addrR));
end if;
end process;
end Behavioral;
 
/image_component_labeling_and_feature_extraction/trunk/serial_div2.vhd
0,0 → 1,83
library ieee;
use ieee.std_logic_1164.all;
use ieee.std_logic_arith.all;
use ieee.std_logic_unsigned.all;
 
entity serial_div2 is
generic ( M_PP : natural := 34; -- Size of dividend
N_PP : natural := 19; -- Size of divisor
R_PP : natural := 0; -- Size of remainder
S_PP : natural := 0; -- Skip this many bits (known leading zeros)
COUNT_WIDTH_PP : natural := 6; -- 2^COUNT_WIDTH_PP-1 >= (M_PP+R_PP-S_PP-1)
HELD_OUTPUT_PP : natural := 1 -- Set to 1 if stable output should be held
); -- from previous operation, during current operation.
port ( clk_i : in std_logic;
clk_en_i : in std_logic := '1';
rst_i : in std_logic := '0';
divide_i : in std_logic := '1';
dividend_i : in std_logic_vector(M_PP-1 downto 0) := (others => '0');
divisor_i : in std_logic_vector(N_PP-1 downto 0) := (others => '0');
quotient_o : out std_logic_vector(M_PP+R_PP-N_PP+1 downto 0); --17
done_o : out std_logic
);
end serial_div2;
 
architecture Behavioral of serial_div2 is
signal divide_count : std_logic_vector(COUNT_WIDTH_PP-1 downto 0) := (others => '0');
signal divisor_node : std_logic_vector(M_PP+N_PP-1 downto 0);
signal quotient_node : std_logic_vector(M_PP-N_PP+R_PP+1 downto 0);
signal remainder_node : std_logic_vector(M_PP+N_PP-1 downto 0); -- Subtract node has extra "sign" bit
--signal remainder_node2 : std_logic_vector(M_PP-1 downto 0); -- Subtract node has extra "sign" bit
--signal msb_indicate : std_logic ;
 
begin
s_div : process(clk_i)
begin -- s_div
if(clk_i'event and clk_i='1') then
if (rst_i = '1') then
quotient_node <= (others => '0');
divide_count <= (others => '0');
divisor_node <= (others => '0');
remainder_node <= (others => '0');
-- quotient_o <= (others => '0');
done_o <= '0';
-- msb_indicate <= '0';
else
if (clk_en_i = '1') then
if (divide_i = '1') then
done_o <= '0';
-- quotient_o <= (others => '0');
quotient_node <= (others => '0');
divide_count <= (others => '0');
divisor_node(M_PP+N_PP-1 downto M_PP) <= divisor_i;
divisor_node(M_PP-1 downto 0) <= (others => '0');
remainder_node(M_PP+N_PP-1 downto N_PP) <= dividend_i;
remainder_node(N_PP-1 downto 0) <= (others => '0');
-- msb_indicate <= '0';
 
elsif (conv_integer(divide_count) = (M_PP-11) ) then --- works with (-11), no explanation right now
done_o <= '1';
quotient_o <= quotient_node;
else
if (remainder_node > divisor_node) then
remainder_node <= remainder_node - divisor_node;
quotient_node <= quotient_node(M_PP+R_PP-N_PP downto 0) & '1';
else
quotient_node <= quotient_node(M_PP+R_PP-N_PP downto 0) & '0';
end if;
 
-- final shift... TODO
divide_count <= divide_count + 1; -- Advance the counter
divisor_node <= '0' & divisor_node(M_PP +N_PP-1 downto 1);
end if; -- DIVIDE
end if; -- clk_en
end if; -- RST
end if; -- CLK
end process s_div;
-- quotient_o <= quotient_node; -- final shift... TODO
 
end Behavioral;
/image_component_labeling_and_feature_extraction/trunk/mac_module.vhd
0,0 → 1,334
library ieee;
use ieee.std_logic_1164.all;
use IEEE.STD_LOGIC_UNSIGNED.ALL;
use ieee.numeric_std.all;
use ieee.std_logic_arith.all;
 
 
---- Uncomment the following library declaration if instantiating
---- any Xilinx primitives in this code.
library UNISIM;
use UNISIM.VComponents.all;
 
entity mac_module is
generic( CODE_BITS : integer := 10;
ROW : natural := 480;
ROW_BITS : natural := 9;
COL : natural := 640;
COL_BITS : natural := 10);
port (
code : in std_logic_vector(CODE_BITS-1 downto 0);
pdata_in : in std_logic_vector(7 downto 0); -- input greyvalue (0...255)
fsync_in : in std_logic;
rsync_in : in std_logic;
Reset : in std_logic;
pclk : in std_logic;
selectspace : in std_logic;
tablePreset : in std_logic;
compuCode : in STD_LOGIC_VECTOR (9 downto 0);
mergeEnable : in STD_LOGIC;
compute : in STD_LOGIC;
divready_out : out std_logic;
x_cog : out std_logic_vector(16 downto 0);
y_cog : out std_logic_vector (16 downto 0)
);
end mac_module;
 
 
architecture behavioral of mac_module is
 
signal compute_delay, divide_init, done_y, done_x: std_logic; -- control signals for division
signal postx_numerator_stored,posty_numerator_stored,x_numerator_stored,y_numerator_stored,Sx_numerator,Tx_numerator,Sy_numerator,Ty_numerator: std_logic_vector(33 downto 0) := (others => '0');
signal Sdenominator,Tdenominator : std_logic_vector(18 downto 0) := (others => '0'); --denominator
signal Sx_numerator_stored,Tx_numerator_stored,Sy_numerator_stored,Ty_numerator_stored: std_logic_vector(33 downto 0) := (others => '0');
signal Sdenominator_stored,Tdenominator_stored,denominator_stored,postdenominator_stored: std_logic_vector(18 downto 0):= (others => '0');
signal merge_denom_input,denominator_input : std_logic_vector(18 downto 0) := (others => '0');
signal y_numerator_input,merge_ynum_input : std_logic_vector(33 downto 0) := (others => '0');
signal x_numerator_input,merge_xnum_input : std_logic_vector(33 downto 0) := (others => '0');
signal runPreset : std_logic;
 
signal c_count, c_count_delay : std_logic_vector(COL_BITS-1 downto 0) := (others => '0');
signal r_count : std_logic_vector(ROW_BITS-1 downto 0) := (others => '0');
signal rsync_delayed : std_logic;
signal pdata_delayed : std_logic_vector(7 downto 0);
signal prod_x : std_logic_vector(17 downto 0);
signal prod_y : std_logic_vector(16 downto 0);
 
 
signal SaddrR,SaddrW : std_logic_vector(9 downto 0) := (others => '0'); --adress vectors in RAM S
signal TaddrR,TaddrW,macaddrw,mergeaddrw : std_logic_vector(9 downto 0) := (others => '0'); --adress vectors in RAM T
signal readaddr,readaddr_delayed, preaddr : std_logic_vector(9 downto 0) := "0000000000";
signal Twe,Swe,setwe,mergewe,prewe: std_logic := '0'; --control signals for RAM access
signal mergereadaddr, compuCodeDelayed : std_logic_vector(9 downto 0);
signal xNumeratorDelayed, yNumeratorDelayed : std_logic_vector(33 downto 0);
signal denominatorDelayed : std_logic_vector(18 downto 0);
signal mergeEnableDelayed : std_logic;
 
 
--type ppstatetype is (startup1,startup2,startup3,startup4);
--signal ppstate : ppstatetype;
 
 
 
 
begin
 
s_div_y : entity work.serial_div2
-- generic map ( M_PP => 31, N_PP => 17, R_PP => 0, S_PP => 0, COUNT_WIDTH_PP => 5,
--a HELD_OUTPUT_PP => 1 )
PORT MAP(
clk_i => pclk,
clk_en_i => '1',
rst_i => reset,
divide_i => divide_init,
dividend_i => posty_numerator_stored,
divisor_i => postdenominator_stored,
done_o => done_y,
quotient_o => y_cog
);
s_div_x : entity work.serial_div2
-- generic map ( M_PP => 31, N_PP => 17, R_PP => 0, S_PP => 0, COUNT_WIDTH_PP => 5,
--a HELD_OUTPUT_PP => 1 )
PORT MAP(
clk_i => pclk,
clk_en_i => '1',
rst_i => reset,
divide_i => divide_init,
dividend_i => postx_numerator_stored,
divisor_i => postdenominator_stored,
done_o => done_x,
quotient_o => x_cog
);
 
 
ram_xnumS : entity work.ram_num port map (
addrW => SaddrW,
din => Sx_numerator,
we => Swe,
addrR => SaddrR,
dout => Sx_numerator_stored,
clk => pclk);
ram_xnumT : entity work.ram_num port map (
addrW => TaddrW,
din => Tx_numerator,
we => Twe,
addrR => TaddrR,
dout => Tx_numerator_stored,
clk => pclk);
ram_ynumS : entity work.ram_num port map (
addrW => SaddrW,
din => Sy_numerator,
we => Swe,
addrR => SaddrR,
dout => Sy_numerator_stored,
clk => pclk);
 
ram_ynumT : entity work.ram_num port map (
addrW => TaddrW,
din => Ty_numerator,
we => Twe,
addrR => TaddrR,
dout => Ty_numerator_stored,
clk => pclk);
ram_denomS : entity work.ram_denom port map (
addrW => SaddrW,
din => Sdenominator,
we => Swe,
addrR => SaddrR,
dout => Sdenominator_stored,
clk => pclk);
ram_denomT : entity work.ram_denom port map (
addrW => TaddrW,
din => Tdenominator,
we => Twe,
addrR => TaddrR,
dout => Tdenominator_stored,
clk => pclk);
 
 
--=============== Multiplexer statements for selecting memories for interlieving of table accesses =======
--=============== selectSpace is the signal that controls interlieveing per frames =======
 
---------- Memory inputs -----------------------------
 
 
 
Swe <= Setwe when selectspace ='0' else
mergewe when runPreset = '0' else
prewe;
Sdenominator <= denominator_input when selectspace ='0' else
merge_denom_input when runPreset = '0' else
(others => '0');
Sx_numerator <= x_numerator_input when selectspace='0' else
merge_xnum_input when runPreset = '0' else
(others => '0');
Sy_numerator <= y_numerator_input when selectspace='0' else
merge_ynum_input when runPreset = '0' else
(others => '0');
SaddrR <= readaddr when selectspace='0' else
mergereadaddr;
Saddrw <= macaddrw when selectspace = '0' else
mergeaddrw when runPreset = '0' else
preaddr;
 
Twe <= Setwe when selectspace='1' else
mergewe when runPreset = '0' else
prewe;
Tdenominator <= denominator_input when selectspace='1' else
merge_denom_input when runPreset = '0' else
(others => '0');
Tx_numerator <= x_numerator_input when selectspace='1' else
merge_xnum_input when runPreset = '0' else
(others => '0');
Ty_numerator <= y_numerator_input when selectspace='1' else
merge_ynum_input when runPreset = '0' else
(others => '0');
TaddrR <= readaddr when selectspace='1' else
mergereadaddr;
Taddrw <= macaddrw when selectspace = '1' else
mergeaddrw when runPreset = '0' else
preaddr;
 
 
-------------------------------------------------------
---------- Memory outputs ----------------------------
 
x_numerator_stored <= Sx_numerator_stored when selectSpace = '0' else
Tx_numerator_stored;
y_numerator_stored <= Sy_numerator_stored when selectSpace = '0' else
Ty_numerator_stored;
denominator_stored <= Sdenominator_stored when selectSpace = '0' else
Tdenominator_stored;
postx_numerator_stored <= Sx_numerator_stored when selectSpace = '1' else
Tx_numerator_stored;
posty_numerator_stored <= Sy_numerator_stored when selectSpace = '1' else
Ty_numerator_stored;
postdenominator_stored <= Sdenominator_stored when selectSpace = '1' else
Tdenominator_stored;
 
-------------------------------------------------------
-- Signal mappings
 
mergereadaddr <= compuCode;
mergeaddrw <= compuCodeDelayed;
mergewe <= mergeEnableDelayed;
merge_denom_input <= postdenominator_stored + denominatorDelayed;
merge_xnum_input <= postx_numerator_stored + xNumeratorDelayed;
merge_ynum_input <= posty_numerator_stored + yNumeratorDelayed;
 
 
divready_out <= done_x and done_y;
--divide_init <= compute or compute_delay;
divide_init <= compute_delay;
 
 
mac: process(pclk,Reset)
 
begin
if reset = '1' then
SetWe <= '0';
y_numerator_input <= (others=>'0');
denominator_input <= (others=>'0');
x_numerator_input <= (others=>'0');
c_count <= (others=>'0');
r_count <= (others=>'0');
elsif fsync_in = '1' then
c_count <= (others => '0');
r_count <= (others => '0');
elsif pclk'event and pclk = '1' then
if rsync_in = '0' and rsync_delayed = '1' then
c_count <= (others => '0');
r_count <= r_count + 1;
elsif rsync_in = '1' then
c_count <= c_count + 1; --increment coloumn counter
end if;
if readaddr_delayed = macaddrw then
denominator_input <= denominator_input + pdata_delayed;
x_numerator_input <= x_numerator_input + prod_x;
y_numerator_input <= y_numerator_input + prod_y;
else
denominator_input <= denominator_stored + pdata_delayed;
x_numerator_input <= x_numerator_stored + prod_x;
y_numerator_input <= y_numerator_stored + prod_y;
end if;
if readaddr_delayed = 0 then
denominator_input <= (others=>'0');
x_numerator_input <= (others=>'0');
y_numerator_input <= (others=>'0');
SetWe <= '0';
else
SetWe <= '1';
end if;
prod_x <= pdata_in * c_count_delay;
prod_y <= pdata_in * r_count;
rsync_delayed <= rsync_in;
readaddr_delayed <= readaddr;
macaddrw <= readaddr_delayed;
pdata_delayed <= pdata_in;
c_count_delay <= c_count;
end if; -- pclk'event and pclk = '1'
end process mac;
 
readaddr <= code;
 
 
merge: process (pclk, reset)
begin
if reset = '1' then
 
compuCodeDelayed <= (others=>'0');
elsif pclk'event and pclk = '1' then
compuCodeDelayed <= compuCode;
xNumeratorDelayed <= postx_numerator_stored;
yNumeratorDelayed <= posty_numerator_stored;
denominatorDelayed <= postdenominator_stored;
mergeEnableDelayed <= mergeEnable;
compute_delay <= compute;
end if;
end process merge;
 
preset : process (pclk, reset)
begin
if reset = '1' then
preaddr <= "0000000000";
runPreset <= '1';
elsif pclk'event and pclk = '1' then
prewe <= '0';
if tablePreset = '1' then
preaddr <= (others => '0');
runPreset <= '1';
prewe <= '1';
elsif preaddr = "1111111111" then
preaddr <= "1111111111";
runPreset <= '0';
else
prewe <= '1';
preaddr <= preaddr +1;
end if;
end if;
end process preset;
end behavioral;
/image_component_labeling_and_feature_extraction/trunk/equivalenceTable.vhd
0,0 → 1,383
 
----------------------------------------------------------------------------------
-- Company:
-- Engineer:
--
-- Create Date: 22:24:37 10/25/2008
-- Design Name:
-- Module Name: equivalenceTable - Struct
-- Project Name:
-- Target Devices:
-- Tool versions:
-- Description:
--
-- Dependencies:
--
-- Revision:
-- Revision 0.01 - File Created
-- Additional Comments:
--
----------------------------------------------------------------------------------
library IEEE;
use IEEE.STD_LOGIC_1164.ALL;
use IEEE.STD_LOGIC_ARITH.ALL;
use IEEE.STD_LOGIC_UNSIGNED.ALL;
 
---- Uncomment the following library declaration if instantiating
---- any Xilinx primitives in this code.
--library UNISIM;
--use UNISIM.VComponents.all;
 
entity equivalenceTable is
Port ( a : in STD_LOGIC_VECTOR (9 downto 0);
b : in STD_LOGIC_VECTOR (9 downto 0);
c : in STD_LOGIC_VECTOR (9 downto 0);
d : in STD_LOGIC_VECTOR (9 downto 0);
we : in STD_LOGIC;
readAddr : in STD_LOGIC_VECTOR (9 downto 0);
dout : out STD_LOGIC_VECTOR (9 downto 0);
equalcnt : out STD_LOGIC_VECTOR (9 downto 0);
fsync : in STD_LOGIC;
tableReady : out STD_LOGIC;
tablePreset : in STD_LOGIC;
reset : in STD_LOGIC;
clk : in STD_LOGIC;
space : out STD_LOGIC;
SetdoutrefA : out std_logic_vector(9 downto 0);--asynchronous out put of memory
SetdoutrefB : out std_logic_vector(9 downto 0)
);
end equivalenceTable;
 
architecture Struct of equivalenceTable is
 
signal SaddrRA,SdoutA,SaddrRB,SdoutB,SaddrW,Sdin : std_logic_vector(9 downto 0);
signal TaddrRA,TdoutA,TaddrRB,TdoutB,TaddrW,Tdin : std_logic_vector(9 downto 0);
signal Twe,Swe,eqready,spc,selectSpace : std_logic := '0';
signal Saddrefa : STD_LOGIC_VECTOR (9 downto 0);
signal Saddrefb : STD_LOGIC_VECTOR (9 downto 0);
signal Sdoutrefa : STD_LOGIC_VECTOR (9 downto 0);
signal Sdoutrefb: STD_LOGIC_VECTOR (9 downto 0);
signal Taddrefa : STD_LOGIC_VECTOR (9 downto 0);
signal Taddrefb : STD_LOGIC_VECTOR (9 downto 0);
signal Tdoutrefa : STD_LOGIC_VECTOR (9 downto 0);
signal Tdoutrefb : STD_LOGIC_VECTOR (9 downto 0);
signal SetAddrW,PostAddrW,PreAddrW : std_logic_vector(9 downto 0);
signal PostAddrR,PostAddrRDelayed : std_logic_vector(9 downto 0);
signal SetDoutA,SetDoutB,PostDout : std_logic_vector(9 downto 0); signal SetDin, PostDin, PreDin : std_logic_vector(9 downto 0);
 
signal SetWe,PostWe,PreWe : std_logic;
 
signal a_delay1,b_delay1 : std_logic_vector(9 downto 0);
 
type ppstatetype is (idle,startup1,startup2,indexing,toFindEqual,findEqual);
signal ppstate : ppstatetype;
signal tblwrite : std_logic_vector(9 downto 0); -- Used for debugging purposes
 
type ByteT is (c0,c1,c2,c3,c4,c5,c6,c7,c8,c9,c10,c11,c12,c13,c14,c15,c16,c17,c18,
c19,c20,c21,c22,c23,c24,c25,c26,c27,c28,c29,c30,c31,c32,c33,c34,
c35,c36,c37,c38,c39,c40,c41,c42,c43,c44,c45,c46,c47,c48,c49,c50,
c51,c52,c53,c54,c55,c56,c57,c58,c59,c60,c61,c62,c63,c64,c65,c66,
c67,c68,c69,c70,c71,c72,c73,c74,c75,c76,c77,c78,c79,c80,c81,c82,
c83,c84,c85,c86,c87,c88,c89,c90,c91,c92,c93,c94,c95,c96,c97,c98,
c99,c100,c101,c102,c103,c104,c105,c106,c107,c108,c109,c110,c111,
c112,c113,c114,c115,c116,c117,c118,c119,c120,c121,c122,c123,c124,
c125,c126,c127,c128,c129,c130,c131,c132,c133,c134,c135,c136,c137,
c138,c139,c140,c141,c142,c143,c144,c145,c146,c147,c148,c149,c150,
c151,c152,c153,c154,c155,c156,c157,c158,c159,c160,c161,c162,c163,
c164,c165,c166,c167,c168,c169,c170,c171,c172,c173,c174,c175,c176,
c177,c178,c179,c180,c181,c182,c183,c184,c185,c186,c187,c188,c189,
c190,c191,c192,c193,c194,c195,c196,c197,c198,c199,c200,c201,c202,
c203,c204,c205,c206,c207,c208,c209,c210,c211,c212,c213,c214,c215,
c216,c217,c218,c219,c220,c221,c222,c223,c224,c225,c226,c227,c228,
c229,c230,c231,c232,c233,c234,c235,c236,c237,c238,c239,c240,c241,
c242,c243,c244,c245,c246,c247,c248,c249,c250,c251,c252,c253,c254,c255);
subtype Byte is ByteT;
type ByteFileType is file of Byte;
file outfile : ByteFileType open write_mode is "Labels.bin";
 
begin
 
ramS : entity work.ram1w2r port map (
addrefa => Saddrefa,
addrefb=> Saddrefb,
doutrefa => Sdoutrefa,
doutrefb => Sdoutrefb,
addrW => SaddrW,
din => Sdin,
we => Swe,
addrRA => SaddrRA,
doutA => SdoutA,
addrRB => SaddrRB,
doutB => SdoutB,
clk => clk);
 
ramT : entity work.ram1w2r port map (
addrefa => Taddrefa,
addrefb=> Taddrefb,
doutrefa => Tdoutrefa,
doutrefb => Tdoutrefb,
addrW => TaddrW,
din => Tdin,
we => Twe,
addrRA => TaddrRA,
doutA => TdoutA,
addrRB => TaddrRB,
doutB => TdoutB,
clk => clk);
--=============== Multiplexer statements for selecting memories for interlieving of table accesses =======
--=============== selectSpace is the signal that controls interlieveing per frames =======
 
---------- Memory inputs -----------------------------
SaddrRA <= c when selectSpace ='0' else
PostAddrR;
SaddrRB <= d when selectSpace = '0' else
readAddr;
SaddrW <= SetAddrW when selectSpace='0' else
PostAddrW when eqready='0' else
PreAddrW;
Sdin <= SetDin when selectSpace = '0' else
PostDin when eqready = '0' else
PreDin;
Swe <= SetWe when selectSpace='0' else
PostWe when eqready = '0' else
PreWe;
Saddrefa <= a when selectSpace = '0' ;
Saddrefb <= b when selectSpace = '0' ;
TaddrRA <= c when selectSpace ='1' else
PostAddrR;
TaddrRB <= d when selectSpace = '1' else
readAddr;
TaddrW <= SetAddrW when selectSpace='1' else
PostAddrW when eqready='0' else
PreAddrW;
Tdin <= SetDin when selectSpace = '1' else
PostDin when eqready = '0' else
PreDin;
Twe <= SetWe when selectSpace='1' else
PostWe when eqready = '0' else
PreWe;
Taddrefa <= a when selectSpace = '1';
Taddrefb <= b when selectSpace = '1' ;
-------------------------------------------------------
---------- Memory outputs ----------------------------
 
SetDoutA <= SdoutA when selectSpace = '0' else
TdoutA;
SetDoutB <= SdoutB when selectSpace = '0' else
TdoutB;
PostDout <= SdoutA when selectSpace = '1' else
TdoutA;
dout <= SdoutB when selectSpace = '1' else
TdoutB;
SetdoutrefA <= Sdoutrefa when selectSpace = '0' else
Tdoutrefa;
SetdoutrefB <= Sdoutrefb when selectSpace = '0' else
Tdoutrefb;
-------------------------------------------------------
 
--====================== Other signal mappings =========================================================
tableReady <= eqready;
space <= selectspace;
--======================================================================================================
 
EqualSet : process(clk,reset)
 
variable contentA, contentB : std_logic_vector(9 downto 0);
begin
if reset = '1' then
Setwe <= '0';
a_delay1 <= (others=>'0');
b_delay1 <= (others=>'0');
tblwrite <= (others=>'0');
elsif clk'event and clk = '1' then
if fsync = '1' then
-- write(outfile, ByteT'val(0));
-- write(outfile, ByteT'val(0));
-- write(outfile, ByteT'val(0));
end if;
if we = '1' or fsync = '1' then
if a_delay1 = SetaddrW and Setwe = '1' then
contentA := Setdin;
else
contentA := SetDoutA;
end if;
if b_delay1 = SetaddrW and Setwe = '1' then
contentB := Setdin;
else
contentB := SetDoutB;
end if;
if contentA > contentB and a_delay1/= 0 and b_delay1/= 0 then
SetaddrW <= contentA; -- Position a_store is overwritten by the smaller label in b_out
Setdin <= contentB;
Setwe <= '1';
tblwrite <= tblwrite + 1;
-- write(outfile, ByteT'val(ieee.numeric_std.To_Integer(ieee.numeric_std.unsigned(contentA))));
-- write(outfile, ByteT'val(ieee.numeric_std.To_Integer(ieee.numeric_std.unsigned(contentB))));
--write(outfile, ByteT'val(0));
elsif contentB > contentA and a_delay1/=0 and b_delay1/= 0 then
SetaddrW <= contentB; -- Position b_store is overwritten by the smaller label in a_out
Setdin <= contentA;
Setwe <= '1';
tblwrite <= tblwrite + 1;
-- write(outfile, ByteT'val(ieee.numeric_std.To_Integer(ieee.numeric_std.unsigned(contentB))));
-- write(outfile, ByteT'val(ieee.numeric_std.To_Integer(ieee.numeric_std.unsigned(contentA))));
--write(outfile, ByteT'val(0));
else
Setwe <= '0';
end if;
else
Setwe <= '0';
end if;
if(fsync = '1' ) then
a_delay1 <= (others=>'0');
b_delay1 <= (others=>'0');
tblwrite <= (others=>'0');
elsif we = '1' then
a_delay1 <= c;
b_delay1 <= d;
end if;
end if;
 
end process EqualSet;
PostProc : process(clk,reset)
variable eqindex,aindex,bindex,equcnt : std_logic_vector(9 downto 0);
variable incIndex : std_logic := '0';
variable scount : std_logic_vector(6 downto 0);
begin
if reset = '1' then
spc <= '0';
selectSpace <= '0';
eqready <= '1';
eqindex := (others=>'0');
PostAddrR <= eqindex;
PostWe <= '0';
incIndex := '0';
equcnt := (others=>'0');
scount := (others=>'0');
elsif clk'event and clk = '1' then
selectSpace <= spc;
case ppstate is
when idle=>
if fsync = '1' then
ppstate <= startup1;
PostAddrR <= eqindex;
eqready <= '0';
eqindex := (others=>'0');
spc <= not spc;
equcnt := (others=>'0');
scount := (others=>'0');
end if;
PostWe <= '0';
when startup1 =>
ppstate <= startup2;
PostAddrR <= eqindex;
PostWe <= '0';
when startup2 =>
scount := (others=>'0');
ppstate <= indexing;
PostAddrR <= eqindex;
PostWe <= '0';
when indexing =>
if fsync = '1' then
ppstate <= startup1;
PostAddrR <= eqindex;
eqready <= '0';
eqindex := (others=>'0');
spc <= not spc;
PostWe <= '0';
elsif eqindex = 1023 then
ppstate <= idle;
eqready <= '1';
PostWe <= '0';
elsif PostAddrRDelayed /= PostDout and PostDout /= 0 then
aindex := PostAddrRDelayed;
bindex := PostDout;
PostAddrR <= bindex;
equcnt := equcnt + 1;
ppstate <= toFindEqual;
if incIndex = '1' then
eqindex := eqindex + 1;
else
incIndex := '1';
end if;
elsif eqindex < 1023 then
eqindex := eqindex + 1;
PostAddrR <= eqindex;
incIndex := '0';
else
eqready <= '1';
equalcnt <= equcnt;
ppstate <= idle;
end if;
PostWe <= '0';
when toFindEqual =>
ppstate <= FindEqual;
PostWe <= '0';
when findEqual =>
if fsync = '1' then
ppstate <= startup1;
PostAddrR <= eqindex;
eqready <= '0';
eqindex := (others=>'0');
spc <= not spc;
PostWe <= '0';
elsif PostAddrRDelayed /= PostDout and PostDout /= 0 and scount < 127 then
bindex := PostDout;
PostAddrR <= bindex;
scount := scount + 1;
PostWe <= '0';
else
PostAddrW <= aindex;
PostDin <= bindex;
PostWe <= '1';
PostAddrR <= eqindex;
ppstate <= startup2;
end if;
when others =>
ppstate <= idle;
end case;
PostAddrRDelayed <= PostAddrR;
end if;
end process PostProc;
PreSet : process(clk,reset)
variable ind : std_logic_vector(9 downto 0);
constant maxind : std_logic_vector(9 downto 0):= (others=>'1');
begin
if reset='1' then
ind := maxind;
PreWe <= '0';
elsif clk'event and clk='1' then
if tablePreset = '1' and ind = maxind then
ind := (others=>'0');
PreAddrW <= ind;
PreDin <= ind;
PreWe <= '1';
elsif ind < maxind then
ind := ind + 1;
PreAddrW <= ind;
PreDin <= ind;
PreWe <= '1';
else
PreWe <= '0';
end if;
end if;
end process PreSet;
end Struct;
 
/image_component_labeling_and_feature_extraction/trunk/line_bufferXB.vhd
0,0 → 1,70
------------------------------------------------------------------------------------
-- Company:
 
--
-- Create Date: 14:12:25 04/11/2008
-- Design Name:
-- Module Name: line_buffer_Xb - Behavioral
-- Project Name:
-- Target Devices:
-- Tool versions:
-- Description:
--
-- Dependencies:
--
-- Revision:
-- Revision 0.01 - File Created
-- Additional Comments:
--
----------------------------------------------------------------------------------
library IEEE;
use IEEE.STD_LOGIC_1164.ALL;
use IEEE.STD_LOGIC_ARITH.ALL;
use IEEE.STD_LOGIC_UNSIGNED.ALL;
 
---- Uncomment the following library declaration if instantiating
---- any Xilinx primitives in this code.
library UNISIM;
use UNISIM.VComponents.all;
 
-- This entity constitutes a FIFO-register that can be used for storage of line delays
-- for image processing. It is implemented as a circular buffer using one single pointer.
-- The address for this pointer must be driven externally by the interface signal "pointer".
-- Data is first read from the memory location referenced by "pointer" to "odata" on the falling
-- clock edge and then data is written to the same location from "idata" on the rising clock edge.
-- An additional register on the data output is clocked on the rising clockedge such that data output
-- appears on the output on rising edge allthough it is read on the falling edge.
-- The maximum size of the final line buffer is 1025 by 8 bits. The size of this line buffer can be
-- any size ranging from 1 to 1025 depending on the sequence of addressses driven on "pointer".
 
entity line_buffer_Xb is
generic (
CODE_WIDTH : integer := 10;
ADDRESS_BITS : integer := 10
);
Port ( idata : in STD_LOGIC_VECTOR (CODE_WIDTH-1 downto 0); -- input data port
odata : out STD_LOGIC_VECTOR (CODE_WIDTH-1 downto 0); -- output data port
pointer : in STD_LOGIC_VECTOR (ADDRESS_BITS-1 downto 0); -- reference to a memory location
ena : in STD_LOGIC; -- must be high to enable shifting of data
clk : in STD_LOGIC);
end line_buffer_Xb;
 
architecture behave of line_buffer_Xb is
 
type ram_type is array((2**ADDRESS_BITS)-1 downto 0) of std_logic_vector(CODE_WIDTH-1 downto 0);
signal ram_array : ram_type:=(others=>(others=>'0'));
begin
 
process(clk)
begin
if clk'event and clk ='1' then
odata <= ram_array(conv_integer(pointer));
if ena='1' then
ram_array(conv_integer(pointer)) <= idata;
end if;
end if;
end process;
end behave;
 
 
/image_component_labeling_and_feature_extraction/trunk/img_testbench2_08bits.vhd
0,0 → 1,170
library ieee;
use ieee.std_logic_1164.all;
use ieee.std_logic_arith.all;
use ieee.std_logic_unsigned.all;
use std.textio.all;
 
entity img_testbench is
port (
pclk_i : in std_logic;
reset_i : in std_logic;
fsync_i : in std_logic;
rsync_i : in std_logic;
pdata_i : in std_logic_vector(7 downto 0);
cols_o : out std_logic_vector(15 downto 0);
rows_o : out std_logic_vector(15 downto 0);
col_o : out std_logic_vector(15 downto 0);
row_o : out std_logic_vector(15 downto 0);
rsync_o : out std_logic;
fsync_o : out std_logic;
pdata_o : out std_logic_vector(7 downto 0) );
end img_testbench;
 
architecture main of img_testbench is
type ByteT is (c0,c1,c2,c3,c4,c5,c6,c7,c8,c9,c10,c11,c12,c13,c14,c15,c16,c17,c18,
c19,c20,c21,c22,c23,c24,c25,c26,c27,c28,c29,c30,c31,c32,c33,c34,
c35,c36,c37,c38,c39,c40,c41,c42,c43,c44,c45,c46,c47,c48,c49,c50,
c51,c52,c53,c54,c55,c56,c57,c58,c59,c60,c61,c62,c63,c64,c65,c66,
c67,c68,c69,c70,c71,c72,c73,c74,c75,c76,c77,c78,c79,c80,c81,c82,
c83,c84,c85,c86,c87,c88,c89,c90,c91,c92,c93,c94,c95,c96,c97,c98,
c99,c100,c101,c102,c103,c104,c105,c106,c107,c108,c109,c110,c111,
c112,c113,c114,c115,c116,c117,c118,c119,c120,c121,c122,c123,c124,
c125,c126,c127,c128,c129,c130,c131,c132,c133,c134,c135,c136,c137,
c138,c139,c140,c141,c142,c143,c144,c145,c146,c147,c148,c149,c150,
c151,c152,c153,c154,c155,c156,c157,c158,c159,c160,c161,c162,c163,
c164,c165,c166,c167,c168,c169,c170,c171,c172,c173,c174,c175,c176,
c177,c178,c179,c180,c181,c182,c183,c184,c185,c186,c187,c188,c189,
c190,c191,c192,c193,c194,c195,c196,c197,c198,c199,c200,c201,c202,
c203,c204,c205,c206,c207,c208,c209,c210,c211,c212,c213,c214,c215,
c216,c217,c218,c219,c220,c221,c222,c223,c224,c225,c226,c227,c228,
c229,c230,c231,c232,c233,c234,c235,c236,c237,c238,c239,c240,c241,
c242,c243,c244,c245,c246,c247,c248,c249,c250,c251,c252,c253,c254,c255);
subtype Byte is ByteT;
type ByteFileType is file of Byte;
file infile : ByteFileType open read_mode is "test1.bmp";
file outfile : ByteFileType open write_mode is "result_08bits.bmp";
-- integer to bit_vector conversion
function int2bit_vec(A: integer; SIZE: integer) return BIT_VECTOR is
variable RESULT : BIT_VECTOR(SIZE-1 DOWNTO 0);
variable TMP : integer;
begin
TMP := A;
for i in 0 to SIZE - 1 loop
if TMP mod 2 = 1 then RESULT(i) := '1';
else RESULT(i) := '0';
end if;
TMP := TMP / 2;
end loop;
return RESULT;
end;
 
begin -- main
 
img_read : process (pclk_i)
variable pixelB : Byte;
variable pixelG : Byte;
variable pixelR : Byte;
variable pixel : Byte;
variable pixel1 : REAL;
variable cols : std_logic_vector(15 downto 0);
variable rows : std_logic_vector(15 downto 0);
variable col : std_logic_vector(15 downto 0);
variable row : std_logic_vector(15 downto 0);
variable cnt : integer;
variable rsync : std_logic := '0';
variable stop : std_logic;
variable pixptr : std_logic_vector(19 downto 0) := (others => '0');
type videomemtype is array (1048575 downto 0) of std_logic_vector(7 downto 0);
variable videomem : videomemtype := (others=> (others=>'0'));
begin -- process img_read
if (reset_i = '1') then
pdata_o <= (others => '0');
col := (others => '0');
row := (others => '0');
for i in 0 to 53 loop -- read header infos
read(infile, pixel);
write(outfile, pixel);
case i is
when 18 => -- 1st byte of cols
cols(7 downto 0 ) := To_Stdlogicvector(int2bit_vec(ByteT'pos(pixel), 8));
when 19 => -- 2nd byte of cols
cols(15 downto 8) := To_Stdlogicvector(int2bit_vec(ByteT'pos(pixel), 8));
when 22 => -- 1st byte of rows
rows(7 downto 0 ) := To_Stdlogicvector(int2bit_vec(ByteT'pos(pixel), 8));
when 23 => -- 2nd byte of rows
rows(15 downto 8) := to_Stdlogicvector(int2bit_vec(ByteT'pos(pixel), 8));
when 24 => -- do important things
cols_o <= cols;
rows_o <= rows;
cols := cols - 1;
rows := rows - 1;
when others =>
null;
end case;
end loop; -- i
rsync := '1';
cnt := 10;
stop := '0';
elsif (pclk_i'event and pclk_i = '1') then
rsync_o <= rsync;
if rsync = '1' then
if row = "0000000000000000" and col = "0000000000000000" then
fsync_o <= '1';
pixptr := (others => '0');
else
fsync_o <= '0';
end if;
if stop = '0' then
read(infile, pixelB); -- B
read(infile, pixelG); -- G
read(infile, pixelR); -- R
pixel1 := (ByteT'pos(pixelB)*0.11) + (ByteT'pos(pixelR)*0.3) + (ByteT'pos(pixelG)*0.59);
pdata_o <= CONV_STD_LOGIC_VECTOR(INTEGER(pixel1), 8);
videomem(conv_integer(pixptr)) := CONV_STD_LOGIC_VECTOR(INTEGER(pixel1), 8);
pixptr := pixptr + 1;
col_o <= col;
row_o <= row;
else
pdata_o <= videomem(conv_integer(pixptr));
pixptr := pixptr + 1;
end if;
if col = cols then
col := (others => '0');
rsync := '0';
if row = rows then
File_Close(infile);
stop := '1';
row := (others=>'0'); -- This line was added by Benny
else
row := row + 1;
end if; -- row
else
col := col + 1;
end if; -- col
else -- rsync
if cnt > 0 then
cnt := cnt -1;
else
cnt := 10; -- Can be changed from 10 to 300 to get correct frame speed timing
rsync := '1';
end if;
pdata_o <= (others => 'X');
end if; -- rsync
if rsync_i = '1' then
write(outfile, ByteT'val(ieee.numeric_std.To_Integer(ieee.numeric_std.unsigned(pdata_i)))); --, pixel);
write(outfile, ByteT'val(ieee.numeric_std.To_Integer(ieee.numeric_std.unsigned(pdata_i)))); --, pixel);
write(outfile, ByteT'val(ieee.numeric_std.To_Integer(ieee.numeric_std.unsigned(pdata_i)))); --, pixel);
end if; -- rsync_i
end if; -- clk
end process img_read;
end main;
/image_component_labeling_and_feature_extraction/trunk/topLevel.ucf
0,0 → 1,211
## PINOUT AND IO DRIVE CHARACTERISTICS FOR THE LEFT LOW SPEED
## EXPANSION PORT OF THE XUP-V2PRO DEVELOPMENT SYSTEM
## REVISION C PRINTED CIRCUIT BOARD DEC 8 2004
 
NET "sda" LOC = "R6" ;
NET "sclk" LOC = "R5" ;
NET "rst" LOC = "AG5";
 
## EXPANSION J1
 
NET "TC<0>" LOC = "K2";
NET "TC<1>" LOC = "L2";
NET "TC<2>" LOC = "N8";
NET "TC<3>" LOC = "N7";
NET "TC<4>" LOC = "K4";
NET "TC<5>" LOC = "K3";
NET "TC<6>" LOC = "L1";
NET "TC<7>" LOC = "M1";
NET "TC<8>" LOC = "N6";
NET "TC<9>" LOC = "N5";
 
### EXPANSION J2
NET "hsync_i" LOC = "R2"; #NET "hsync" IOSTANDARD = LVTTL | DIFF_TERM = TRUE;
NET "vsync_i" LOC = "T2"; #NET "vsync" IOSTANDARD = LVTTL | DIFF_TERM = TRUE;
NET "pclk_i" LOC = "R4"; #NET "pclk" IOSTANDARD = LVTTL | DIFF_TERM = TRUE;
NET "data_i<0>" LOC = "P8"; #NET "d0" IOSTANDARD = LVTTL | DIFF_TERM = TRUE;
NET "data_i<1>" LOC = "P7"; #NET "d1" IOSTANDARD = LVTTL | DIFF_TERM = TRUE;
NET "data_i<2>" LOC = "N4"; #NET "d2" IOSTANDARD = LVTTL | DIFF_TERM = TRUE;
NET "data_i<3>" LOC = "N3"; #NET "d3" IOSTANDARD = LVTTL | DIFF_TERM = TRUE;
NET "data_i<4>" LOC = "P3"; #NET "d4" IOSTANDARD = LVTTL | DIFF_TERM = TRUE;
NET "data_i<5>" LOC = "P2"; #NET "d6" IOSTANDARD = LVTTL | DIFF_TERM = TRUE;
NET "data_i<6>" LOC = "R8"; #NET "d5" IOSTANDARD = LVTTL | DIFF_TERM = TRUE;
NET "data_i<7>" LOC = "R7"; #NET "d7" IOSTANDARD = LVTTL | DIFF_TERM = TRUE;
 
### SWITCHES
NET "SW<0>" LOC = "AC11";
NET "SW<1>" LOC = "AD11";
NET "SW<2>" LOC = "AF8";
NET "SW<3>" LOC = "AF9";
 
NET "SW<0>" IOSTANDARD = LVCMOS25;
NET "SW<1>" IOSTANDARD = LVCMOS25;
NET "SW<2>" IOSTANDARD = LVCMOS25;
NET "SW<3>" IOSTANDARD = LVCMOS25;
 
### LEDS
 
NET "LED<0>" LOC = "AC4";
NET "LED<1>" LOC = "AC3";
NET "LED<2>" LOC = "AA6";
NET "LED<3>" LOC = "AA5";
 
### RS232
 
NET "RS232_TX_DATA" LOC = "AE7";
NET "RS232_DSR_OUT" LOC = "AD10";
NET "RS232_CTS_OUT" LOC = "AE8";
NET "RS232_RTS_IN" LOC = "AK8";
 
NET "RS232_TX_DATA" IOSTANDARD = LVCMOS25;
NET "RS232_DSR_OUT" IOSTANDARD = LVCMOS25;
NET "RS232_CTS_OUT" IOSTANDARD = LVCMOS25;
NET "RS232_RTS_IN" IOSTANDARD = LVCMOS25;
 
NET "RS232_TX_DATA" DRIVE = 8;
NET "RS232_DSR_OUT" DRIVE = 8;
NET "RS232_CTS_OUT" DRIVE = 8;
 
NET "RS232_TX_DATA" SLEW = SLOW;
NET "RS232_DSR_OUT" SLEW = SLOW;
NET "RS232_CTS_OUT" SLEW = SLOW;
 
 
## PINOUT AND IO DRIVE CHARACTERISTICS FOR THE XSGA
## VIDEO OUTPUT OF THE XUP-V2PRO DEVELOPMENT SYSTEM
## REVISION C PRINTED CIRCUIT BOARD DEC 8 2004
 
NET "VGA_VSYNCH" LOC = "D11";
NET "VGA_HSYNCH" LOC = "B8";
NET "VGA_OUT_BLANK_Z" LOC = "A8";
NET "VGA_COMP_SYNCH" LOC = "G12";
NET "VGA_OUT_PIXEL_CLOCK" LOC = "H12";
 
NET "VGA_OUT_RED[7]" LOC = "H10";
NET "VGA_OUT_RED[6]" LOC = "C7";
NET "VGA_OUT_RED[5]" LOC = "D7";
NET "VGA_OUT_RED[4]" LOC = "F10";
NET "VGA_OUT_RED[3]" LOC = "F9";
NET "VGA_OUT_RED[2]" LOC = "G9";
NET "VGA_OUT_RED[1]" LOC = "H9";
NET "VGA_OUT_RED[0]" LOC = "G8";
 
NET "VGA_OUT_GREEN[7]" LOC = "E11";
NET "VGA_OUT_GREEN[6]" LOC = "G11";
NET "VGA_OUT_GREEN[5]" LOC = "H11";
NET "VGA_OUT_GREEN[4]" LOC = "C8";
NET "VGA_OUT_GREEN[3]" LOC = "D8";
NET "VGA_OUT_GREEN[2]" LOC = "D10";
NET "VGA_OUT_GREEN[1]" LOC = "E10";
NET "VGA_OUT_GREEN[0]" LOC = "G10";
 
NET "VGA_OUT_BLUE[7]" LOC = "E14";
NET "VGA_OUT_BLUE[6]" LOC = "D14";
NET "VGA_OUT_BLUE[5]" LOC = "D13";
NET "VGA_OUT_BLUE[4]" LOC = "C13";
NET "VGA_OUT_BLUE[3]" LOC = "J15";
NET "VGA_OUT_BLUE[2]" LOC = "H15";
NET "VGA_OUT_BLUE[1]" LOC = "E15";
NET "VGA_OUT_BLUE[0]" LOC = "D15";
 
NET "VGA_OUT_BLUE[0]" IOSTANDARD = LVTTL;
NET "VGA_OUT_BLUE[1]" IOSTANDARD = LVTTL;
NET "VGA_OUT_BLUE[2]" IOSTANDARD = LVTTL;
NET "VGA_OUT_BLUE[3]" IOSTANDARD = LVTTL;
NET "VGA_OUT_BLUE[4]" IOSTANDARD = LVTTL;
NET "VGA_OUT_BLUE[5]" IOSTANDARD = LVTTL;
NET "VGA_OUT_BLUE[6]" IOSTANDARD = LVTTL;
NET "VGA_OUT_BLUE[7]" IOSTANDARD = LVTTL;
 
NET "VGA_OUT_GREEN[0]" IOSTANDARD = LVTTL;
NET "VGA_OUT_GREEN[1]" IOSTANDARD = LVTTL;
NET "VGA_OUT_GREEN[2]" IOSTANDARD = LVTTL;
NET "VGA_OUT_GREEN[3]" IOSTANDARD = LVTTL;
NET "VGA_OUT_GREEN[4]" IOSTANDARD = LVTTL;
NET "VGA_OUT_GREEN[5]" IOSTANDARD = LVTTL;
NET "VGA_OUT_GREEN[6]" IOSTANDARD = LVTTL;
NET "VGA_OUT_GREEN[7]" IOSTANDARD = LVTTL;
 
NET "VGA_OUT_RED[0]" IOSTANDARD = LVTTL;
NET "VGA_OUT_RED[1]" IOSTANDARD = LVTTL;
NET "VGA_OUT_RED[2]" IOSTANDARD = LVTTL;
NET "VGA_OUT_RED[3]" IOSTANDARD = LVTTL;
NET "VGA_OUT_RED[4]" IOSTANDARD = LVTTL;
NET "VGA_OUT_RED[5]" IOSTANDARD = LVTTL;
NET "VGA_OUT_RED[6]" IOSTANDARD = LVTTL;
NET "VGA_OUT_RED[7]" IOSTANDARD = LVTTL;
 
NET "VGA_OUT_BLUE[0]" SLEW = SLOW;
NET "VGA_OUT_BLUE[1]" SLEW = SLOW;
NET "VGA_OUT_BLUE[2]" SLEW = SLOW;
NET "VGA_OUT_BLUE[3]" SLEW = SLOW;
NET "VGA_OUT_BLUE[4]" SLEW = SLOW;
NET "VGA_OUT_BLUE[5]" SLEW = SLOW;
NET "VGA_OUT_BLUE[6]" SLEW = SLOW;
NET "VGA_OUT_BLUE[7]" SLEW = SLOW;
 
NET "VGA_OUT_GREEN[0]" SLEW = SLOW;
NET "VGA_OUT_GREEN[1]" SLEW = SLOW;
NET "VGA_OUT_GREEN[2]" SLEW = SLOW;
NET "VGA_OUT_GREEN[3]" SLEW = SLOW;
NET "VGA_OUT_GREEN[4]" SLEW = SLOW;
NET "VGA_OUT_GREEN[5]" SLEW = SLOW;
NET "VGA_OUT_GREEN[6]" SLEW = SLOW;
NET "VGA_OUT_GREEN[7]" SLEW = SLOW;
 
NET "VGA_OUT_RED[0]" SLEW = SLOW;
NET "VGA_OUT_RED[1]" SLEW = SLOW;
NET "VGA_OUT_RED[2]" SLEW = SLOW;
NET "VGA_OUT_RED[3]" SLEW = SLOW;
NET "VGA_OUT_RED[4]" SLEW = SLOW;
NET "VGA_OUT_RED[5]" SLEW = SLOW;
NET "VGA_OUT_RED[6]" SLEW = SLOW;
NET "VGA_OUT_RED[7]" SLEW = SLOW;
 
NET "VGA_OUT_BLUE[0]" DRIVE = 6;
NET "VGA_OUT_BLUE[1]" DRIVE = 6;
NET "VGA_OUT_BLUE[2]" DRIVE = 6;
NET "VGA_OUT_BLUE[3]" DRIVE = 6;
NET "VGA_OUT_BLUE[4]" DRIVE = 6;
NET "VGA_OUT_BLUE[5]" DRIVE = 6;
NET "VGA_OUT_BLUE[6]" DRIVE = 6;
NET "VGA_OUT_BLUE[7]" DRIVE = 6;
 
NET "VGA_OUT_GREEN[0]" DRIVE = 6;
NET "VGA_OUT_GREEN[1]" DRIVE = 6;
NET "VGA_OUT_GREEN[2]" DRIVE = 6;
NET "VGA_OUT_GREEN[3]" DRIVE = 6;
NET "VGA_OUT_GREEN[4]" DRIVE = 6;
NET "VGA_OUT_GREEN[5]" DRIVE = 6;
NET "VGA_OUT_GREEN[6]" DRIVE = 6;
NET "VGA_OUT_GREEN[7]" DRIVE = 6;
 
NET "VGA_OUT_RED[0]" DRIVE = 6;
NET "VGA_OUT_RED[1]" DRIVE = 6;
NET "VGA_OUT_RED[2]" DRIVE = 6;
NET "VGA_OUT_RED[3]" DRIVE = 6;
NET "VGA_OUT_RED[4]" DRIVE = 6;
NET "VGA_OUT_RED[5]" DRIVE = 6;
NET "VGA_OUT_RED[6]" DRIVE = 6;
NET "VGA_OUT_RED[7]" DRIVE = 6;
 
NET "VGA_VSYNCH" IOSTANDARD = LVTTL;
NET "VGA_OUT_PIXEL_CLOCK" IOSTANDARD = LVTTL;
NET "VGA_HSYNCH" IOSTANDARD = LVTTL;
NET "VGA_OUT_BLANK_Z" IOSTANDARD = LVTTL;
NET "VGA_COMP_SYNCH" IOSTANDARD = LVTTL;
 
NET "VGA_VSYNCH" DRIVE = 12;
NET "VGA_OUT_PIXEL_CLOCK" DRIVE = 6;
NET "VGA_HSYNCH" DRIVE = 12;
NET "VGA_OUT_BLANK_Z" DRIVE = 6;
NET "VGA_COMP_SYNCH" DRIVE = 6;
 
NET "VGA_VSYNCH" SLEW = SLOW;
NET "VGA_OUT_PIXEL_CLOCK" SLEW = SLOW;
NET "VGA_HSYNCH" SLEW = SLOW;
NET "VGA_OUT_BLANK_Z" SLEW = SLOW;
NET "VGA_COMP_SYNCH" SLEW = SLOW;
 
 
/image_component_labeling_and_feature_extraction/trunk/SendFeatures.vhd
0,0 → 1,235
----------------------------------------------------------------------------------
-- Company:
-- Engineer:
--
-- Create Date: 13:14:03 11/05/2008
-- Design Name:
-- Module Name: SendFeatures - Behavioral
-- Project Name:
-- Target Devices:
-- Tool versions:
-- Description:
--
-- Dependencies:
--
-- Revision:
-- Revision 0.01 - File Created
-- Additional Comments:
--
----------------------------------------------------------------------------------
library IEEE;
use IEEE.STD_LOGIC_1164.ALL;
use IEEE.STD_LOGIC_ARITH.ALL;
use IEEE.STD_LOGIC_UNSIGNED.ALL;
 
---- Uncomment the following library declaration if instantiating
---- any Xilinx primitives in this code.
--library UNISIM;
--use UNISIM.VComponents.all;
 
entity SendFeatures is
Port ( features : in STD_LOGIC_VECTOR (34 downto 0);
fsync : in STD_LOGIC;
wstrobe : in STD_LOGIC;
ready : out STD_LOGIC;
clk : in STD_LOGIC;
reset : in STD_LOGIC;
RX_DATA : in STD_LOGIC;
RTS_IN : in STD_LOGIC;
DSR_OUT : out STD_LOGIC;
TX_DATA : out STD_LOGIC;
CTS_OUT : out STD_LOGIC);
end SendFeatures;
 
architecture Behavioral of SendFeatures is
 
signal transdata : std_logic_vector(7 downto 0); -- Data to be transmitted
signal wr : std_logic; -- write strobe
signal tbe : std_logic; -- transmitt buffer empty
type state_type is (idle, sendB1_A, sendB1_B, sendB1_C, sendB2_A, sendB2_B, sendB2_C,
sendB3_A, sendB3_B, sendB3_C, sendB4_A, sendB4_B, sendB4_C, sendB5_A,
sendB5_B, sendB5_C); --state declaration
signal state : state_type := idle;
signal firstByteInFrame : std_logic := '0';
signal data_vector : std_logic_vector(34 downto 0);
signal recdata : std_logic_vector(7 downto 0);
begin
 
serial : entity work.UARTcomponent port map (
TXD => TX_DATA, -- Transmitted serial data output
RXD => RX_DATA, -- Received serial data input
CLK => clk, -- Clock signal
DBIN => transdata, -- Input parallel data to be transmitted
DBOUT => recdata, -- Recevived parallel data output
RDA => open, -- Read Data Available
TBE => tbe, -- Transfer Buffer Emty
RD => '0',
WR => wr,
PE => open, -- Parity error
FE => open, -- Frame error
OE => open, -- Overwrite error
RST => reset ); -- Reset signal
DSR_OUT <= '1';
CTS_OUT <= RTS_IN;
 
sendStates: process(clk,reset)
-- This process
begin
 
if reset = '1' then
state <= idle;
elsif clk'event and clk = '1' then
case state is
when idle => -- Waiting for the feature vector to be ready and the wstrobe
if fsync = '1' then
firstByteInFrame <= '1'; -- The most significant bit is set for
end if; -- the first byte in the first feature vector for all frames.
-- This bit is thus used for frame syncronization with the
-- recieving unit on the serial RS232 link.
ready <= '1';
if wstrobe = '1' then
state <= sendB1_A;
data_vector <= features;
end if;
when sendB1_A => -- Send first byte for feature vector
ready <= '0';
if tbe = '1' then
state <= sendB1_B;
end if;
when sendB1_B =>
state <= sendB1_C;
when sendB1_C =>
if tbe = '1' then
state <= sendB2_A;
firstByteInFrame <= '0';
end if;
when sendB2_A => -- Send second byte for feature vector
ready <= '0';
if tbe = '1' then
state <= sendB2_B;
end if;
when sendB2_B =>
state <= sendB2_C;
when sendB2_C =>
if tbe = '1' then
state <= sendB3_A;
end if;
 
when sendB3_A => -- Send third byte for feature vector
ready <= '0';
firstByteInFrame <= '0';
if tbe = '1' then
state <= sendB3_B;
end if;
when sendB3_B =>
state <= sendB3_C;
when sendB3_C =>
if tbe = '1' then
state <= sendB4_A;
end if;
when sendB4_A => -- Send fourth byte for feature vector
ready <= '0';
firstByteInFrame <= '0';
if tbe = '1' then
state <= sendB4_B;
end if;
when sendB4_B =>
state <= sendB4_C;
when sendB4_C =>
if tbe = '1' then
state <= sendB5_A;
end if;
when sendB5_A => -- Send fifth byte for feature vector
ready <= '0';
firstByteInFrame <= '0';
if tbe = '1' then
state <= sendB5_B;
end if;
when sendB5_B =>
state <= sendB5_C;
when sendB5_C =>
if tbe = '1' then
state <= idle;
end if;
 
end case;
 
end if; -- of synchronous part
end process; -- sendStates
 
sendOut: process(state)
begin
case state is
when idle =>
wr <= '0';
transdata <= firstByteInFrame&data_vector(34 downto 28);
when sendB1_A => --- Send first byte -----------------
transdata <= firstByteInFrame&data_vector(34 downto 28);
wr <= '0';
when sendB1_B => -- Activate strobe
transdata <= firstByteInFrame&data_vector(34 downto 28);
wr <= '1';
when sendB1_C =>
transdata <= firstByteInFrame&data_vector(34 downto 28);
wr <= '0';
when sendB2_A => --- Send second byte -----------------
transdata <= firstByteInFrame&data_vector(27 downto 21);
wr <= '0';
when sendB2_B => -- Activate strobe
transdata <= firstByteInFrame&data_vector(27 downto 21);
wr <= '1';
when sendB2_C =>
transdata <= firstByteInFrame&data_vector(27 downto 21);
wr <= '0';
when sendB3_A => --- Send third byte -----------------
transdata <= firstByteInFrame&data_vector(20 downto 14);
wr <= '0';
when sendB3_B => -- Activate strobe
transdata <= firstByteInFrame&data_vector(20 downto 14);
wr <= '1';
when sendB3_C =>
transdata <= firstByteInFrame&data_vector(20 downto 14);
wr <= '0';
when sendB4_A => --- Send fourth byte -----------------
transdata <= firstByteInFrame&data_vector(13 downto 7);
wr <= '0';
when sendB4_B => -- Activate strobe
transdata <= firstByteInFrame&data_vector(13 downto 7);
wr <= '1';
when sendB4_C =>
transdata <= firstByteInFrame&data_vector(13 downto 7);
wr <= '0';
when sendB5_A => --- Send fifth byte -----------------
transdata <= firstByteInFrame&data_vector(6 downto 0);
wr <= '0';
when sendB5_B => -- Activate strobe
transdata <= firstByteInFrame&data_vector(6 downto 0);
wr <= '1';
when sendB5_C =>
transdata <= firstByteInFrame&data_vector(6 downto 0);
wr <= '0';
when others =>
wr <= '0';
transdata <= firstByteInFrame&data_vector(34 downto 28);
end case;
end process; -- sendOut
 
end Behavioral;
 
/image_component_labeling_and_feature_extraction/trunk/labellingen_cog_op.xise
0,0 → 1,511
<?xml version="1.0" encoding="UTF-8" standalone="no" ?>
<project xmlns="http://www.xilinx.com/XMLSchema" xmlns:xil_pn="http://www.xilinx.com/XMLSchema">
 
<header>
<!-- ISE source project file created by Project Navigator. -->
<!-- -->
<!-- This file contains project source information including a list of -->
<!-- project source files, project and process properties. This file, -->
<!-- along with the project source files, is sufficient to open and -->
<!-- implement in ISE Project Navigator. -->
<!-- -->
<!-- Copyright (c) 1995-2012 Xilinx, Inc. All rights reserved. -->
</header>
 
<version xil_pn:ise_version="14.1" xil_pn:schema_version="2"/>
 
<files>
<file xil_pn:name="img_testbench2_08bits.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="2"/>
<association xil_pn:name="Implementation" xil_pn:seqID="2"/>
</file>
<file xil_pn:name="serial_div2.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="3"/>
<association xil_pn:name="Implementation" xil_pn:seqID="3"/>
</file>
<file xil_pn:name="ram1w2r.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="5"/>
<association xil_pn:name="Implementation" xil_pn:seqID="5"/>
</file>
<file xil_pn:name="equivalenceTable.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="6"/>
<association xil_pn:name="Implementation" xil_pn:seqID="6"/>
</file>
<file xil_pn:name="label8AndFeatures.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="8"/>
<association xil_pn:name="Implementation" xil_pn:seqID="8"/>
</file>
<file xil_pn:name="compuSequencer.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="10"/>
<association xil_pn:name="Implementation" xil_pn:seqID="10"/>
</file>
<file xil_pn:name="measurePoints_guide.ncd" xil_pn:type="FILE_NCD"/>
<file xil_pn:name="i2c_master_top.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="15"/>
<association xil_pn:name="Implementation" xil_pn:seqID="15"/>
</file>
<file xil_pn:name="SendFeatures.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="16"/>
<association xil_pn:name="Implementation" xil_pn:seqID="16"/>
</file>
<file xil_pn:name="ram_num.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="17"/>
<association xil_pn:name="Implementation" xil_pn:seqID="17"/>
</file>
<file xil_pn:name="mac_module.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="19"/>
<association xil_pn:name="Implementation" xil_pn:seqID="19"/>
</file>
<file xil_pn:name="ram_denom.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="22"/>
<association xil_pn:name="Implementation" xil_pn:seqID="22"/>
</file>
<file xil_pn:name="line_bufferXB.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="26"/>
<association xil_pn:name="Implementation" xil_pn:seqID="26"/>
</file>
<file xil_pn:name="UART_Component.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="28"/>
<association xil_pn:name="Implementation" xil_pn:seqID="28"/>
</file>
<file xil_pn:name="i2c_master_bit_ctrl.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="29"/>
<association xil_pn:name="Implementation" xil_pn:seqID="29"/>
</file>
<file xil_pn:name="i2c_master_byte_ctrl.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="30"/>
<association xil_pn:name="Implementation" xil_pn:seqID="30"/>
</file>
<file xil_pn:name="test_LabelOperation.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="31"/>
<association xil_pn:name="PostMapSimulation" xil_pn:seqID="31"/>
<association xil_pn:name="PostRouteSimulation" xil_pn:seqID="31"/>
<association xil_pn:name="PostTranslateSimulation" xil_pn:seqID="31"/>
</file>
<file xil_pn:name="labelOperation.vhd" xil_pn:type="FILE_VHDL">
<association xil_pn:name="BehavioralSimulation" xil_pn:seqID="32"/>
<association xil_pn:name="Implementation" xil_pn:seqID="32"/>
</file>
<file xil_pn:name="topLevel.ucf" xil_pn:type="FILE_UCF">
<association xil_pn:name="Implementation" xil_pn:seqID="34"/>
</file>
</files>
 
<autoManagedFiles>
<!-- The following files are identified by `include statements in verilog -->
<!-- source files and are automatically managed by Project Navigator. -->
<!-- -->
<!-- Do not hand-edit this section, as it will be overwritten when the -->
<!-- project is analyzed based on files automatically identified as -->
<!-- include files. -->
</autoManagedFiles>
 
<properties>
<property xil_pn:name="AES Initial Vector virtex4" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="AES Key (Hex String)" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Add File to project" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Add I/O Buffers" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Add I/O Pads" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Advanced FSM Optimization" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Allow Logic Optimization Across Hierarchy" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Allow SelectMAP Pins to Persist" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Allow Unexpanded Blocks" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Allow Unmatched LOC Constraints" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Allow Unmatched Timing Group Constraints" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Array Bounds Check" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Asynchronous To Synchronous" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Auto Constrain" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Auto Implementation Compile Order" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Auto Implementation Top" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Automatic BRAM Packing" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Automatically Insert glbl Module in the Netlist" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Automatically Run Generate Target PROM/ACE File" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="BRAM Utilization Ratio" xil_pn:value="100" xil_pn:valueState="default"/>
<property xil_pn:name="Baud rate" xil_pn:value="None" xil_pn:valueState="default"/>
<property xil_pn:name="Bring Out Global Set/Reset Net as a Port" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Bring Out Global Tristate Net as a Port" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Bus Delimiter" xil_pn:value="&lt;>" xil_pn:valueState="default"/>
<property xil_pn:name="CLB Pack Factor Percentage" xil_pn:value="100" xil_pn:valueState="default"/>
<property xil_pn:name="Case" xil_pn:value="Maintain" xil_pn:valueState="default"/>
<property xil_pn:name="Case Implementation Style" xil_pn:value="None" xil_pn:valueState="default"/>
<property xil_pn:name="Change Device Speed To" xil_pn:value="-12" xil_pn:valueState="default"/>
<property xil_pn:name="Change Device Speed To Post Trace" xil_pn:value="-12" xil_pn:valueState="default"/>
<property xil_pn:name="Combinatorial Logic Optimization" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Compile EDK Simulation Library" xil_pn:value="false" xil_pn:valueState="non-default"/>
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<property xil_pn:name="Compile SmartModels (PPC, MGT) Simulation Library" xil_pn:value="true" xil_pn:valueState="default"/>
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<property xil_pn:name="Compile for HDL Debugging" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Compiled Library Directory" xil_pn:value="E:/labellingen_cog_op" xil_pn:valueState="non-default"/>
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<property xil_pn:name="Configuration Name" xil_pn:value="Default" xil_pn:valueState="default"/>
<property xil_pn:name="Configuration Pin Busy" xil_pn:value="Pull Up" xil_pn:valueState="default"/>
<property xil_pn:name="Configuration Pin CS" xil_pn:value="Pull Up" xil_pn:valueState="default"/>
<property xil_pn:name="Configuration Pin DIn" xil_pn:value="Pull Up" xil_pn:valueState="default"/>
<property xil_pn:name="Configuration Pin Done" xil_pn:value="Pull Up" xil_pn:valueState="default"/>
<property xil_pn:name="Configuration Pin HSWAPEN" xil_pn:value="Pull Up" xil_pn:valueState="default"/>
<property xil_pn:name="Configuration Pin Init" xil_pn:value="Pull Up" xil_pn:valueState="default"/>
<property xil_pn:name="Configuration Pin M0" xil_pn:value="Pull Up" xil_pn:valueState="default"/>
<property xil_pn:name="Configuration Pin M1" xil_pn:value="Pull Up" xil_pn:valueState="default"/>
<property xil_pn:name="Configuration Pin M2" xil_pn:value="Pull Up" xil_pn:valueState="default"/>
<property xil_pn:name="Configuration Pin Powerdown" xil_pn:value="Pull Up" xil_pn:valueState="default"/>
<property xil_pn:name="Configuration Pin Program" xil_pn:value="Pull Up" xil_pn:valueState="default"/>
<property xil_pn:name="Configuration Pin RdWr" xil_pn:value="Pull Up" xil_pn:valueState="default"/>
<property xil_pn:name="Configuration Rate" xil_pn:value="4" xil_pn:valueState="default"/>
<property xil_pn:name="Convert Tristates To Logic" xil_pn:value="Yes" xil_pn:valueState="default"/>
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<property xil_pn:name="Create IEEE 1532 Configuration File" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Create Logic Allocation File" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Create Mask File" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Create ReadBack Data Files" xil_pn:value="false" xil_pn:valueState="default"/>
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<property xil_pn:name="Default Enum Encoding Goal" xil_pn:value="default" xil_pn:valueState="default"/>
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<property xil_pn:name="Delay Values To Be Read from SDF ModelSim" xil_pn:value="Setup Time" xil_pn:valueState="default"/>
<property xil_pn:name="Device" xil_pn:value="xc4vlx80" xil_pn:valueState="non-default"/>
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<property xil_pn:name="FPGA Start-Up Clock" xil_pn:value="CCLK" xil_pn:valueState="default"/>
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<property xil_pn:name="Generate Datasheet Section" xil_pn:value="true" xil_pn:valueState="default"/>
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<property xil_pn:name="Other NETGEN Command Line Options" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Other Ngdbuild Command Line Options" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Other Place &amp; Route Command Line Options" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Other VCOM Command Line Options" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Other VLOG Command Line Options" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Other VSIM Command Line Options" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Other XPWR Command Line Options" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Other XST Command Line Options" xil_pn:value="" xil_pn:valueState="default"/>
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<property xil_pn:name="Output File Base Name" xil_pn:value="" xil_pn:valueState="default"/>
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<property xil_pn:name="Package" xil_pn:value="ff1148" xil_pn:valueState="default"/>
<property xil_pn:name="Parallel Case" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Perform Advanced Analysis" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Perform Advanced Analysis Post Trace" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Perform Timing-Driven Packing and Placement" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Pipelining" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Place &amp; Route Effort Level (Overall)" xil_pn:value="High" xil_pn:valueState="default"/>
<property xil_pn:name="Place And Route Mode" xil_pn:value="Normal Place and Route" xil_pn:valueState="default"/>
<property xil_pn:name="Placer Effort Level (Overrides Overall Level)" xil_pn:value="None" xil_pn:valueState="default"/>
<property xil_pn:name="Port to be used" xil_pn:value="Auto - default" xil_pn:valueState="default"/>
<property xil_pn:name="Post Map Simulation Model Name" xil_pn:value="SendFeatures_map.vhd" xil_pn:valueState="default"/>
<property xil_pn:name="Post Place &amp; Route Simulation Model Name" xil_pn:value="SendFeatures_timesim.vhd" xil_pn:valueState="default"/>
<property xil_pn:name="Post Synthesis Simulation Model Name" xil_pn:value="SendFeatures_synthesis.vhd" xil_pn:valueState="default"/>
<property xil_pn:name="Post Translate Simulation Model Name" xil_pn:value="SendFeatures_translate.vhd" xil_pn:valueState="default"/>
<property xil_pn:name="Power Reduction" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Power Reduction Map" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Power Reduction Par" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Preferred Language" xil_pn:value="VHDL" xil_pn:valueState="default"/>
<property xil_pn:name="Priority Encoder Extraction" xil_pn:value="Yes" xil_pn:valueState="default"/>
<property xil_pn:name="Process window" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Produce Verbose Report" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Project Description" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Project Generator" xil_pn:value="ProjNav" xil_pn:valueState="default"/>
<property xil_pn:name="Property Specification in Project File" xil_pn:value="Store all values" xil_pn:valueState="default"/>
<property xil_pn:name="Push Tristates across Process/Block Boundaries" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="RAM Extraction" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="RAM Style" xil_pn:value="Auto" xil_pn:valueState="default"/>
<property xil_pn:name="ROM Extraction" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="ROM Style" xil_pn:value="Auto" xil_pn:valueState="default"/>
<property xil_pn:name="Read Cores" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Regenerate Core" xil_pn:value="Under Current Project Setting" xil_pn:valueState="default"/>
<property xil_pn:name="Register Balancing" xil_pn:value="No" xil_pn:valueState="default"/>
<property xil_pn:name="Register Duplication" xil_pn:value="Off" xil_pn:valueState="default"/>
<property xil_pn:name="Register Duplication Xst" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Release Set/Reset (Output Events)" xil_pn:value="Default (6)" xil_pn:valueState="default"/>
<property xil_pn:name="Release Write Enable (Output Events)" xil_pn:value="Default (6)" xil_pn:valueState="default"/>
<property xil_pn:name="Rename Design Instance in Testbench File to" xil_pn:value="UUT" xil_pn:valueState="default"/>
<property xil_pn:name="Rename Top Level Architecture To" xil_pn:value="Structure" xil_pn:valueState="default"/>
<property xil_pn:name="Rename Top Level Entity to" xil_pn:value="SendFeatures" xil_pn:valueState="default"/>
<property xil_pn:name="Rename Top Level Module To" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Report Clock Frequencies" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Report Critical Paths" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Report Fastest Path(s) in Each Constraint" xil_pn:value="false" xil_pn:valueState="non-default"/>
<property xil_pn:name="Report Fastest Path(s) in Each Constraint Post Trace" xil_pn:value="false" xil_pn:valueState="non-default"/>
<property xil_pn:name="Report Missing Constraints" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Report Paths by Endpoint" xil_pn:value="3" xil_pn:valueState="default"/>
<property xil_pn:name="Report Paths by Endpoint Post Trace" xil_pn:value="3" xil_pn:valueState="default"/>
<property xil_pn:name="Report Timing Summary" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Report Timing Violations" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Report Type" xil_pn:value="Verbose Report" xil_pn:valueState="default"/>
<property xil_pn:name="Report Type Post Trace" xil_pn:value="Verbose Report" xil_pn:valueState="default"/>
<property xil_pn:name="Report Unconstrained Paths" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Report Unconstrained Paths Post Trace" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Reset On Configuration Pulse Width" xil_pn:value="100" xil_pn:valueState="default"/>
<property xil_pn:name="Resource Sharing" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Resource Sharing Precision" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Resource Sharing Synthesis" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Retain Hierarchy" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Retiming" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Router Effort Level (Overrides Overall Level)" xil_pn:value="None" xil_pn:valueState="default"/>
<property xil_pn:name="Run Design Rules Checker (DRC)" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Run Retiming" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Run for Specified Time" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Run for Specified Time Par" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Safe Implementation" xil_pn:value="No" xil_pn:valueState="default"/>
<property xil_pn:name="Security" xil_pn:value="Enable Readback and Reconfiguration" xil_pn:valueState="default"/>
<property xil_pn:name="Selected Module Instance Name" xil_pn:value="/i2c_master_top" xil_pn:valueState="non-default"/>
<property xil_pn:name="Selected Simulation Root Source Node Behavioral" xil_pn:value="work.i2c_master_top" xil_pn:valueState="non-default"/>
<property xil_pn:name="Selected Simulation Source Node" xil_pn:value="UUT" xil_pn:valueState="default"/>
<property xil_pn:name="Setting Output File" xil_pn:value="Default" xil_pn:valueState="non-default"/>
<property xil_pn:name="Shift Register Extraction" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Show All Models" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Show Clock Domain Crossing" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Show Net Fan Out" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Signal window" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Simulation Model Target" xil_pn:value="VHDL" xil_pn:valueState="default"/>
<property xil_pn:name="Simulation Resolution" xil_pn:value="Default (1 ps)" xil_pn:valueState="default"/>
<property xil_pn:name="Simulation Run Time ISim" xil_pn:value="1000 ns" xil_pn:valueState="default"/>
<property xil_pn:name="Simulation Run Time Modelsim" xil_pn:value="1000ns" xil_pn:valueState="default"/>
<property xil_pn:name="Simulation Run Time Par" xil_pn:value="1000 ns" xil_pn:valueState="default"/>
<property xil_pn:name="Simulator" xil_pn:value="Modelsim-PE VHDL" xil_pn:valueState="non-default"/>
<property xil_pn:name="Simulator Path" xil_pn:value="remote_sources/Modeltech_pe_edu_10.3c/win32pe_edu" xil_pn:valueState="non-default"/>
<property xil_pn:name="Slice Packing" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Slice Utilization Ratio" xil_pn:value="100" xil_pn:valueState="default"/>
<property xil_pn:name="Source window" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Specify 'define Macro Name and Value" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Specify Top Level Instance Names" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Speed Grade" xil_pn:value="-12" xil_pn:valueState="default"/>
<property xil_pn:name="Starting CBC Value (Hex)" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Starting Key" xil_pn:value="None" xil_pn:valueState="default"/>
<property xil_pn:name="Starting Placer Cost Table (1-100) Map" xil_pn:value="1" xil_pn:valueState="default"/>
<property xil_pn:name="Starting Placer Cost Table (1-100) Par" xil_pn:value="1" xil_pn:valueState="default"/>
<property xil_pn:name="Structure window" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Symbolic FSM Compiler" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Synthesis Tool" xil_pn:value="XST (VHDL/Verilog)" xil_pn:valueState="default"/>
<property xil_pn:name="Sysgen Instantiation Template Target Language" xil_pn:value="VHDL" xil_pn:valueState="default"/>
<property xil_pn:name="Target Simulator" xil_pn:value="Modelsim-PE VHDL" xil_pn:valueState="default"/>
<property xil_pn:name="Timing Mode Map" xil_pn:value="Non Timing Driven" xil_pn:valueState="default"/>
<property xil_pn:name="Timing Mode Par" xil_pn:value="Performance Evaluation" xil_pn:valueState="default"/>
<property xil_pn:name="Top-Level Module Name in Output Netlist" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Top-Level Source Type" xil_pn:value="HDL" xil_pn:valueState="default"/>
<property xil_pn:name="Transform Set/Reset on DFFs to Latches" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Tri-state Buffer Transformation Mode" xil_pn:value="Off" xil_pn:valueState="default"/>
<property xil_pn:name="Trim Unconnected Signals" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Tristate On Configuration Pulse Width" xil_pn:value="0" xil_pn:valueState="default"/>
<property xil_pn:name="Unused IOB Pins" xil_pn:value="Pull Down" xil_pn:valueState="default"/>
<property xil_pn:name="Update modelsim.ini File for Xilinx SmartModel Use" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use 64-bit PlanAhead on 64-bit Systems" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Use Automatic Do File" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Use Clock Enable" xil_pn:value="Yes" xil_pn:valueState="non-default"/>
<property xil_pn:name="Use Configuration Name" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use Custom Do File" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use Custom Do File Behavioral" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use Custom Do File Map" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use Custom Do File Par" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use Custom Do File Translate" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use Custom Project File Behavioral" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use Custom Simulation Command File" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use Custom Simulation Command File Behavioral" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use Custom Simulation Command File Par" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use DSP48" xil_pn:value="Auto" xil_pn:valueState="default"/>
<property xil_pn:name="Use Explicit Declarations Only" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Use FSM Explorer Data" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use LOC Constraints" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Use RLOC Constraints" xil_pn:value="Yes" xil_pn:valueState="default"/>
<property xil_pn:name="Use Safe FSM" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use Smart Guide" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Use Synchronous Reset" xil_pn:value="Yes" xil_pn:valueState="non-default"/>
<property xil_pn:name="Use Synchronous Set" xil_pn:value="Yes" xil_pn:valueState="non-default"/>
<property xil_pn:name="Use Synthesis Constraints File" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="User Browsed Strategy Files" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="UserID Code (8 Digit Hexadecimal)" xil_pn:value="0xFFFFFFFF" xil_pn:valueState="default"/>
<property xil_pn:name="VHDL" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="VHDL Source Analysis Standard" xil_pn:value="VHDL-93" xil_pn:valueState="default"/>
<property xil_pn:name="VHDL Syntax" xil_pn:value="93" xil_pn:valueState="default"/>
<property xil_pn:name="VHDL Syntax Precision" xil_pn:value="VHDL 93" xil_pn:valueState="non-default"/>
<property xil_pn:name="Value Range Check" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Variables window" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Verilog" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Verilog 2001 Xst" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Verilog Macros" xil_pn:value="" xil_pn:valueState="default"/>
<property xil_pn:name="Verilog Standard" xil_pn:value="Verilog 2001" xil_pn:valueState="default"/>
<property xil_pn:name="Wait for DCI Match (Output Events) virtex2" xil_pn:value="Auto" xil_pn:valueState="default"/>
<property xil_pn:name="Wait for DLL Lock (Output Events)" xil_pn:value="Default (NoWait)" xil_pn:valueState="default"/>
<property xil_pn:name="Wave window" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="Working Directory" xil_pn:value="." xil_pn:valueState="non-default"/>
<property xil_pn:name="Write Mapped VHDL Netlist" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Write Mapped Verilog Netlist" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Write Timing Constraints" xil_pn:value="false" xil_pn:valueState="default"/>
<property xil_pn:name="Write Vendor Constraint File" xil_pn:value="true" xil_pn:valueState="default"/>
<property xil_pn:name="XOR Collapsing" xil_pn:value="true" xil_pn:valueState="default"/>
<!-- -->
<!-- The following properties are for internal use only. These should not be modified.-->
<!-- -->
<property xil_pn:name="PROP_BehavioralSimTop" xil_pn:value="Architecture|test_labelOperation|behavior" xil_pn:valueState="non-default"/>
<property xil_pn:name="PROP_DesignName" xil_pn:value="justCamToVGA" xil_pn:valueState="non-default"/>
<property xil_pn:name="PROP_DevFamilyPMName" xil_pn:value="virtex4" xil_pn:valueState="default"/>
<property xil_pn:name="PROP_FPGAConfiguration" xil_pn:value="FPGAConfiguration" xil_pn:valueState="default"/>
<property xil_pn:name="PROP_HdlTemplateLang" xil_pn:value="VHDL" xil_pn:valueState="default"/>
<property xil_pn:name="PROP_HdlTemplateName" xil_pn:value="justCamToVGA.vhd" xil_pn:valueState="default"/>
<property xil_pn:name="PROP_PostFitSimTop" xil_pn:value="Architecture|test_mhvfTovga|behavior" xil_pn:valueState="non-default"/>
<property xil_pn:name="PROP_PostMapSimTop" xil_pn:value="Architecture|test_labelOperation|behavior" xil_pn:valueState="non-default"/>
<property xil_pn:name="PROP_PostParSimTop" xil_pn:value="Architecture|test_labelOperation|behavior" xil_pn:valueState="non-default"/>
<property xil_pn:name="PROP_PostSynthSimTop" xil_pn:value="Architecture|test_labelOperation|behavior" xil_pn:valueState="non-default"/>
<property xil_pn:name="PROP_PostXlateSimTop" xil_pn:value="Architecture|test_labelOperation|behavior" xil_pn:valueState="non-default"/>
<property xil_pn:name="PROP_PreSynthesis" xil_pn:value="PreSynthesis" xil_pn:valueState="default"/>
<property xil_pn:name="PROP_intProjectCreationTimestamp" xil_pn:value="2014-08-06T23:36:10" xil_pn:valueState="non-default"/>
<property xil_pn:name="PROP_intWbtProjectID" xil_pn:value="A1ECBFF737354DF0BFF4210B83806FA4" xil_pn:valueState="non-default"/>
<property xil_pn:name="PROP_intWorkingDirLocWRTProjDir" xil_pn:value="Same" xil_pn:valueState="non-default"/>
<property xil_pn:name="PROP_intWorkingDirUsed" xil_pn:value="No" xil_pn:valueState="non-default"/>
</properties>
 
<bindings/>
 
<libraries/>
 
</project>
/image_component_labeling_and_feature_extraction/trunk/label8AndFeatures.vhd
0,0 → 1,197
library ieee;
use ieee.std_logic_1164.all;
use IEEE.STD_LOGIC_UNSIGNED.ALL;
use ieee.numeric_std.all;
use ieee.std_logic_arith.all;
 
 
---- Uncomment the following library declaration if instantiating
---- any Xilinx primitives in this code.
library UNISIM;
use UNISIM.VComponents.all;
 
entity label8AndFeatures is
generic( CODE_BITS : integer := 10;
row : natural := 480;
col : natural := 640);
port (
ip9 : in std_logic_vector(CODE_BITS-1 downto 0);
ip8 : in std_logic_vector(CODE_BITS-1 downto 0);
ip7 : in std_logic_vector(CODE_BITS-1 downto 0);
ip6 : in std_logic_vector(CODE_BITS-1 downto 0);
ibin : in std_logic;
pdata_in : in std_logic_vector(7 downto 0);
fsync_in : in std_logic;
fsync_out : out std_logic;
pdata_o : out std_logic_vector(CODE_BITS-1 downto 0) := (others => '0');
rsync_in : in std_logic;
rsync_out : out std_logic;
Reset : in std_logic;
pclk : in std_logic;
featureDataStrobe : out std_logic;
acknowledge : in std_logic;
cntObjects : out std_logic_vector(9 downto 0);
x_cog : out std_logic_vector(16 downto 0);
y_cog : out std_logic_vector (16 downto 0)
);
end label8AndFeatures;
 
 
architecture struct of label8AndFeatures is
 
 
signal a,b,dout,indexMax,equalcnt : std_logic_vector(9 downto 0):= (others => '0');
signal readAddr: std_logic_vector(9 downto 0);
signal tableReady,tablePreset,we,computeDone : std_logic;
signal hit : std_logic_vector(CODE_BITS-1 downto 0);
signal selectspace : std_logic := '0';
signal pdata_osig : std_logic_vector(CODE_BITS-1 downto 0) := (others => '0');
signal pdata_delayed : std_logic_vector(7 downto 0);
signal eindex : std_logic_vector(CODE_BITS-1 downto 0);
signal compuCode : std_logic_vector(9 downto 0);
signal mergeEnable, compute : std_logic;
signal refa,refb:std_logic_vector(9 downto 0);
subtype col_range is natural range 0 to col ;
subtype row_range is natural range 0 to row + 1;
 
begin
 
equtbl : entity work.equivalenceTable Port map
( a => a,
b => b,
c => refa,--contents of memory locations are set for merging not just labels
d => refb,
we => we,
readAddr => readAddr,
dout => dout,
equalcnt => equalcnt,
fsync => fsync_in,
tableReady => tableReady,
tablePreset => tablePreset,
space => selectspace,
reset => Reset,
clk => pclk,
SetdoutrefA => refa,
SetdoutrefB => refb
);
 
MAC : entity work.mac_module
generic map( ROW=>row, COL=>col,CODE_BITS=>CODE_BITS)
Port Map
( code => pdata_osig,
fsync_in => fsync_in,
rsync_in => rsync_in,
Reset => reset,
pclk => pclk,
pdata_in => pdata_delayed,
tablePreset => tablePreset,
divready_out => computeDone,
selectspace => selectspace,
y_cog => y_cog,
compuCode => compuCode,
mergeEnable => mergeEnable,
compute => compute,
x_cog => x_cog
);
Sequencer : entity work.compuSequencer Port map
( clk => pclk,
reset => fsync_in,
tableReady => tableReady,
computeDone => computeDone,
featureDataStrobe => featureDataStrobe,
acknowledge => acknowledge,
indexMax => indexMax,
eqData => dout,
eqAddress => readAddr,
compuCode => compuCode,
cntObjects => cntObjects,
mergeEnable => mergeEnable,
compute => compute,
tablePreset => tablePreset
);
a <= (others=>'0') when reset= '1' else --check all the conditions for labelling
ip6 when (ibin = '1' and ip7 /= 0 and ip6 /= 0) else
ip6 when (ibin = '1' and ip8 /= 0 and ip6 /= 0) else
ip6 when (ibin = '1' and ip9 /= 0 and ip6 /= 0) else
ip8 when (ibin = '1' and ip8 /= 0 and ip9 /= 0) else
ip7 when (ibin = '1' and ip7 /= 0 and ip9 /= 0) else
ip7 when (ibin = '1' and ip7 /= 0 and ip8 /= 0) else
ip6 when (ibin = '1' and ip7 /= 0 and ip6 /= 0) else
ip8 when (ibin = '1' and ip8 /= 0) else
ip6 when (ibin = '1' and ip6 /= 0)else
ip9 when (ibin= '1' and ip9 /= 0) else
ip7 when (ibin= '1' and ip7 /= 0) else
eindex when ibin='1' else
(others=> '0');
b <=(others=>'0') when reset= '1' else
ip7 when (ibin = '1' and ip7 /= 0 and ip6 /= 0) else
ip8 when (ibin = '1' and ip8 /= 0 and ip6 /= 0) else
ip9 when (ibin = '1' and ip9 /= 0 and ip6 /= 0) else
ip9 when (ibin = '1' and ip8 /= 0 and ip9 /= 0) else
ip9 when (ibin = '1' and ip7 /= 0 and ip9 /= 0) else
ip8 when (ibin = '1' and ip7 /= 0 and ip8 /= 0) else
ip7 when (ibin = '1' and ip7 /= 0 and ip6 /= 0) else
ip8 when (ibin = '1' and ip8 /= 0) else
ip6 when (ibin = '1' and ip6 /= 0) else
ip9 when (ibin= '1' and ip9 /= 0) else
ip7 when (ibin= '1' and ip7 /= 0) else
eindex when ibin='1' else
(others =>'0');
--eindex <= eindex+1 when (ibin = '1' and ip6 = 0 and ip7 = 0 and ip8=0 and ip9=0) ;
-- pdata_o <= refa when (refa < refb) and ibin='1' else
-- refb when ibin ='1' else
-- (others=>'0');
we <= '1' when (ip6 /= 0 or ip7 /= 0 or ip8/=0 or ip9/=0) else
'0';
label8: process(pclk,Reset)
-- This process performs 8-connectivity labeling of the binary input video stream on input port ibin
-- Only the first pass of the labeling process is done. This means that the information stored in the
-- table of equvivalences must be read in order to identify all pixels belonging
-- to one single image component. The equvivalences are stored in block-RAMs through the ports of
-- equtbl : entity work.equivalenceTable. This entity actually contains two tables of equvivalences.
-- One is written to during the labelling process and the other can be used for post processing when
-- image component features are calculated.
 
begin
if Reset = '1' then
eindex <= conv_std_logic_vector(1,CODE_BITS);
--a <= (others=>'0');
--b <= (others=>'0');
hit <= (others=>'0');
--we <= '0';
elsif pclk'event and pclk = '1' then
--we <= '0';
if (ibin = '1' and ip6 = 0 and ip7 = 0 and ip8=0 and ip9=0) then
eindex <= eindex+1 ;
end if;
if refa < refb and ibin='1' then
pdata_osig <= refa;
elsif ibin='1' then
pdata_osig <= refb;
else
pdata_osig <= (others => '0');
end if;
if fsync_in = '1' then
indexMax <= eindex;
eindex <= conv_std_logic_vector(1,CODE_BITS);
hit <= (others=>'0');
end if;
fsync_out <= fsync_in;
rsync_out <= rsync_in;
pdata_delayed <= pdata_in;
end if;--pclk'event
end process label8;
 
pdata_o <= pdata_osig;
end struct;
/image_component_labeling_and_feature_extraction/trunk/ram1w2r.vhd
0,0 → 1,68
----------------------------------------------------------------------------------
-- Company:
-- Engineer:
--
-- Create Date: 10:00:30 11/27/2008
-- Design Name:
-- Module Name: ram1w2r - Behavioral
-- Project Name:
-- Target Devices:
-- Tool versions:
-- Description:
--
-- Dependencies:
--
-- Revision:
-- Revision 0.01 - File Created
-- Additional Comments:
--
----------------------------------------------------------------------------------
library IEEE;
use IEEE.STD_LOGIC_1164.ALL;
use IEEE.STD_LOGIC_ARITH.ALL;
use IEEE.STD_LOGIC_UNSIGNED.ALL;
 
---- Uncomment the following library declaration if instantiating
---- any Xilinx primitives in this code.
--library UNISIM;
--use UNISIM.VComponents.all;
 
entity ram1w2r is
Port (
addrefa:in STD_LOGIC_VECTOR (9 downto 0);
addrefb:in STD_LOGIC_VECTOR (9 downto 0);
doutrefa:out STD_LOGIC_VECTOR (9 downto 0);
doutrefb:out STD_LOGIC_VECTOR (9 downto 0);
addrW : in STD_LOGIC_VECTOR (9 downto 0);
din : in STD_LOGIC_VECTOR (9 downto 0);
we : in STD_LOGIC;
addrRA : in STD_LOGIC_VECTOR (9 downto 0);
doutA : out STD_LOGIC_VECTOR (9 downto 0);
addrRB : in STD_LOGIC_VECTOR (9 downto 0);
doutB : out STD_LOGIC_VECTOR (9 downto 0);
clk : in STD_LOGIC);
end ram1w2r;
 
architecture Behavioral of ram1w2r is
 
type ram_type is array(1023 downto 0) of std_logic_vector(9 downto 0);
signal ram_array : ram_type:=(others=>(others=>'0'));
 
begin
doutrefa <= ram_array(conv_integer(addrefa));--for reading the memory asynchronously
doutrefb <= ram_array(conv_integer(addrefb));
process(clk)
begin
if clk'event and clk ='1' then
if we='1' then
ram_array(conv_integer(addrW)) <= din;
end if;
doutA <= ram_array(conv_integer(addrRA));
doutB <= ram_array(conv_integer(addrRB));
end if;
end process;
 
 
end Behavioral;
 
/image_component_labeling_and_feature_extraction/trunk/UART_Component.vhd
0,0 → 1,756
------------------------------------------------------------------------
-- uartcomponent.vhd
------------------------------------------------------------------------
-- Author: Dan Pederson
-- Copyright 2004 Digilent, Inc.
------------------------------------------------------------------------
-- Description: This file defines a UART which transfers data to and
-- from serial and parallel information. It requires two
-- major processes: receiving and transferring. The
-- receiving portion reads serially transmitted data, and
-- converts it into parallel data, while the transferring
-- portion reads parallel data, and transmits it as serial
-- data. There are three error signals provided with this
-- UART. They are frame error, parity error, and overwrite
-- error signals. This UART is configured to use an ODD
-- parity bit at a baud rate of 9600.
--
------------------------------------------------------------------------
-- Revision History:
-- 07/15/04 (DanP) Created
-- 05/24/05 (DanP) Updated commenting style
-- 06/06/05 (DanP) Synchronized state machines to fix timing bug
------------------------------------------------------------------------
 
library IEEE;
use IEEE.STD_LOGIC_1164.ALL;
use IEEE.STD_LOGIC_ARITH.ALL;
use IEEE.STD_LOGIC_UNSIGNED.ALL;
 
-------------------------------------------------------------------------
--
--Title: UARTcomponent entity
--
--Inputs: 7 : RXD
-- CLK
-- DBIN
-- RDA
-- RD
-- WR
-- RST
--
--Outputs: 7 : TXD
-- DBOUT
-- RDA
-- TBE
-- PE
-- FE
-- OE
--
--Description: This describes the UART component entity. The inputs are
-- the Pegasus 50 MHz clock, a reset button, The RXD from
-- the serial cable, an 8-bit data bus from the parallel
-- port, and Read Data Available (RDA)and Transfer Buffer
-- Empty(TBE) handshaking signals. The outputs are the TXD
-- signal for the serial port, an 8-bit data bus for the
-- parallel port, RDA and TBE handshaking signals, and three
-- error signals for parity, frame, and overwrite errors.
--
-------------------------------------------------------------------------
entity UARTcomponent is
Port ( TXD : out std_logic := '1'; -- Transmitted serial data output
RXD : in std_logic; -- Received serial data input
CLK : in std_logic; -- Clock signal
DBIN : in std_logic_vector (7 downto 0); -- Input parallel data to be transmitted
DBOUT : out std_logic_vector (7 downto 0); -- Recevived parallel data output
RDA : inout std_logic; -- Read Data Available
TBE : out std_logic := '1'; -- Transfer Buffer Emty
RD : in std_logic;
WR : in std_logic;
PE : out std_logic; -- Parity error
FE : out std_logic; -- Frame error
OE : out std_logic; -- Overwrite error
RST : in std_logic := '0'); -- Reset signal
end UARTcomponent;
 
architecture Behavioral of UARTcomponent is
 
------------------------------------------------------------------------
-- Local Type and Signal Declarations
------------------------------------------------------------------------
 
-------------------------------------------------------------------------
--Title: Local Type Declarations
--
--Description: There are two state machines used in this entity. The
-- rstate is used to synchronize the receiving portion of
-- the UART, and the tstate is used to synchronize the
-- sending portion of the UART.
--
-------------------------------------------------------------------------
type rstate is (
strIdle,
strEightDelay,
strGetData,
strWaitFor0,
strWaitFor1,
strCheckStop
);
 
type tstate is (
sttIdle,
sttTransfer,
sttShift,
sttDelay,
sttWaitWrite
);
 
-------------------------------------------------------------------------
--
--Title: Local Signal Declarations
--
--Description: The constants and signals used by this entity are
-- described below:
--
-- -baudRate : This is the Baud Rate constant used to
-- synchronize the Pegasus 50 MHz clock with a
-- baud rate of 9600. To get this number, divide
-- 50MHz by 9600.
-- -baudDivide : This is the Baud Rate divider used to safely
-- read data transmitted at a baud rate of 9600.
-- It is simply the above described baudRate
-- constant divided by 16.
--
-- -rdReg : this is the receive holding register
-- -rdSReg : this is the receive shift register
-- -tfReg : this is the transfer holding register
-- -tfSReg : this is the transfer shifting register
-- -clkDiv : counter used to get rClk
-- -ctr : used for delay times
-- -tfCtr : used to delay in the transfer process
-- -dataCtr : counts the number of read data bits
-- -parError : parity error bit
-- -frameError : frame error bit
-- -CE : clock enable bit for the writing latch
-- -ctRst : reset for the ctr
-- -load : load signal used to load the transfer shift
-- register
-- -shift : shift signal used to unload the transfer
-- shift register
-- -par : represents the parity in the transfer
-- holding register
-- -tClkRST : reset for the tfCtr
-- -rShift : shift signal used to load the receive shift
-- register
-- -dataRST : reset for the dataCtr
-- -dataIncr : signal to increment the dataCtr
-- -tfIncr : signal to increment the tfCtr
-- -tDelayCtr : counter used to delay the transfer state
-- machine.
-- -tDelayRst : reset signal for the tDelayCtr counter.
--
-- The following signals are used by the two state machines
-- for state control:
-- -Receive State Machine : strCur, strNext
-- -Transfer State Machine : sttCur, sttNext
--
-------------------------------------------------------------------------
 
-- constant baudRate : std_logic_vector(12 downto 0) := "1 0100 0101 1000";
-- constant baudRate : std_logic_vector(12 downto 0) := conv_std_logic_vector(1406,13); --19200
constant baudRate : std_logic_vector(12 downto 0) := conv_std_logic_vector(234,13); -- 115 200
-- constant baudRate : std_logic_vector(12 downto 0) := conv_std_logic_vector(482,13); -- 56 000
-- baudrate is set for 115 200 at 27MHz clock freq
constant baudDivide : std_logic_vector(8 downto 0) := conv_std_logic_vector(15,9);
signal rdReg : std_logic_vector(7 downto 0) := "00000000";
signal rdSReg : std_logic_vector(9 downto 0) := "1111111111";
signal tfReg : std_logic_vector(7 downto 0);
signal tfSReg : std_logic_vector(10 downto 0) := "11111111111";
signal clkDiv : std_logic_vector(9 downto 0) := "0000000000";
signal ctr : std_logic_vector(3 downto 0) := "0000";
signal tfCtr : std_logic_vector(3 downto 0) := "0000";
signal dataCtr : std_logic_vector(3 downto 0) := "0000";
signal parError : std_logic;
signal frameError : std_logic;
signal CE : std_logic;
signal ctRst : std_logic := '0';
signal load : std_logic := '0';
signal shift : std_logic := '0';
signal par : std_logic;
signal tClkRST : std_logic := '0';
signal rShift : std_logic := '0';
signal dataRST : std_logic := '0';
signal dataIncr : std_logic := '0';
signal tfIncr : std_logic := '0';
signal tDelayCtr : std_logic_vector (12 downto 0);
signal tDelayRst : std_logic := '0';
 
signal strCur : rstate := strIdle;
signal strNext : rstate;
signal sttCur : tstate := sttIdle;
signal sttNext : tstate;
 
-------------------------------------------------------------------------
-- Module Implementation
-------------------------------------------------------------------------
begin
-------------------------------------------------------------------------
--
--Title: Initial signal definitions
--
--Description: The following lines of code define 4 internal and 1
-- external signal. The most significant bit of the rdSReg
-- signifies the frame error bit, so frameError is tied to
-- that signal. The parError is high if there is a parity
-- error, so it is set equal to the inverse of rdSReg(8)
-- XOR-ed with the data bits. In this manner, it can
-- determine if the parity bit found in rdSReg(8) matches
-- the data bits. The parallel information output is equal
-- to rdReg, so DBOUT is set equal to rdReg. Likewise, the
-- input parallel information is equal to DBIN, so tfReg is
-- set equal to DBIN. Because the tfSReg is used to shift
-- out transmitted data, the TXD port is set equal to the
-- first bit of tfsReg. Finally, the par signal represents
-- the parity of the data, so par is set to the inverse of
-- the data bits XOR-ed together. This UART can be changed
-- to use EVEN parity if the "not" is omitted from the par
-- definition.
--
-------------------------------------------------------------------------
frameError <= not rdSReg(9);
parError <= not ( rdSReg(8) xor (((rdSReg(0) xor rdSReg(1)) xor
(rdSReg(2) xor rdSReg(3))) xor ((rdSReg(4) xor rdSReg(5)) xor
(rdSReg(6) xor rdSReg(7)))) );
DBOUT <= rdReg;
tfReg <= DBIN;
TXD <= tfsReg(0);
par <= not ( ((tfReg(0) xor tfReg(1)) xor (tfReg(2) xor tfReg(3))) xor
((tfReg(4) xor tfReg(5)) xor (tfReg(6) xor tfReg(7))) );
-------------------------------------------------------------------------
--
--Title: Clock Divide counter
--
--Description: This process defines clkDiv as a signal that increments
-- with the clock up until it is either reset by ctRst, or
-- equals baudDivide. This signal is used to define a
-- counter called ctr that increments at the rate of the
-- divided baud rate.
--
-------------------------------------------------------------------------
process (CLK, clkDiv)
begin
if (CLK = '1' and CLK'event) then
if (clkDiv = baudDivide or ctRst = '1') then
clkDiv <= "0000000000";
else
clkDiv <= clkDiv +1;
end if;
end if;
end process;
-------------------------------------------------------------------------
--
--Title: Transfer delay counter
--
--Description: This process defines tDelayCtr as a counter that runs
-- until it equals baudRate, or until it is reset by
-- tDelayRst. This counter is used to measure delay times
-- when sending data out on the TXD signal. When the
-- counter is equal to baudRate, or is reset, it is set
-- equal to 0.
--
-------------------------------------------------------------------------
process (CLK, tDelayCtr)
begin
if (CLK = '1' and CLK'event) then
if (tDelayCtr = baudRate or tDelayRst = '1') then
tDelayCtr <= "0000000000000";
else
tDelayCtr <= tDelayCtr+1;
end if;
end if;
end process;
-------------------------------------------------------------------------
--
--Title: ctr set up
--
--Description: This process sets up ctr, which uses clkDiv to count
-- increase at a rate needed to properly receive data in
-- from RXD. If ctRst is strobed, the counter is reset. If
-- clkDiv is equal to baudDivide, then ctr is incremented
-- once. This signal is used by the receiving state machine
-- to measure delay times between RXD reads.
--
-------------------------------------------------------------------------
process (CLK)
begin
if CLK = '1' and CLK'Event then
if ctRst = '1' then
ctr <= "0000";
elsif clkDiv = baudDivide then
ctr <= ctr + 1;
else
ctr <= ctr;
end if;
end if;
end process;
-------------------------------------------------------------------------
--
--Title: transfer counter
--
--Description: This process makes tfCtr increment whenever the tfIncr
-- signal is strobed high. If the tClkRst signal is strobed
-- high, the tfCtr is reset to "0000." This counter is used
-- to keep track of how many data bits have been
-- transmitted.
--
-------------------------------------------------------------------------
process (CLK, tClkRST)
begin
if (CLK = '1' and CLK'event) then
if tClkRST = '1' then
tfCtr <= "0000";
elsif tfIncr = '1' then
tfCtr <= tfCtr +1;
end if;
end if;
end process;
-------------------------------------------------------------------------
--
--Title: Error and RDA flag controller
--
--Description: This process controls the error flags FE, OE, and PE, as
-- well as the Read Data Available (RDA) flag. When CE goes
-- high, it means that data has been read into the rdSReg.
-- This process then analyzes the read data for errors, sets
-- rdReg equal to the eight data bits in rdSReg, and flags
-- RDA to indicate that new data is present in rdReg. FE
-- and PE are simply equal to the frameError and parError
-- signals. OE is flagged high if RDA is already high when
-- CE is strobed. This means that unread data was still in
-- the rdReg when it was written over with the new data.
--
-------------------------------------------------------------------------
process (CLK, RST, RD, CE)
begin
if RD = '1' or RST = '1' then
FE <= '0';
OE <= '0';
RDA <= '0';
PE <= '0';
elsif CLK = '1' and CLK'event then
if CE = '1' then
FE <= frameError;
PE <= parError;
rdReg(7 downto 0) <= rdSReg (7 downto 0);
if RDA = '1' then
OE <= '1';
else
OE <= '0';
RDA <= '1';
end if;
end if;
end if;
end process;
-------------------------------------------------------------------------
--
--Title: Receiving shift register
--
--Description: This process controls the receiving shift register
-- (rdSReg). Whenever rShift is high, implying that data
-- needs to be shifted in, rdSReg is shifts in RXD to the
-- most significant bit, while shifting its existing data
-- right.
--
-------------------------------------------------------------------------
process (CLK, rShift)
begin
if CLK = '1' and CLK'Event then
if rShift = '1' then
rdSReg <= (RXD & rdSReg(9 downto 1));
end if;
end if;
end process;
-------------------------------------------------------------------------
--
--Title: Incoming Data counter
--
--Description: This process controls the dataCtr to keep track of
-- shifted values into the rdSReg. The dataCtr signal is
-- incremented once every time dataIncr is strobed high.
--
-------------------------------------------------------------------------
 
process (CLK, dataRST)
begin
if (CLK = '1' and CLK'event) then
if dataRST = '1' then
dataCtr <= "0000";
elsif dataIncr = '1' then
dataCtr <= dataCtr +1;
end if;
end if;
end process;
-------------------------------------------------------------------------
--
--Title: Receiving State Machine controller
--
--Description: This process takes care of the Receiving state machine
-- movement. It causes the next state to be evaluated on
-- each rising edge of CLK. If the RST signal is strobed,
-- the state is changed to the default starting state,
-- which is strIdle
--
-------------------------------------------------------------------------
process (CLK, RST)
begin
if CLK = '1' and CLK'Event then
if RST = '1' then
strCur <= strIdle;
else
strCur <= strNext;
end if;
end if;
end process;
-------------------------------------------------------------------------
--
--Title: Receiving State Machine
--
--Description: This process contains all of the next state logic for the
-- Receiving state machine.
--
-------------------------------------------------------------------------
process (strCur, ctr, RXD, dataCtr)
begin
case strCur is
-------------------------------------------------------------------------
--
--Title: strIdle state
--
--Description: This state is the idle and startup default stage for the
-- Receiving state machine. The machine stays in this state
-- until the RXD signal goes low. When this occurs, the
-- ctRst signal is strobed to reset ctr for the next state,
-- which is strEightDelay.
--
-------------------------------------------------------------------------
when strIdle =>
dataIncr <= '0';
rShift <= '0';
dataRst <= '1';
CE <= '0';
ctRst <= '1';
 
if RXD = '0' then
strNext <= strEightDelay;
else
strNext <= strIdle;
end if;
-------------------------------------------------------------------------
--
--Title: strEightDelay state
--
--Description: This state simply delays the state machine for eight clock
-- cycles. This is needed so that the incoming RXD data
-- signal is read in the middle of each data emission. This
-- ensures an accurate RXD signal reading. ctr counts from
-- 0 to 8 to keep track of rClk cycles. When it equals 8
-- (1000) the next state, strWaitFor0, is loaded. During
-- this state, the dataRst signal is strobed high to reset
-- the shift-in data counter (dataCtr).
--
-------------------------------------------------------------------------
when strEightDelay =>
dataIncr <= '0';
rShift <= '0';
dataRst <= '1';
CE <= '0';
ctRst <= '0';
 
if ctr(3 downto 0) = "1000" then
strNext <= strWaitFor0;
else
strNext <= strEightDelay;
end if;
-------------------------------------------------------------------------
--
--Title: strGetData state
--
--Description: In this state, the dataIncr and rShift signals are
-- strobed high for one clock cycle. By doing this, the
-- rdSReg shift register shifts in RXD once, while the
-- dataCtr is incremented by one. This state simply
-- captures the incoming data on RXD into the rdSReg shift
-- register. The next state loaded is strWaitFor0, which
-- starts the two delay states needed between data shifts.
--
-------------------------------------------------------------------------
when strGetData =>
CE <= '0';
dataRst <= '0';
ctRst <= '0';
dataIncr <= '1';
rShift <= '1';
 
strNext <= strWaitFor0;
-------------------------------------------------------------------------
--
--Title: strWaitFor0 state
--
--Description: This state is a delay state, which delays the receive
-- state machine if not all of the incoming serial data has
-- not been shifted in yet. If dataCtr does not equal 10
-- (1010), the state is stayed in until the fourth bit of
-- ctr is equal to 1. When this happens, half of the delay
-- has been achieved, and the second delay state is loaded,
-- which is strWaitFor1. If dataCtr does equal 10 (1010),
-- all of the needed data has been acquired, so the
-- strCheckStop state is loaded to check for errors and
-- reset the receive state machine.
--
-------------------------------------------------------------------------
when strWaitFor0 =>
CE <= '0';
dataRst <= '0';
ctRst <= '0';
dataIncr <= '0';
rShift <= '0';
 
if dataCtr = "1010" then
strNext <= strCheckStop;
elsif ctr(3) = '0' then
strNext <= strWaitFor1;
else
strNext <= strWaitFor0;
end if;
-------------------------------------------------------------------------
--
--Title: strEightDelay state
--
--Description: This state is much like strWaitFor0, except it waits for
-- the fourth bit of ctr to equal 1. Once this occurs, the
-- strGetData state is loaded in order to shift in the next
-- data bit from RXD. Because strWaitFor0 is the only state
-- that calls this state, no other signals need to be
-- checked.
--
-------------------------------------------------------------------------
when strWaitFor1 =>
CE <= '0';
dataRst <= '0';
ctRst <= '0';
dataIncr <= '0';
rShift <= '0';
 
if ctr(3) = '0' then
strNext <= strWaitFor1;
else
strNext <= strGetData;
end if;
-------------------------------------------------------------------------
--
--Title: strCheckStop state
--
--Description: This state allows the newly acquired data to be checked
-- for errors. The CE flag is strobed to start the
-- previously defined error checking process. This state is
-- passed straight through to the strIdle state.
--
-------------------------------------------------------------------------
when strCheckStop =>
dataIncr <= '0';
rShift <= '0';
dataRst <= '0';
ctRst <= '0';
CE <= '1';
strNext <= strIdle;
end case;
end process;
-------------------------------------------------------------------------
--
--Title: Transfer shift register controller
--
--Description: This process uses the load, shift, and clk signals to
-- control the transfer shift register (tfSReg). Once load
-- is equal to '1', the tfSReg gets a '1', the parity bit,
-- the data bits found in tfReg, and a '0'. Under this
-- format, the shift register can be used to shift out the
-- appropriate signal to serially transfer the data. The
-- data is shifted out of the tfSReg whenever shift = '1'.
--
-------------------------------------------------------------------------
process (load, shift, CLK, tfSReg)
begin
if CLK = '1' and CLK'Event then
if load = '1' then
tfSReg (10 downto 0) <= ('1' & par & tfReg(7 downto 0) &'0');
elsif shift = '1' then
tfSReg (10 downto 0) <= ('1' & tfSReg(10 downto 1));
end if;
end if;
end process;
-------------------------------------------------------------------------
--
--Title: Transfer State Machine controller
--
--Description: This process takes care of the Transfer state machine
-- movement. It causes the next state to be evaluated on
-- each rising edge of CLK. If the RST signal is strobed,
-- the state is changed to the default starting state, which
-- is sttIdle.
--
-------------------------------------------------------------------------
process (CLK, RST)
begin
if (CLK = '1' and CLK'Event) then
if RST = '1' then
sttCur <= sttIdle;
else
sttCur <= sttNext;
end if;
end if;
end process;
-------------------------------------------------------------------------
--
--Title: Transfer State Machine
--
--Description: This process controls the next state logic in the
-- transfer state machine. The transfer state machine
-- controls the shift and load signals that are used to load
-- and transmit the parallel data in a serial form. It also
-- controls the Transmit Buffer Empty (TBE) signal that
-- indicates if the transmit buffer (tfSReg) is in use or
-- not.
--
-------------------------------------------------------------------------
process (sttCur, tfCtr, WR, tDelayCtr)
begin
case sttCur is
-------------------------------------------------------------------------
--
--Title: sttIdle state
--
--Description: This state is the idle and startup default stage for the
-- transfer state machine. The state is stayed in until
-- the WR signal goes high. Once it goes high, the
-- sttTransfer state is loaded. The load and shift signals
-- are held low in the sttIdle state, while the TBE signal
-- is held high to indicate that the transmit buffer is not
-- currently in use. Once the idle state is left, the TBE
-- signal is held low to indicate that the transfer state
-- machine is using the transmit buffer.
--
-------------------------------------------------------------------------
when sttIdle =>
TBE <= '1';
tClkRST <= '0';
tfIncr <= '0';
shift <= '0';
load <= '0';
tDelayRst <= '1';
 
if WR = '0' then
sttNext <= sttIdle;
else
sttNext <= sttTransfer;
end if;
-------------------------------------------------------------------------
--
--Title: sttTransfer state
--
--Description: This state sets the load, tClkRST, and tDelayRst signals
-- high, while setting the TBE signal low. The load signal
-- is set high to load the transfer shift register with the
-- appropriate data, while the tClkRST and tDelayRst signals
-- are strobed to reset the tfCtr and tDelayCtr. The next
-- state loaded is the sttDelay state.
--
-------------------------------------------------------------------------
when sttTransfer =>
TBE <= '0';
shift <= '0';
load <= '1';
tClkRST <= '1';
tfIncr <= '0';
tDelayRst <= '1';
sttNext <= sttDelay;
-------------------------------------------------------------------------
--
--Title: sttShift state
--
--Description: This state strobes the shift and tfIncr signals high, and
-- checks the tfCtr to see if enough data has been
-- transmitted. By strobing the shift and tfIncr signals
-- high, the tfSReg is shifted, and the tfCtr is incremented
-- once. If tfCtr does not equal 9 (1001), then not all of
-- the bits have been transmitted, so the next state loaded
-- is the sttDelay state. If tfCtr does equal 9, the final
-- state, sttWaitWrite, is loaded.
--
-------------------------------------------------------------------------
when sttShift =>
TBE <= '0';
shift <= '1';
load <= '0';
tfIncr <= '1';
tClkRST <= '0';
tDelayRst <= '0';
 
if tfCtr = "1010" then
sttNext <= sttWaitWrite;
else
sttNext <= sttDelay;
end if;
-------------------------------------------------------------------------
--
--Title: sttDelay state
--
--Description: This state is responsible for delaying the transfer state
-- machine between transmissions. All signals are held low
-- while the tDelayCtr is tested. Once tDelayCtr is equal
-- to baudRate, the sttShift state is loaded.
--
-------------------------------------------------------------------------
when sttDelay =>
TBE <= '0';
shift <= '0';
load <= '0';
tClkRst <= '0';
tfIncr <= '0';
tDelayRst <= '0';
 
if tDelayCtr = baudRate then
sttNext <= sttShift;
else
sttNext <= sttDelay;
end if;
-------------------------------------------------------------------------
--
--Title: sttWaitWrite state
--
--Description: This state checks to make sure that the initial WR signal
-- that triggered the transfer state machine has been
-- brought back low. Without this state, a write signal
-- that is held high for a long time will result in multiple
-- transmissions. Once the WR signal is low, the sttIdle
-- state is loaded to reset the transfer state machine.
--
-------------------------------------------------------------------------
when sttWaitWrite =>
TBE <= '0';
shift <= '0';
load <= '0';
tClkRst <= '0';
tfIncr <= '0';
tDelayRst <= '0';
if WR = '1' then
sttNext <= sttWaitWrite;
else
sttNext <= sttIdle;
end if;
end case;
end process;
end Behavioral;
/image_component_labeling_and_feature_extraction/trunk/measurePoints_guide.ncd
0,0 → 1,3
XILINX-XDB 0.1 STUB 0.1 ASCII
XILINX-XDM V1.4
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###3224:XlxV32DM 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###2940:XlxV32DM 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c44eNrtW92S3KgOfpl9AH4Mhu7Kq2wVGLvq3Jy92MtU3v0IgTByG0/Syc725MxNivizZQlkvk9qJhl1E7f7f2QymgZTHvwFA0MDS9BMA0eDQINIg4UGCQdKOoT+gsFSrwRPg0CDWAdxqjdHQ1fK29U8rzTY6sAJGkgaKBpoGkw0KOHAINCgOjZ7TQNHA08DvDkGafKVbF18/UNuYBXiSff/wjDejNX+/ge4Ot/ctKh7vsHcolcGrs423WQQAubEurlM6Vbm7Vu2uzzaXXe75i27cmQ3PtrddrvTW3bVwK7N8xCZXW92u+rErpVut+vArg81kXwUNJA0UOWVQdWMClr8SALMbQK2R0e7idWnjvrd0fS8o29mIXPU5rmdmaNhn1EV3lgpmTMryIXmxtHA0yDQgPLdUZo7vOfb3zBb+ZL++gUXOIdy/4JTiMM/pU8WbjMuYbbm2+B7yPmRsU0WLJEJyGnEvmAatts03BanVZMJCDw7DliQG5pALxR5AbMPWDLFPMazY1EgphDDr7TDJGIasRg5phCbyvuazRwqvS+U9wWG1ffF8r7IsfK+pbxv4Vh5X8JZtlsXe16i+595N0Rs1hwLiGVfQlwXjrmMxbIkpo89fySA5X8xhsixDbEy135hmBMZg38xhsQxiVhZB9PHnnMdsbIO88IxjVhZB584NiFW1iGuHDOImTIvok852Ikwl1TBTMOWHZsKNjUs7li2KbftEB+mKk6tc+WGg0PdDbBa3+ADDBp2V7Xd7E0uX+lbzB8rfsLW5C0iVeKEL6TsFeA3XdF0ZaKBqduItDSgjUVutNXUp8JMlDx5GjQmljT4pPbvoXav8J4BtU92fpLawa4dUzvYfZLawa4ZUzvYfZLaMaWH1A52X4XaYQL8mNrB0VehdpjRaUztk7XvQe0wW6rwMi5woXacwiO1Vx7B72FA7ZjThdoxDQfUjoEfqN0uDdNHaneJYYzaw8qxntqXjWM9tdtm0/sjtbuVYYzaw8axntqT4NhO7eCB72Jn1A5XEscYtW8c66nd9rEfqN1tHOupPQqGMWpPkmM9tds+9gO1e8Gxntqj5FhP7UlxbKd28IClXE/tgO2+WE7tgO3rZ0bUTvFhquLUHqidHOpuQGqfHG4vQO3yNj0yu5ST/OT2D8Ltk0MPLacK4vZ1JaaYTEo7U+idKRa+aHWSKi9AuLQlyzmxuPvdEJ1gu+Hk4sQxi5hFbBIMU7HtsJSaFcuvz1+TDzlvoQhKV5IUJPLymbgfJHFhodNYlOptfVKUQpKIsSgFu0+KUvB3G4tSsPukKMWkHopSsPsqohQc1WNRCo6+iigFR9exKNVbeg9RCumyFEWJC1xEKU7hQJTi9zAQpZjTRZRiGg5EKQZ+7DfZhqWHftPMMN5vchxj/SbPsV6UUk+ihMpFqTcMY6I0Wo4xUTpzbBelzsc+diZKAZs5dtZvIqwXpbPp4juIUm85xkTpzDAuSh3HelE697EfRenMMSZKHceYKPUc20UpzMvUp1wvSgHbnxNclALW3pdz8FyUUnyYqji1B1FKDnU3oCg1s7BFlOpbeuR25+yrUXt2LOU90N8by7dr7v5DhE/PBXl/5P4GqnuTAe1F2/13UQRGKjlmQpniVvdt7UEx1n3b5S38e5iwTWKesMo17dp6/3l+BPfVmB/B/fXEfavWM34kx6K6jyOJ+jES2FN/nkDNLN1jTbHUSNJCCsrk1WlEL/ZA4tM1hY6pVMWFpb5gTiCNwKYm5Y6phsW8wYbV7ZjeMYl7T/fctGO4wUpVCCTvjoGwXJGAL757rmCKfJmSdA2LDUNfAPMNW3Ys+6KJ6AqDNUyhn0qQL7B/VKz4EiJ1gnBxOMlLuTIM6ynYxzJWd9WKtXpKY4tfUj1l4KnTRkD6rKc+SpNf+uWiyT8r9WSTX57UPX5qduX6lt15YPeq7gG77lWa8WDgohk/S/8qzXh5VfeAo/Id6h650S/VOG+1+yib0Ms3+HZDOtyQpaKXpE8xpXnTVO7Wdw0K2whvxNY375q3a+BWrNfKrfFbsV5jJ8mdPW0m1+d63R4Ff66vBdzGsK6GCER/NCPnzXJ5rEu8pNqDnttrHcA0x/YaqWv45xhYbdX9UFCxviZzK8f6Wq79MFEwVgMufeyH2jGsHOtrzvbjinysY13iz+11bPeDjXyojb3O+TJRLtmaiFSsF+9rsb5p/gsSZmZXrH+LcvXTRVM9Wf8iVNqXKFelzCfBcoLVm3AX5Ylbwq7vl1ae+OmSsPoK5KpS+Wkay1uL6JU1hlPVrF6s7JV1xVDN6mRVr6wJQ2Vdc57Uc8FQsQIdCW8v1eUkPsXlRxGXwpkrcbmEJ8WlQAExFJeLfVJcCuzTDcXlIl5FXApchaG4XOSriEuBncihuIz+fcVlnreqHbNnj+ISdx92A4pLQYf0MKW5uBRON8wdxeWy8jf34jIkjvXi0i0c68XlkrizTFxG/lwvLsPCn2PiMjKMict2EqPMCBeXgT/XiUsRBH+uE5fCLxzrxeXSx34Ul5FjTFwGjjFx6RnGxWUf+1FcBo4xcekYxsWl58+dissc+1FciiouMZdsTURL4hK9H4hLzEwmLo1UpohLdfOPVAr//Xep9Kgfmc60919FsMcuOWuOi/tvR7t12UeSM4SzjrjV4ozGjqqSqc/l/k+QG7hvLzriIfxAR/zBZ2qNs464vP86yvs7LGY69KJN1/+dD71oQ4pZrvVvCPZetCHFTB9y12821OM1dHh+7zfb7n3m0G+2Xb85HPrNtvWbYfM+9Jtt6zevKR36zXZX7yqYK/Vu7ad4/zjHv6fL49/h6ePf84V4t/Oz4j2n3tUxbfE6x7TD5TFt+TrHtO3lMe13Fu953tq5VHsi3nHzYTe4ciy2HbGGlD4cp/X7Mdx52Bmubz7tDFfstDNcsdPOcHV2cMw4DDvD9bnTznDBzsV7mZHRMWpzEO/dMePyXCfeVRPhFTvtDOcYRp3hip12hit22hku2HlnOMcw6gxX7LQzXLDRsXszFO859lFnGHOp/jVANkF/WxCG4h0z89gZ1ped4fB/Id5/686wv+oMR/v9neH3l+lnnWHfdYbVoTPsu86wPnSGfdcZ1ofOsG/aMpjgrrSl09sv+yL+B0IEhyY=###3184:XlxV32DM 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###3140:XlxV32DM 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###3024:XlxV32DM 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###3052:XlxV32DM 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###5388:XlxV32DM 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qauJJjyBQwR8BeTqGID+WYWtVA0iGoNVE56bL5qCj7AJHAqbN/k3mJLPdvcfmjZet8HwFJu9P7wPztWVZkx4evzc75ud1Mw/byaX9y8kkmZnR2cbTO1TjbtNK9hORg8Eml/ctNpdT4fklMi0ZPCzTi2dXEaX+hqTqypcb1DhETS4tooVIC1OzI6YyAYR6I/A4V7Fq1Q+qrDbUeu6bdXHjaFQq2qotKxU1wiRlXWc5maATBFtN1KSmlu2W2E3/azSJMmLbjNlVCVis+9gQC2hSdxotLdUX1iIy64Wx46RLha46HZX3NwW7tKOu7amCCjktwo5vQ06/j8v8Phy###5400:XlxV32DM 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13f8eNpdmV0S7agKRqcUQY2erh6MxDCBfuzqud/8GNau+0Z9xQZENMna0vRPmiX/9XeTy5S9pWVe6kQtf/1d8iHL4TMf1Xqor/mqG+oW6mihvuaj9jPU17zUXXdb6mfeqtT8qcu81JbbF+Ezb1WtfOoyb1V2j2W+5hN35NWHx/xSvOpEvX3TOD7f21y+S52oTw29ff29za+cV52oT2VVYi+qRJGvOlHfeiv1Vuqt1Ftf3//+2VO3P9ce/HtXdv5JY69fvX3Wx8Hy5aDLQdLofy3f7vKY41X/+6e0eVy+Kad//x5d7Ha5Uo8huszufYS6yWe2FGbfRviWgUPG4SBCxhe1ePjm9pm7fzWMavMztz1FBP3q7adEtlETwQbBCsGcYCxTJ8FqRDgibhtRQ/Vo1KZR5G4lgu09glXhZ6xCCz/b+RkLqrTvqNRAo0ZEaO2MYDvBflbcw6HUFg7p24A+zy9FPw4nwh4RxkYEtjudRIi4x2QDRkRofaPIHg5ntK8dMQ/7jCk5Z6TwGX2oe/ThumSihiMWf9iX7Znw6+iMJ24s8zw34jbKoalH9Ky2RDYjWycb56KwTI1lVgmHLbG2n6a2aFTeo7Jzi4k6zuiDTZpahGxGtkw2VjyEbJ1sQjba5xvZwrdp9OG6QyLbxhlilGfjBET7+kE2K1FvkQimznn7OVkxqVc2Dpmx881IkUnBkW5KikpiRq7E/J5xP1z3acy6aZyWIWyLRr21sptbrE1nTJQYxzTuyX4eiRQnKehkPchG6Ru3ETeMMhpyRDl1xjLLEeXkEdnOHFs4aUlO0TNxaujUu8cqRuWunlw2B1NtTHUuZDvJRqP8JJuSjQ2o4VtGtCS32Ld+RvvajMRHInG0r48Zd4laBJMW7Uu1ky2uikwf+tnJJmTbiduIK8TlLtmi9HFy2ZwxXPmI7dY9JrUfYTaLciZ3lMWs98E8CE/IxBOynHTyoCWxx9fPlJ/x6Mh08hAqG1TGFnrUa4mfbVFkOyNxLlGkKqfwp5M9fFMLdSvcMImmbjTKEym4FDjdZqx40Kg2SBHbkjZmkqFtOwcn3qNGVo5pih0ag+PUY4w6o9H2QjaeARu7KRxpbiP96e9gA7qRIhz6iAHXEqZsPEV4FkqO/g5G2fbYwh6jcQUj2zDicshyJlgmGLvJ4e05akjCbR9b2AfBWo/KZMbBSQdFspv5PIg7iVuIy3j2TFymj1PYG7dnPLCHKQ7CKyDvconXpJFjxY13ROMEdOHt1RjPwRWkP8HYocRwbXSS952N97N28np7TiKwm2njZ7z64LtxjtPPVVx49eFV2MqOySoKLy4ewYbzQt/DYcatfJl8rDgP9x4TVXPC5Ph37uo4hWNMvocYo9F/TF7HW0z12E/USDx4oAyLynrdMUnMm8KQqLdVsknn8yxStO/T6Pqu69erwvYnK591ymfdZfZyfGqvh4bDe2fqk2PHN8z18aR8yz3qyKgb6mcOu9+/Rp6PWZf5FPm+mvd9S5HtHBGspignf2rf+xEp3jl6f1bjZ2Xys8rPWpg7Dkc41FZw6DgIDlFkrZFtfeS8qqBGU9dXxeMgDTPjEMtcp+w191iQH5iswtjYOVH52YxVrFF9HPTHJEIPc02tMrWPr7CxWw81sRdbIQLzsEfpa8Kfn5Uzfpap104cBg50shZ8l8N//wy7Xjm3P+VjGJKsrgl/zaJXez5zx9zGMlueusxn7iNCmPv1kRjmiAjXd1Ko9Qs29VMfUrAcbhCwHGwTfAXfiW/GN0e2/hVZxMPU+hVZssSC7jfriNuJuxE3Sk81Et+fNsu8P21WhPvLJXwd3x3fGr7HFpVZi8o6qygSpjpxjWwHKZQU38+6dsNkN4+B+q34eXEO06N9+4Eaie8xWqTgfmSvYPdj+HPQgRpdV2EvUsO34hvDdT9lw6QPJ2r7Wt3qUTDZY2bnvreX6SV+5pUNGAWHb8WtzYxZI24qqMIJ6ByRwhH5UVdl1zHsV6ce7rhO4RhxnJb5nP/8cMeryus+OYM7zvI+2G42vJ9/hTpCbfI9wV7fZzhe36WOUG/fazfycljmq96nfqmP+cZNHsEe81Gf4r9y9vDdJGq4d2P97FVHqG+EG46utUXiTx2hLt8D3wPfA9+DGjI1ZGrI1MCKk9IHurPt9GGnhkbiRraNFFuoN7ZdNRTa96oj1Nf3fpIv38v8fF91hLrqLdRbyDZJMaPeI/pwm1/pR/ThVZdvxbfiW/Gt1JCoIRFB+Bl7fKPYFXeUcHjVEery3fFluF51hLp26GSHTiIoP9NQzzgXt/k5nHEuXnX5Uu9JvSf1noU+CH1gxWfiZ193Xi72xH2fI4/Dp45Ql++O747vji99UI8a1Img/ExDrRpxKw5VI2798aXeSr2Veit9yMxDZsUxyp35fenTG/c2l8NSR6iP74OnXt/bXL5LHaG+2aZHvdMj8fSodzo1dGro1NCpoVODUINQg1CDRA1nihpOFn+mqOHkHOdKzzhZerCbByr91Z9OFkqP2bnR/FfkcdKdSUtmRDha9OFoEexVR6hvXIu13eaXwmJtr/pmO2LfbvNLfMS+veryFXwFX8FXqHdQ76DeQb2DepV6lXqVerntM3dqZqq10/UeqnDvCP216PprrnorRdaobMR4vuajPszvrfc2l8NSR6hvtq1Gz7ZIsdQR6pvtjHNxm1/iM87Fq64anBqcGpwauGG2Rg2NGho1MDvO7Diz48yO/5wLnrz555aj63qicv+qsAqjdKPeTJGZ7kxaEv19GOWqd2d2dmZn554cnPnBmR+c+cGJrRbzW6PIpY5QVw2FGgo1FGrgeTG41wf3+uBej2fhiza/GiY1TGqY7AXviJk3JmWHlB2SxrmInb+/rL9yOvdv5dKt3LQ7o7FzlzTuh8b90LgfWjx5H9L6Prtvcz2ElzpCfWvIR/QhH1FOPqIPOe7f+318oZgHxX7lMFEtU06mnEY5jXIa5TTKOSnnpJyTchh7YQN+XgQyL7KZq015zGilskw5mVZzV7eNyrhpc1yvD1Befcj0IdOHzCHrPEI7j9DOI7RzxTeu+EbixhXffmrgGsxcg5lrMHMN9kwNmRoyNWRqYDQao9EYjfbzaGbstbEXG3uxsW/GvhnZePI2Dk5m1rOwCt6CenxqPAh9zZkyZ8qcKXMmHH/h+AvHXyZxB3EHcQdxB3GduE5cJ67TByb154NUeQhroQbOsXJ4hduTz98H4696U4+fpR71prhsHs6/6t04bxvnjY+KBzt+cY24Rlx2M8Wrz21+cVO8+rzq6gOvdcIDUOmOKjXsJN5ZBePJ5+/zp8Gqt/CzEp9Rr7p86VmhZ4WelZ9XH+4S4S4phZ/xQeoxO7f5fZt6zM6rLt8D3wPfA1/OW+JzBxRxc9/4GR/mM/btNj+HGfv2qst34su39Jz48lhMvIykkwidn/VQO3E7cTtx+8QXZNBBBh1k0DlDiQ+FBPjoLLPH2p6/X9YnbePTvvFp32I3n/9nVg37GcH2M2rY+dhujbiQkdaIy160LeI2eEnbIm7jXGyTT/ufrvM6Huf4gemROLMKxminO8acGQ7GnFn4Pv89rbVVUEQFRVSwUO34dnw7vsyD0V+jv0Z/jed8og+JPmzs/PZTL6yicgqNo2ecNwE3CbhJwE0C1BHWJqxNWJustd3csqX/55YCt3S4pcEtFUIpcEtHNbilwi0dbqlwS4dbKtzS4ZYKt3S4pUIoBW7pqAa3VAilwC0d1eCWCqEUuKWjGtxSIZQCt3RUg1sq3NLhlgq3dLilwi0dbqlwS4dbKoRS4JaOanBLhVAK3NJRDW6pcEuHWyrc0uGWCqEUuKWjGtxSIZQCt3RUg1sq3NLhlgq3dLilQigFbumoBrdUCKXALR3V4JYKt3S4pcItHW6pEEqBWzqqwS0VQilwS0c1uKXCLR1uqXBLh1sqhFLglo5qcEuFUArc0lENbqlwS4dbKtzS4ZYKoRS4paMa3FIhlAK3dFSDWyrc0uGWCrd0uKVCKAVu6agGt1QIpcAtHdXglgqhFLiloxrcUiGUArd0VINbKoRS4JaOanBLhVAK3NJRDW6pcEuHWyrc0uGWCrd0uKXCLR1uqXBLh1sq3NLhlgqhFLiloxrcUiGUArd0VINbKoRS4JaOanBLhVAK3NJRDW6pEEqBWzqqwS0VQilwS0c1uKXCLR1uqXBLh1sq3NLhlgq3dLilwi0dbqlwS4dbKoRS4JaOanBLhVAK3NJRDW6pEEqBWzqqwS0VQilwS0c1uKVCKAVu6agGt1QIpcAtHdXglgq3dLilwi0dbqlwS4dbKtzS4ZYKt3S4pcItHW6pEEqBWzqqwS0VQilwS0c1uKVCKAVu6agGt1QIpcAtHdXglgqhFLiloxrcUiGUArd0VINbKtzS4ZYKt3S4pcItHW6pcEuHWyrc0uGWCrd0uKVCKAVu6agGt1QIpcAtHdXglgqhFLiloxrcUsGSAqx0VANWKlhSgJWOasBKBUsKsNJRDVipwEoHVt7q/aXwEtWPWzrcUuGWDrdUuKXDLRVu6XBLhVs63FIhlAK3dFSDWyqEUuCWjmpwS4VQCtzSUQ1uqRBKgVs6qsEtFUIpcEtHNbilQigFbumoBrdUuKXDLRVu6XBLhVs63FLhlg63VLilwy0VbulwS4VQCtzSUQ1uqRBKgVs6qsEtFUIpcEtHNbilQigFbumoBrdUuKXDLRVu6XBLhVs63FLhlg63VAilwC0d1eCWCqEUuKWjGtxSIZQCt3RUg1sqhFLglo5qcEuFWzrcUuGWDrdUuKXDLRVu6XBLhVAK3NJRDW6pEEqBWzqqwS0VbulwS4VbOtxSIZQCt3RUg1sqhFLglo5qcEuFWzrcUuGWDrdUCKXALR3V4JYKoRS4paMa3FLhlg63VLilwy0VQilwS0c1uKVCKAVu6agGt1S4pcMtFW7pcEuFUArc0lENbqkQSoFbOqrBLRVCKXBLRzW4pUIoBW7pqAa3VLilwy0VbulwS4VbOtxS4ZYOt1QIpcAtHdXglgqhFLiloxrcUiGUArd0VINbKoRS4JaOanBLhVs63FLhlg63VLilwy0VbulwS4VQCtzSUQ1uqRBKgVv+D2IILEo=###4960:XlxV32DM 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uJ24nbiduJ64nrieuJ7amAD78Xa8HQ6FxIVsByl2l4Ssf5P1/UHko16b1mx5q7wzhfv+M8/+qXxhl7fKO7G1JeIm4ibiJuIO4g7iDuIOio8UH/FygNgNByOxka2SYh/b3591JodpfoDtrfLObPPvPt8WvuZKvLxV3g97HsKe2ovlrfIuDhccLjhccODItIuKf7wMpDn4Nkg2siVSaC/mH5y+vXjNtVDLW+X9Br3peP3+qPjNfNPx+nkXlqu5cTU3ruaW4RDhEOEQ4fCz85WKK17Da3DwJPZkc6RgzXQMTnMvn47B5V3YG+wN9gbLpWZc7taIcPGZjuIed9xpLpLLW+X9sEnXTE+6Zpa3yrs4FDgUsnVS6Fhpp54+7dTgLG+Vd2Eb2Aa2gW1wSHBIRMh8lv8PBqrxpw==###4352:XlxV32DM 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OHpFlOlb9PNHsawyHfX/iK8f3a9XREnHZ8uPbvtrt2M3YXf0irbMhvb9BDca2hvxbGhtnQ3tVYjOFD/X5VGxl5pUW68f3WhoX/ris+VHt/2127GbsPs5ecesGz8O+uSW08mHxoSxj4eO1eKHxCxC+S3c1/KjG05+RDU+az+6y1+7HbsJu31kff6eHD9b+pxZtd3z9+QYdb994/fkbw6NLZy/J08F0wAcnxV00/XXbsduwu5w8rzmmfx+UPVJzaeT5z3P5Efjx2rx42sWS/8WPu/rRzec/Hh+fLb86La/djt2E3bHJFDPyGT81DsmgerKZK9XZHIoxJUePwsPJ1n40bUf3ZgEqu98VtD166/djt2E3eFk6ZHJ+BHaJ+2YTpY9Mhl0ZqwWP1hnkZFv4bJfP7rh5Mdh4rPlR7f9tduxm7A7nLxtksTv53GfhGg6eZeZnY9ojdXip/Qs6vMtfJfyoxtOfuwqPmP+uv8fbP41gQ==###5692:XlxV32DM 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###4928:XlxV32DM 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p5m9xaR1pNFY7uLpVNDhLT/6umbLv1CXxmL2Fr1x4TSz5Zu0iDQaS1Gri7ygjL3KS3MJB2Efh91j6XLFarixZTnXZSzFjKUqoGAszYzlUkHlZyyJsToWs7eYaZafsZi0jjQeS/N0KujwWJKva8Zyoy6NxewtZprlZywmLSKNx6LbeCk6lqZfinDIY2kOS2ORdV1DHotzXcYyzFi6AgbGMsxYbhU0fsbyMFbHYvYWM83xMxaT1pHGYxmeTgUdHsvj69JY/g+GyIgx###5128:XlxV32DM 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et0vSoaoGaJW9FZJVG/zQtR4SOEfgIhKa6rPtnBHYRG1oXAjUTPlVVEziXobwBI1k6hGsy0qff3h9GbAq/bV2ym9XRYgor432f8BnkdZXw==###5168:XlxV32DM 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eYFrV4JpDN1GanHMYHp9KI+svPpvh36foMUZbFTYOWEnWISCG+lbBWm3C2ctvj00LrvFf5//dUPZaNooFwQF2Q7E1XeVT4v1E/aEf1jMN2H6s3yg2K34/qVMi6p9njLr2NM69ineqH2L/wdcg5Xl###5508:XlxV32DM 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hU694wQx4PqrSQnh+gi8EW+BqcFmJTAjHp6tiLuGewtch5h4BbaJXSewBKaJKbBMVCUgJiImYhCBiImoTFwfgWUiKhNNCYiJqkwQRcVExUQyH4FlomLCHUpgm8gOE0miyE5MZKdMXB+BaSI7ZcIqgW3ivBQXUci6oPvaJsaH/vGn/O1H5MLreMkCKy/pNQJ5iy+e0/276vo2YFlwWJj/f8j13lv2+NgYu9brw33PsT582Cd2uU4ePgiMwIqs3Am8utb6OrSNqTdjm1+Rw8T4J8n09xpVmMPfF45u6dst0y3TzdDtnbHuvFeF3pI9d7eVane2+BF42dwC42PjvSBHYLK5uSjTs3V8mq07oPwTkMUz+wo0t5eVLnx/NWQ0qNgcGhwa3IziFCczYWYVZv4IrDAzYd6HEthhsmQOvJzcK+IaBJ8wPU56nPRTg/tqyGhQYQY0BDTYGUXdTtZDwqyHCrN9BGaYQ+D/K+Kp0A==###5332:XlxV32DM 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vkRoRoQORGg7hF5DaDCErkJoJYT+QWgahE5BaA+EnkBoBITqXyj5hTpfKO6Fil4o44XaXSjYhSpdKM2FelwowoXKWyi3hRpbKKyFaloooYW6WSiWhQrZIkaKZYsYqZtbbemoyhxqngrOOx29rI5eltGT0ZNKgEPMe5zHITLqvPVuHuJ3h9prUp9ioh6XWXnP0pHCmoPp0XOnV9Oz8Ft6GE6YR3eAIXc82TcqZKEsllnqzhYlEoeoBcSpFcal/5TaC+BJnYKS8qoVwEvVO6tTRLq2sBTsy1vwYbY6tItX0Pqgi/8HJji6/g==###5608:XlxV32DM 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###5736:XlxV32DM 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###5756:XlxV32DM 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###5628:XlxV32DM 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###5728:XlxV32DM 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###5348:XlxV32DM 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###5108:XlxV32DM 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8cBYD7lLiL8txN8M8ZEhfuO+sDDE2x+BHvKnaqem8cMDyNJSSpzNA9Ame96zewDaZD+UP0CltjlDYwL+D/LG2Ic=###5412:XlxV32DM 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InmgnZ5IHiKxZWLLxJaJLRNbILZAbIHYeAvn/7V4tt9s9/x68sutUaiSclJ9D9X3UFHcRpnbKHNzZW6uxKSQuHdKIn28889Jok6yc5OSmzwYgqcLT66Kk3v9oo8v+viijy/uvsC5Bc4tcG6BGzExRyXmqMQclWY92Dj7osIRUJx90a0a2zP9rXCE+Ux/u1V9yJPr8uR2q2BtPtBDkR6K9FCkhx566KGHHnrooYcu3vmLd/7inb94LwLvfOCdD7zzgXlyDk8DtpqkUmWpVLgCNzMx5f8HcxqehQ==###4916:XlxV32DM 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###6040:XlxV32DM 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###5524:XlxV32DM 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###5460:XlxV32DM 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jRvdP7B0GyUPx1RZN8jvPhqt2XNA8k8D81YyObYnI31p3cUqUr2XQcvLyfIocgJc+atG2FylsSgPqV2Akwc8sHkZpOJcJKDi5RR6yeULmVSs3MVUmANhqpb3pxiv4A4gVylGevmvSGbIAJyK99J8/snQMzTeWO/AWfrALVWWPklRbGXViPRqUAzXWAMpkTczb/+VTlBqksaqlKgt0nPnKpI+MhvyqzSoKgyGiOI1h1eyU7ykr3ikrzwX4KSveKRvb+B2uxm5q6hyWf9mJ8gIOIk67Wb6XcxilmtoAAeGUxs/1SdAxjzJetsFOHrxsjLYhx/rVHlkQR+X81DGPuYCnC8rHlm8gCqADoauGNIFIAalwfAX5ftSMcM0imFcgMMwjWJwAvAAeLUi4jBD50XXXqNQjwqBf2kmwGb4TGYInW4tGfCJ/B9R07EW###5432:XlxV32DM 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fCP2to9v87gtsN5dVWOGAL0DZHuP7udjyQLkDDB03BbYIdI7UZXw+3x1BlkEWQeZ0uCY7HvTCm8Hbzi8vGrzOC3k1Wkhz/8y4zgUAE7jhHu3/jsIRf3Cz+S+SOXFKQMCVZC5s1L4DcOATv1CMFQL2K2XWdGbufUQ1Ho52NN6kTNarGxrSEW6nvXOFlDAcCZg/583/itJ0CgfKKMoCdRsnrSfl71NTZYnk4IqJzv3aLekcvkrYRxuU9mnUpkSpsm8FcybarpxG4Hj4CkkiPqwgEANJAC6BQwAzrRwyYB4aVqKmpZiADQtXU3LtIACBvICqdHhhRa5LCBQ30lEzmkBg/4GAS9uBRAvuvKiGwB5seBFDhZQwEBeINQLXqDPW9dlAXuIpbq087GAAcBhyHqI/wGkPee7###5888:XlxV32DM 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###6036:XlxV32DM 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###4908:XlxV32DM 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lYpYKYiVilj5et/X3ZVPDq9vo6VbKrqloFsquqWgWyq6paBbKrqloFBGdEvF29EtBYUyolsq3o5uKSiUEd1S8XZ0S0GhjOiWirejWwoKZUS3VLwd3VJQKCO6peLt6JaCQhnRLRVvR7cUFMqIbql4O7qloFsquqWgWyq6paBbKrqloFsquqWgWyq6paBbKrqloFsquqWgWyq6paBQRnRLxdvRLQWFMqJbKt6ObikolBHdUvF2dEtBoYzoloq3o1sKCmVEt1S8Hd1SUCgjuqXi7eiWgkIZ0S0Vb0e3FBTKiG6peDu6paBbKrqloFsquqWgWyq6paBbKrqloFsquqWgWyq6paBbKrqloFsquqWgUEZ0S8Xb0S0FhTKiWyrejm4pKJQR3VLxdnRLQaGM6JaKt6NbCgplRLdUvB3dUlAoI7qluvf/9yI7sQ==###4780:XlxV32DM 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###5824:XlxV32DM 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###5804:XlxV32DM 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###5828:XlxV32DM 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###4876:XlxV32DM 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###4168:XlxV32DM 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###4316:XlxV32DM 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###4284:XlxV32DM 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116ceNp9m0kW5aYOhrdEYwxU1vEWYGwzzCyjnOz9cS39NLrWHeRUKZ8vjVBHU/Wu9TJhM9aYlO69TvJm7/CRk+BJcJfCPnPI4FcKYWmfZfA7WTtzyOBZ8Cx4G4yfOWTwaqybOeQrh61JNSafP7IzYZ9lcCe4E/wy/pg5ZPAkOOTTXvEznsNs8SObdOVZBg+CB8Fr2tLMIff2BT86r+7RV3In8brNMnhNrswcMvhh3DVzyOBB8NA5jQ/6xvgggzvBneDQN/gl9JsET2J9MF+sD2RwzBccMjjmCw4ZPAgehH5g79APZPAseBYc9t7Xj+W+fmzvff1YBi/JbDOHDL4Lvgve/rrPHDL4aUyYOeTB877yvPw+Ch4FtymnpX+We/spx6V9lof9bnG13y2u9rvyIPjwP/jH6l+H4JC39t8cb1L7v7MM7gR3gsPewSGDJ8Gl/UPfsE/IPT4KHgWHvsEh9/ZZ3719ljG+Zi5uHh9k8GJ2O3PI4CHtfuaQe/uCG8FtsnXmkMHPZO+ZQ+7r12a2rB/Lff0Ed4LbVNzaf3Fr/8Wu/Re79l/82n/xa/8rd51TfoS9Iz9CBg+CB8Fh7z2/dvvm9gU/BB/zJz7mT3zMn/iYP/Exf+JRzM8JLuc/1h/9Y/3RP9Yf/WP90T/WF/1jfdH/yiGH7M7Z3z55Y5bBo+BRcPgbOOTePvtbb7/7H8+P2+vzY3nMb+VRcPQ39JfTqr8cV/2h//NY+z/L2j/xKHgUfPRPfPTP7ff+uX30b+r5rMfln3xU4/3IJm1P+y2RxUefhmT5fTEnzc/vj+zSbR85hie/b7H4p95Iu3n7/jDlkUsI6e374NtyPfme5DPd98Mj/d4nczzxkH8vv8d4Qkw8Pho/5FBtIHtJFK+NyY9s0zP+9tEz/7v98fZ9jO6J53eKx9v3MdJ4iilPeweP39RSZh7S4d6+3zHeejzrtZf6rGdumvzILQikllVN9a6Sfrz/yCWS3Lw8fOTTuOPte8ip2uPt+3C57SPHZK+375MnfQTW98H6q9d+0HxJzjGYt+/l+hh/X2y/tD7Mfck0nkz6cYb0f1w03szjOwPJbZSe9HeVZziexnvF+7GXzPO7w0X9N8she+LxlM2/2av8/m7DfvKJ3Qr5y3ZTfvWJeH7swXv2l3p4spctvNrDResbE61vtGRfV6LxVuMf/Z28flJfnu0llkz1bXJP/8GT/jez+Xk95PrI72X78J8SM9k3t7cV8r9otye/eo4XdyF9WY4nWE98fwZv1/Uj2fP6SXvWvofc+nnkwxv2t2Bnew/XYx7j96J9+f1///2dmo7cH/PHbu7ff2xNxx/319/tz/LH+sv/9b/21/zH+3P71yfv2n8HnOSKLtKg6mN0Z2anE3JTeaKij4xmr+R0njzOhEhygVMKWfZ3sJFH/j3kC0ZvyOhiIKPeLnKqyEZd2ImDJadE0PFsBMmTvHHQOri9OxwUtDhJlOt8+B44aLFRSxnjab5KTlYo6ezcfuD2ci7cv+MinebTNPXIWMTRPi0yZBiVlNF/25JyEiCnhtNa3gMf7IRw+pr9OTs9nHRP4Z6DQrThnIOClGV7rfh7nCpFR/q15aagaRd9+UBBEevnOSjK9Sn8fbHktHJ9zouSfuH1QBAwHJT3QEH7NpTkpAx7qXbn8VD/l9nZyYiXli3n8d0pxbfxavLBSfHm/jB/aS+afOL3Qpb6uAOKHtKnR9Fj46uszQfy0e2bgnLLRhQ0DfmT1LeUpT9+zV/Ygxz/nqgoaSM43+RUHR/qcZDn+e0XJUFnKGhrMooWn4J/+32M8Dfi0j6+4lHw9ePVO9s75DbQ/fOHlE9DQby2dp/gzvKVKelvgeIl2mubj+d3rXfzFm9rugv5H8WDw1L8tNzf8cl7zw9anfaRIxUdGzfx9XsRj52leK+2J2VL7d/pfuK88xetPw4lzfnEh5g5aQv5uCh+GE7KSHIo4qS+pHx7SrIH4m0M96wv2Z6UtfWEjO9zKw5JfzT/6mulYiBUmve7LMejja9t2bmopvZTMK/rLWXo02fm7L+jiCB/Patbiq5SKR/n4PhQnb6X85P2+GWfYrxSlvYE+2h7mPPpR/Qn5Yvt60o1vMmG65W2t/JUXK/5yYZiKd4iP1HRa7J79JVLesbXilfaxPDvYyD9lEr8ZF4y+cudVjlBf0L/iYtQjGdLJPf+w2Zn/cv2g6FNwhYo30vZ5POc87v8feTv60XzuU1x6/yp6Mf8P9ssypc8f0/8Yv71+3As85WyXA/YK9qX7UnZXWXRT1PoE2d2ridv3hQWjE/IsI8QNv8mS33lstl5vpAd8ocS3zCfb3nVp5SlPX7ZZyD76/Viinn+vQ37MetHyi3d5nmT+WV/X/N1+yw7PjQY+XWVQ683qJ780o9YL9m/9BfUp5jfzt9rsg1+m+cr49teqB7s/i1kfO+8f+1fjlfKsr+v+Cr0KddP9if1J+PRt7y2dxhqL3I9jU01NsVSxv7Bcb13tR0D1QP7M48t35EOJciupPw5TaFLs2ze5GxIrhG/W2XMt/lfmfODlJshnb9k5BNNhj41ufnJqxxY3z6TvqQs9X2Yy8/1NA45L4ND3nfe9E/1cDm3eT/bD1kTHapq/Ew4hF7r+X7J3/t/5+j/a/+GQ2ZuX+PoX9brOORG/xpH//CfGHGoxofs3L7G0T/2k72+7o8gnPnFI3PsVwvHk6E/vlRQeFNmfTtvGP3TpYbGI3N53jD6p0sVjTtDlzJy/wNezJZ+8fa3PB+C2ULxvF8yJbpU0vjBXO6PxyUpX/KI/fK4ZC3+7TxlXKLS/DWO+WM/OtYX/WP93znWX57PjP5p/TWO9f/aT+IS0ez+F9+Zy/1nv2RNfKmqcJN29xrP+yOYHH9x+F/kfAT/Ho9wyL80Dv/DIayvflmflPiRjcIv5iHT/HD+BO4NXaprPBk8Alr39/0RRbf/d97tX9Qz/ZEB7F/hsH8ZX8G1+Auuxd/+yEKJv9MjCroU4/Oyjfc7g9OjDo3bZPa388bxyIMelWj8ZK61X5N1v3iT+dKC2g/RhvURCD2q0XhlLs9D+yOf5K5f/GAuz0vBm+Wcv3gweKTElwi8P+uPnGD/Cof941Ki16fMYf8ah/3jUgTnIcN++ZGXwjF/rG+5+FKj+wfNT+Ny/sO/aHxa/gGH/2nzg/9pHP4nz8f7Iz/Wr8a7/sV5N3jXv8Khf1zS4ZJnPMIg+9c47F+rL2D/Gof9y/PO/ojT0KNOjbdt8/5239IfmSZ+VKrwi7nc76A+g/41Dv3L/Rg49K9x6F/uB6/s85z/NY78L/ej4Mj/Gkf+/7rvsvbZh/T4o/BD8NZinTn8T+PD/9b8Nh5pvee/8cjrPf+NR1zv+Q8c/ifr657flPp75Dcn7tucyJ+kf41D//I8I+Qtrvb3zjX/B9f8v7fPHPElFTrfRnyA/2kc/ofzQl9DWuMXP/JWOPxPnvdEm+7Z/jUO/cvzJnDoX+Oj/n2PL6P+feeof7/uW7B/4fpX46h/5Xkd1gf617im/2E/7/of9kP85PXdI/kX1gf+p3H4n7yfHfXLFn/x7n/iPDPlutTfGof9y/t4cNi/xnv9Lc5r20Zxn+1P47A/eV4MDvvTOOxP1lcjf73XXyN/eb4fJ35H8u+RH33+xTF/eT6I/ID4r3HEf/leABzxX+OI//L8EfkR/Wsc/cv3C+DoX+PoX94XRHvkxf4UfvX4vN5HgEP/Gof+5X1HtZed56/xrn9xnwLe9a9wzF/e5yA+uB5f3znsX94X9fjC9q9x2P+V9jLfb4S8uzn+aFyLP+Ba/AFH/Pm6b6F/8tL71zj6l++NwNG/xmX8w30c4lOvPxQO/cv78B4fWf8aH/FH3Jda99z7Y/+tcey/v94DMMf+W+PYf8v3HeP8KsdffJw/rO83xvkYzh/eeT9/FfelqA+6/yt8+P96Hws+/P+dw/+1+AL70zjsT4svsD+Nw/60/Ib9n8ax/5P31eBHP99459j/yftw+EdONb3dl4PfzOV9PfhmavzFM3P5nqCf7/f4987hf/K9wrg/IP/TeD9/F+/Roj35fJL8T+PwP/meAhz+p3H4n7PnubwH4PzQ6x+FY/5afsH8Nd7nL96T+Bx2eldB9qdx2J987wIO+9M47E++xzmsj/P+V+PIv3gvhfMlcORfjYd+PrW+Hxj+i/Otd47+Nf9G/2p8YC7fM8E+EH80jvhjuL7F/Qp46Pn1nffzL2vp3Rm/x8L5QKtbC72feeeFOc4XmpvcM7fmPn7xnbnMb1gfLf+Bw//Owo+s+YkUOPxP4/A/bX+D9dc41l/b32D9Nd7r30zvTyq/T0rPv4YY+tc49C/f04FD/xqH/rX6Bv6v8e7/Sn3T/V/h3f/Zv3zmf7TD+Qn5X+PI/7ZQfsP+Ahz5X+Op78/W92fIT7A/jcP+tPwWe3x/57A/2T7WR+u/ry/3v77X/D/xiiUt###4680:XlxV32DM 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114ceNqFm1mWpCAQRbeEMyzHcf9LaNOIG+irNLu/+p1LkQIxgTItzXH+a/LUpPPf0SzjR+9pOj56O/b12I+jzUv30WtztB8952X4xQ/nS9r3jx6bJd35kJb+F5+d73nrrv6nlNP5hH2zzh+9pjR89Bs//zt+9JLW4dLT2dmNjzn1v/jivEvl0t1h/bel7Pfff+P8/pzn6fq9zfqH8/tvnN8fl7X/6D6v1/zwfClvl37jg/OpMV7yttz5Oe79Fz9X4rD5t/Xpj9wZP23kYx85p1+8y/myp2k7rv76NO13Xty+3jj2t/j8pHJcz8f8lHTkX3x3PpSSzR6P4c67fEy/eHbeb87T/OBTnvMvvjov/nxdM3d33qZ5+sUn5zq+uczLr/HDGX86/fCyh+Ho7pzxv3HG3znPzdbeOfb3xrG/rcyDjWfd7hz7e+Nhf8n8Ow/F48N2jbfJef/FR+eL860xg4WvyRzmjTc+wHUjvh3jPT6NaV9+8cX50RjHvuAp7/MvPjjf/Pnmsj/G16Vt/8Wz89n5MWyP8W15W3/xNm/X+IfO7Jv4gn1ueW1/8Tav3d2/+vTk+fylX3xzjn2PpbniLfZxpKa94vcLP4Nn99HHZPZ1iRsvuWl+8d35uc7NNZ7N4nu1H4v/b5z43zsnvlf7tPj+xon/q+e39PmLKz7ug/n/aPbywnfn07YdNp6xvfMuj/0vnp3vy9bY85SHffS5LL94cb748x1LGe78DFjlF+/PvHppX5/9zDT3+BD+98LxP+LLmp8c/3vj+N+62fiqf/v4PL6+ceJv6+tLfA3/9fj6xom/+Nfpp4/8hv+/cfwf/yK/V/81/3/j+D/xnfgS+cP7f+P8PvmF+ALn9984v49/nXF2u9sn6//GWX/863yc8c5Z/zfO+mv/4b8vvx/++/L78Lffh9f4b/VVje+WH2r8/85r/Dde47vxGv+/c+Zf8wv14Vv+gb/lH/hb/oHz+6pzXpdvnP7gaH0eOFrHA0frfKR89Het8wlH63rAs/TfCa+//7SHsywpj/gk9gRPwrFHOFrtGY5WfzjLqvGu1Z/gSTi/B1+k/1E4WuPBWWevd63xBB72JfEIHvYp8QyO1ng4nYX2XWs8haM1HsOz9N8J1/XPUa/b+qA1n8A74XU/YByt+QyO1nzI/KA1n8KT8KiHnS+yvqPwUeyTeoDni/pA6gk4WuuRGJ9rrWeif9daD2GfaK2n4J1w6jE4Wus5eNR3Ug+G/1IfSj0Z/iucehSO1noWjtZ6mPVB/6mnnRfhUY87R2s9D0frfiD8y7XuJ6p/PTn7keq/a/dtP1P917Tuh5ifGv+f+yl4jf/P/Vj4r/h3J1zzT43/lh9q/H/uJ+FJeI3/xmv8f+5n4ep/7Ier/eTt23662k9ev+3Hq33m/dt+Pvp3recBEV9c63lCjS/r/u08osavLX07z6jx68mJt5E/XOt5SuQP4cTb8B+Jr0U4Ws+DsE+0nieFfQvnPAqO1vOs6F844w3/Yv8i52mRv4QzXvgu4yvC0XoemM9d9l3reSK8COc8Eo7W88zo37Weh1IfovU8FY7W81g4Ws9zo3/Xeh7M/KD1PBk+Cifew9F6nh324VrPw2N8nF/IeTp8FM7vweN8RM7z4Wh9H0B8Quv7hIiPwnkfAUfr+4zo37W+Dzn3u/mu4UV4EY69wdHRv9tb9O86/MfzafiP6/Af4UU4+RaOhpNv4Wjmh3jD/KBjfyS8FU68gaOjf+Fxvs7+zvN57O9c1/3dk2fh5Pu6f1y75/7R8n3dP67tPT5U/7f4UP3fePV/49X/jVf/N1793/sXHvmoKctlT7ltzT7KdtfwXngv/Ehtd+do+Cwczfyw3swPOuZXeCuc9Q7/lvWdhKNr/Vge+wt0rR+t3q/1o+lan5bH/gId/QvvY39g9ln3H2afdf/h8SX2Hx5fYv9hvO4/jv65//D+haOnZi7yPmy+a3gRXoQTb+Dxfo7+Pd5E/66JT+x3iE/oGt+evBPOfqfGz3F4xs8nR9f6wccT9YPpWj88eREe4436JDfP+GrjrfH1GX/JN3A0fBA+CCffRHx1Hf0LR0d8ifzq8SXyq/FR+Ci85l/jNf8ar/nXOJr4QL1PfEDDqffhaDj1Phwd/Qtvgm/X87S5n41v3V3Dt9yXO0fDz+lY7hwN74SjY3/h8xn7C97fc34hfBTOfMPj+wDnMd/Oa/1l5wPMN+cDaDjzDUfH+ZrPZ5yvuY7+haOJD0ua2nt8QMNH4aPwlKf+ztHRf566R/+usY+6/mYfdf2N1/U3XtffeF1/43X9jXfC0clOk858Pdj7mMtbqoYn4Un4koZ852j4KBzN/rjWv7Y/rvWvnw8LH4TX+tfPx6L+9f6Fa/yp9ZfFh1p/Gc/Cs/Baf6XmrqP/qL+8f9esD/bG+qAjvggfhWNvcHT07/YW/bu+vo+5BtTZ9wJ5He4aPgufhQ+p2+8cDU/C0Twf9sbzoev4njwJx97q/Jmu8/fk6Jo/jtnyPvnDdM0fR7lzdM1Px3Ln6OhfOJr4QL1BfEDX+ubJO+HUG7V+8vfjUT89eZH6hPWmPkHDZ+GzcNYbPsT6Gk/C0cQH4h3xAQ0n3sHRcOIdPEt864Sj6/49P96/1fzD/j0/3r/V/MP5QH6cj9T84/0Lr/nH/cftOfzHdfiP8CQce4ej4aPwMfzD64eob71+iPrW6wfhnfBa/xqv9e/WPOtf41H/Nq2tO++jc7vcNTwJT8I574Wj4aPweB8T9fu+2rio303X+v3Ji/Du853gjaPr+ce+Pfp3Hf4T8c39J+Kb+4/wJLzGP+M1/hkfhYcubse+38vYvWs4+z04Gs5+D46O/oXHftTtY83tcbcPNHwSPglvU9c86mfXUT+nLj3qZ9dxfhDxzc8PIr75+YHwWXiNf56/JL8l4WjsM74HcfuM96/Oed8Cj/evznnfAo/3r8474fE+1vMD8Zb8gIYTb+HoyF8eTyN/uY78JRydS1ru9nYO+mmPzrE3eNijc+wNHvZI/8LRzA/rzfyg4bPwWTjrHfFL1jcJr/XP1jz3n2afdf/p/hH7T/eP2H9uzXP/aXyU/WUjPN4/NZ29x4nv0bt81/BB+CCcehuOjv6Fo5kf1pv5Qcf6+HrH+riGs97wIuvbC+/FPsh32Ee8D3feCe+Ek+/g8T4c+xSOnptmfc5/sz3n3/ggfBBe5994nX/vX/gsnPMmOBpehBfhnDfB0dF/fE/v/XP+hH/5eMK/OF8K/3ryQTjjrf77tK9ZuNof/gZHw/E3ODrqC/enqC9cR//CG+HsNyO+834/4vuTZ+HsN2v+8Pf/kT9sv1nzh+mlmB/F+W8qD/+Dx/lvKg//g8f5r/P4Ppb+haOJD5y3Ex/Q8FZ4K5zzdjg6+hce72N8f8B42R/EfDhnvPCYD+eMFx7zQf/C+5ifZrS82Pv7odb04XGyMX7Gm+5be3jx+yXa/siNnUMs4/atfVdaq+uT3W8amtbvLRWvF+155q7f7u1z7r4+v7afptXfFxzDt/sY3E/ap3341l6/H9X25zxbXN0soOxHsXse/r320MyN+VPJ39qvyfQxzfO39qebX+vHeNKxrrY/GOz5pqWz/eIxfruvos+r7fuzw/v38fq9vN7f0vtU/2t/xnHz/8PGN5Y83td3TcNxH/+f9v58fP//5z7AMNm8e3998nmdin0/4/3R/9/2bu+DtZ83t6fTUPx57fvt3n5P76PN54b6Pn5tr/Ol7f/Yn9wXy59Q9GnaDfb9+rmx8vxu90Om49pPTcnsX9ufo5zsO/zB8tBkf98k80/1V20/DmYvm9+/0vtUjfsT9wu1vY5/OOx7+MHvg+h40dxXOeOUnV8My9f7YNjz5P3pfZU/9i7t9X6afq//5/mlPeOfm8nzqj0vehx8fG5P2h7OeLS93v/R+wjaH/M1DHZfUL//1vsA+vt6X0S/P9f7CNqf3hfR+1d6H0PtBX/Ylrn99nyMNzVlvN8PiHgg90XUPtfNnu94sU+9r8T9We6v6X025XpfTu1J72Plzu5nFs8X9Mf4Nr//uS+z36ex+SQ/TGc/1352G62enZ73jVUP57iveLGN+/3vt623+T8WyzeeXzrPN8QXba+a31v97zVfZdp7fPnz983i+8lu+Zr/ivVH/p98PPXvy3j/+7/P+2yv9UZzWsxlJ0fx+12zvw+lnlnaq/zy+2DnX148NZudkx2Ln1duu52vL/7+ybS2P/wc77Ti9K39OjUWd5O/J5H2rGc7WLw/y0I7j/N6SNdD28/T4ufT7W7+YvM92uub82m34vWk76t3O4/y+IA+02r+1n6b7Bxs9XiQPN+2g9VT8DHb/VRtj05+/13bj113sC5mX53lsW3x83TT3WT5StsvnY/fx7EnW9+52a+8ui7Gz7ho3wn8bW/nacXnWdr/A4e+i7c=###4388:XlxV32DM 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###4644:XlxV32DM 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Np4T+V/sFxO9+NWQT/P8pNbTWPvjG5b1ImG/HLPtjzN9wF5t5Q3sB+S7dR49EC+gl3498fma7ndSd775P8+OMJs=###5076:XlxV32DM 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###4932:XlxV32DM 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###4828:XlxV32DM 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###4360:XlxV32DM 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###4464:XlxV32DM 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###4844:XlxV32DM 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###4676:XlxV32DM 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###4872:XlxV32DM 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###4528:XlxV32DM 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###4752:XlxV32DM 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###4604:XlxV32DM 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###4652:XlxV32DM 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11c0eNqNW0ua8yoO3RIPY8Tf6+gFGAPDO+vR/e7em0SSbU6UdNek6nxRQK8DSFB/0THo+OP+bH//x7/+Cv/6a/6uf8J+/Ovf86/yJ4W/Y4rH3tLp5s9J5/H6fbg9vn7XdvbX7+7S/sbufMuhPOJa+PvencMab3f79vqd3Nks+SmRnviff/562VItW8oQW/Zpyx4P/S7R+R6TZG5fTrKwzu2I50Ks4yku8v0TbNnFls3vB/vszJY86ofyYus5bY1gqx9FbPXTVh+PLGMd4ifF5+q3Zo5VZawwxwozB8QOT6zn7Ye3WR/49gtjmaubMWoyV55z5Xuuqdrb9ig+aK5tFta5N8gXxK9vPGOi4/ck+SnjIXbE+T3TuFtY838ne77LF27xxTC5R2u+kkuZ85JjplzKrgULX1wRv+P3R9ne8lW4iNiLLZqPiC9bkZsQd7/EvTjL1u1Yba2ebdG4evHzmdac8+BXxSivuiaJS5zeeo9TcR2SHIb5UV59OSWGJS+2epNPWWyN09YYD9VN+ZQ0jsRxRKy6JuBbAr+n1e/B5Fu1+daED5l0TWrJwkn8ckT2C+JLN+Cbjh/EtonJwrGwbzq108IaB8U43+WLhW8lmnzbbb7twpdUdC0QWwHr3Ltb47KDLoovWxzYItgp3xL7+pv8fu2Fq7zYupl8+7K2zLH707YucUB82QY5uEMOKlbdG8RNsa49c376Ja/6obzYmky+eXsvHKKb4iJ+lbF2c6y4clf1KtTacw0uxNsDYvVTc2u+tivmrEtbdckmd8vK3e6yZ1/18h477YV91JuJZe5II1tYdcHPNSaXrhrDlBqfV1q15E+Z37u+W/KoP8qLL8jk7ia+oOkLutcxIhfmAK8Yv3XpfjSJ+YKHE11aTxZWW3SdwfH1rDj/rhY+xdZAQzi64vucsvpasfoaP+8QC8Xiq2Jyf7fX/OpYl97Y78mNaOFLN8kL/L6eyaZtzsJz6+A9QuKO+LINOLJBXm6Qlx041FcOHRaf+1j57K61gcfuhXU7qZOFde4g/Ees4ykWXez6JK9rsvJhFz7MI43sycNZuMne7NKaU8GBLoJRXuNYaHCdIuN36sEaD/VDebH1NPka7BzchU+aM4mYn4g1Z5rEAfG1lrk1LhF8oXjoetBGWvjtxlIHbDR+yqv+KC++aCYfN9sXRfi0yViORrVwF12G6IL4Md62rvPgC2rLWth9y5a8rp3Vc96hPOqP8uKLbvLxS9163nPrOvf06zDHqiu3Va8ZE963vOitOQT4kTPdwo8c6rcuh1nflLRy+5A11VHf4fxUf+G5jnTOyxwk37kPA+N9YO1lpH5Y4z3WqW7Jq+8O8Y3Y6k1uO7vPEl0/nzVELj1a+JFv3cKPfO3PvkkAXavoivMrf/RcgRjHE1vN+mkLq606d9D9Ium5mddExPc+v9q6QY4pLuIr38BWx/OpLTMv2i951Q/lxdZo8inbfMqy/usaPcQ2xGobga0EttLKJ7N+KXE97ykfqvBhbznzXsUxRZxo57Wz8JqF+KQ0eE3g+gKx6p6Bjzq/nl3Vr4jvfsPKxww5noEDKn/3O5YcTZavUhdflemrcvPRKx8l38kLHwEHqenPzKohfvRO+i9MYJvOT5Kjpci5BrDONzL7DvHdY1t96cBX+Dnqo1h8uZt8d2ve6dlY86qR7CGSR4h17gr9CsSn+40L+pogL2i1tQDHFKP+OJ5y3Ol6BvLiq2yuF1/q7iA9s7sHzeuHjGXVdy1qf7DH11hbPLyL+7uyosirTArtXekRK/yBY3il3HXqRTyrXO76l50sXOkInPXsgU+c3qfhMfbTwiUm6UwybRBHt3H1W3K1cGvRM2v41I348DGz3tKdB/8EmhP6121G3C1cfRjvkysFZ+HkWD6lECys86k86tMp0hNLtF8V6g7RPk+N9vGOtrv7LIdcIuzS66JE7K20jefZ93RJDqccPcTaX9quc/46Po6HOEh0fOLxEF/Wfxn/7t3Z9tw9YTp+6asY57u87RZvHya39Jzs/dvd+SbXIclTU+jvZKEtWtiP8C57ppuThRv5d7JEcf8HlraGug/xJstfGTbOUa7U3L5buLvTy5HEWTjQwceuYuO6Fb4S0e+nEuSaof0/n0c5PpTMxy3EjZjM1FKwsIZ3A3JrfMoMIvubw45Yye5SbBbW8QrFas2n6bSt5K0meU9Jp/OdTSEeoUVuoOtSJUtjjEIWwJrsszBIv3CE5N8g+RWjvJInXkW7jN+AfI6O9eJsJW8ixtPLUnDv2dIH7Uf57je5SCCy5HF+lMfP0R6J1mmSP2O0quaW4xzUjXQj0RqxbKSHzIo4CZe77MSIdSP9jjk7vmGfgpQh2Vv4ED116f/AEq2i5YxwY2vBLxub4/4Fymu2KS6yNiYKZI2H/kV5iVYzuaVthPaO1uvyUGY/id6jzcqIL0jmVmJh5doeiSwcJfeb5M601su2Lcck3uhaTIeFdznWONkoESsX0Xuq/9miXMpksjDqY2Dhgj2+YhKM9ir3s1s33gJrR4G1B+ejdePtJvfoG/dIckP32U7sRsRbnjn15pq0DQB7OcQ62ccQV8f73N7kkItYsoPGeshVXIRLvrI8YvXO9fzkCyYCb8K+o5j00JpWbh7E3AxyKB0+kCWP/kV5idYwuacr5Zz0Fa79Jt+h5JNknae6aOE6hPLEyYZYyUSVm3cfWJLxVY5ZeLtePUgyg35eFgMSMiFOnjeeQXuwsC4WrvK0iFWfABsvYvqC741MO7Vgz/WKg8l5LcWQLogPJL9jrMesvcirhS/j6fdRntOlOqP6ndXZWv0milw5k77OYLwJlrG8uVBEXPbjXNjf1auL0q8N+YWDj7uFg5MDefPNwuVFiJf88N3Ce2GiHMTVHs6fE2/6Wm1/4FcZ96i2EWvf7K62VxyppGe1jTjogVo2dcTFsR7fsEb+0HcLYO+1aQtG+StT3BLNYC0kdWB1q3l96q2x5P2WuCuJ+KBNXnDppr5ile+JTlhWEyyry4G6kHZg9VXDbo53bZK08lL1V6y34NrL0HLrQx/4Psp/fA76irejyZ0NN1nN3Sq5u3veVItsqohnLr87IZF4E0GsuZLcyg0dPybelLVYRlyG357FMuL8Gtrf5QLi6t07+tuWuoWHbMq9pWHhHnlVc8QHZsSPVTFZ9io3FKP8Y1V+RmszN1n/jRt6I6UvauaelC1chhw4tc8GOFyvGNdcPj4PqMn6fJPcVO8jfpQH5vdv7mgnydZnnhmqpc/jAJrM+e5y5Olt62aghYHc6FLcFRptzB9t1JThzmfjRnGWt2bltPFoct7cbJwryXuL0C2sjZI+UrVwjXqQk30EsHpnqHfAPpd5H5yEljpjxZ14H01QvBU3T4nzB8dD+TJ3IhlvmPpItMYard3cN/RuvL6j5V9tOs694NddbK6T4Sem37jRmlsNmNxg3xiQm+POfZaTp6jXOi77xiVP1J+4CvZF9jW9jQZ78fv/S/6rvvJ91Feikc19xX0Ub1KcccTvJmiTXPrAJJJQnGTJLRwPsRZ7XbiCWLlahSuIlav1tLFytW42DhS5veVtfFbZR7QnD1izq193Vqs/lDuFVu504E5fuUMmd+q3G4UmsR8krevGsT+k43/9R4rcIGxRS+cV3y+T19zS8XE8xJqr2nJGfFn/ZfyLO1AborxitPf+zx2q1nyXt9ddvFi1TyC79iFpxyv2lB8vxap5OxE0cuMduRSPLOezTJ7zrnLeJ9qKhTdpepSUdwtr0+MbPlOWmkLyGHAkrgb1sgLx1WIbNvbSDi7fMbfGSjbxHansfuHhfuMsbxgQa+QVF9njqtz8KU83PR9DfFBez8fzkJsteckG83KhRlx1tQFYnNyjSs8kVI7eB772gOx+YfRGotUbilFeeaY4Se1UW6Glh+FKXk4AugcJ1j0Q7fumz/gmL9lWYkmWPtogDlPCksfxUV6iZV4uhBNPLFr7kMS6F+lTSF2N+JQ+xp7W2mIH6xWj/HX+kltpPa0H4TaO1+R8qZ+j/Cad01zybsnrezz9HOXPzH2PTdYmlEf/oLxyJwh3UF6iYV4e1PRtD9xcXmof9QZ+rn2A4XnlQax9iFA0l1actRZKhczxxdu57d3CV7Tcyj3U95v+939tZVMf5Wakkq35rmxzy771au4fH7mvbxhCjq/ncuVuF89tb20PE5uHWIsdX/dm4TbLnV84SXKlweMhPuUBcW7ypMQFTjZ+t3st3EeSdqyLg7vp/P1SuFGh7WHEOB5iJTs+EVH/nD7qo99u4ce9sYn1Iee0L1j26OKgd0foj0xDHoZy1hS3vQ/wteniskVpfHhrvusfZfVmUm4b9Pv+bpx4yx9KdsWq/6n2iP77Nb7gxrf45SoV+JUAxq9LPPbKmAo3juYx7bTk9eFdzrY8+h/lcT60pxf2b3SXfxd/hxobL35c4KB8SvHkg4UeBFd5tAfltbGl42G8duKm+NbWpvi3+VF+yGKtrywwXvq5Hs1RXgu4LLdrKH/KP63o7RvKJ3n1kiM3zVX+vypqwZQ=###4364:XlxV32DM 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###4660:XlxV32DM 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###4876:XlxV32DM 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k5e6j44/9q5ZyFWIN/HCffD/AcMyKMI=###4896:XlxV32DM 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###4812:XlxV32DM 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###4628:XlxV32DM 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###4844:XlxV32DM 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###4632:XlxV32DM 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129ceNqFW0GS7SgOvBIYMOLPOeYAxuBl72bV0XcfbEm2yZKrf0RHdUYCRiAJSfCcc6642o/xr6S0DOiy3+OJF4rVwpX29Mb//PMX1XX3f9yf8Pf//EHbn+U/f42/9Y/3Kf/nv+N/y5+0/B1S2JI7rn+V4nZ2LulYT9xdTBY+qNcTU/7Abm8nbs3GOnkCYQiEoVmYxRaGRJg4hIlhC1Suj3VK+ey8lm25pKN4WNhRDSfcQmwWvifnYLIOJuumyQZzsv6YV97REY+x0cHVa2VCOcqJo9uahYtn7CgfFt7IlWvyOVcLj0bX4sSWu4VXcp13Ou8vYaIpzOJEmDCECWEjcv7snB1dC7kmd6lNIgoW7sQfT4k/jvieDE2TSfZkFpnMOiazPivbXLl0ug/yWilXVgu7JCvp1mhhXcklr2ThIVE+8V6yiZusdBHhEKuwC+X2Ena1hQ2zsLryxe2XGtTCK725PVs4i3CZSrHwWo/txIlkcoC7CB+PeycnvItwmwiHWIUNs7DZFjaJsH4I68+dZXdF0lnxOg9G9mC7PdhQ+P4eLM+DFXuwZg9WYGa7DC6DbfZg6+zHiPp6rvkY9RrMD527xA5EFj48K1ySjyEuYl1bE9cBWPckzpOt9mSzrYCRXDpnFhor1PjGZbpfeCUy8S4KVfKljz9xY+FIJot4exTusPBLAd/C7rawxRZ2c8e1A7Hy5Dst/hzsCw87WyyswoWcVwu3wMJlmSziVXbSJfG7P3EXtXwL22xht/mEUmFXty9vJx7HsWfhQ7C6EsS9ilqqKwGcZfKH7BRiFYZmYbopTABr38QgI5vMbaBt1vnDXpk+r0ygSu/jbhzC17a1nDcLJwpXoJAzRQvrto4lrxbePa8EyVmP+OUXj0eY5mxhDtzmvc7e5lTgt7eZcR6B19u7IB4SF/Eu1cI6+eJmYRTfrtRNwtjxbPCzMJW27b0zm8vXx1evk5lxoyVPO/ED8+RT5eMNsU6+w8502Jk+74wdzwYNZPIQJj/x7ELL9bGjlsgGFYuFE61XMF5zzhbeRe1iUW8z49V5Fl52CnF0x35qwghcTHwLDzvbYWf7vLN2vByibcCihU6xFyyD2fFqqPZgxZF/D7bMg9nxZkjzoaA6N45PCYFYx6qXZQasOtYP3hbEOy1Jgolk4er8KpFKsLAu+yHCINZtOGZh7XgzrLOwqpPqLRY3nOY5N9kHxJVYh47ExzfiVNh7ZPEeiJt4j9WLAQJ+DG4WtoOwfRbWjjcD2TvraU3vnaTCkT9i3cmU12LhtS5yYmZv4aAGV1g4xCrcOMS8hd1zyPmXsHY8HDS2oSEsPTurahxlJ1VtEbcQHbdfTZwoes7p0mFhCowXER5xF++kO404yeJ8YV2cAIsVYLHCvFhnvL9ssFrHHQFQi6cHiacX2dVw88qhb2LdLS4FC2v7Vkd4dgbx3mvI29+40Uiw/RnH11X8f3njQEs7cXeJ43YfLkwuBp5P2C3cSmDbGbv9/l51yU/zcemS54ypL5sO7hrfj7iSA7NAJnb+MoMUUrNwL35lH8HrobyrnNTkukTmvYm1/XLwfHS+5fz6C2+SiuwHXes9nPzFR8f1nVS5P2KUF3HzLO9Y2GBhlOdoIXBqsvL8U7jO6/Hl1cJZ9svXwPMXjd2o5BOrxipWPp2FjBev+HH8JZ5YA2jF9/iuhDevePfHcqVmjvVFCyuKlR+mW968YuWrC5nHP8IbKz/C4fXNK771Vb63uFDfWHn9nvKKldfvjW3a3lh5/Z7yim97c2xvGvYrVn64+frmFStPbrnmW6jmN0b7Vl7xrc+O9bmTb2+s/Ei945tXrPwhJhSFV4z2ozza0xB2eY+vWPks9qW8YuXVfnV8xej/lEd/WClN8itWfnVpkl+x8o7Y3+j4itH/Ka/41h/5nuqX4kc/+XuPfjJ+9JO/p/ql+NFP/t6jn/P3O63Le3zFyhe3+jevWPlA7H90fMX3+OMcefOKU1kXKQCwv3VreGPlHe37m1esfHU7+w/hFSufaC9vXjHJ+TbSDLLa3/OjeT46/ld/nB/2V/m644hjO/j8wvVSfLh5P3R9v/rj/mB/3V/tn4dHt/QF4wnUt6/+qp9f/W97g/P63+IFtLev/mif2F+//3Xef8VL6G+++qN/wv7q3/A8/7d4A/3tV3/0z9hf/XsolWv7ZJ8XGA/iefPVH88n7K/nG8YjeF5iPInn7Vd/PJ+xv57vnXq/4olD46E5XtiE95njX4w3vvrr97/63/GF5pqlLFa8NPaR7ceX3Yq3vvprfPbVX+O76LT0Td1q30Ngfyj+BNtjfoDtMT7G9sNQOJ5xbNbYPhzMF8cZ24/2ROL/+FzF9qvct+4jIbz+QvtYOmd0jnls34bGcsbZOXOF9kP902/7MYwgSv3r0g9sj/kdtv+xntDepXbp1+E4P0J9W4jvcZxfV6s9jo/tR9pytQ9+SZa+43g/2ifOT85My8pX8Ps/2lNd+CI0mP6qDT2+/InMB9ujPv1oD/PB83JNaefyzF6t83wNqYreeKt9qcwHkQ/boz1ge+8i52Ntz1a8EYmxP9XZaN/rKvFEbVb77rh+W46arPY/5zu3X6TWdqqrHQ+wPymyvth+l3tEL/uN7dHfYPt+cOHSqf5APDTs5dovrjf9bL8/xXi7/Yf9aXup6JyXrn7Fik7Qe8x4hLPaXsKWaXesn/Ga/9jHnc87jl8Qk+P2yXP89AMXfskTJL9H3BzbQ0xyPgJePNtTFXsa5hekNsr6LufrVsth4VKjvMqozsIj7nKsr7VaeOj7Lv78+v44x6O8n0lvnCTexfUb21B/w1vu23s9ES/3LSuvJ+JXfUn8Fceb/bx6dA+OEg8edZPnAl7OR57PWPZg4ZK4vnMVCA28Na3/HNd3EOv89tCThXG+Wc63ULbrPiWE6lhf9m5hlAcx7sf5ROM6P0PLHIeyPjXvNvY/Mx7qFqd4EjDqw5h+kHhS6iF8XuW0ZAvT0a6bxV3rM4CrnGepxmDho/Xr/qmR1HMkHiB5zOZKJy6H87Yg3kdPOc8OC+N+IN7F32dvY1xvxLheiH/YO2Av67mnnC3sgiO5+zDxHY+S1A8/+BGPmuut8bJ3HE9/8SOeXi190fNc+3/x2h/9oeYr3fF6ffEjnymWf9B8K4mL+OI3x/ke+hPlhzP6lW+O81X0V3c+TCn+xo982P+6Ptr/g8f+Ceo/hdZf+U5c78DzQOMt77ie8sWvDuo1bq73IK/jaT1JMc7nrlfRXI9Ree56GK3eWo+73kZzvU3X867n0Vyv0PbxqUd6az/veiT0V32Idz11rmfc+iS8YtTH+NSDJ/7WZ+EVoz1ovVkx2pPWsxWjPer6KUZ71vVTjP5A6/2K0Z/ofcLTf/ZH930F6X0F+DO9DxEs8eD5ri0tP274NB7ct/h3GAHA+G/Tp5ytcMZd7qebRW4I2CMXyFCaVLC+eBKNQL440fBk88OzFnkbHizeyY5E4VOukiH7qcITpeLzxTtadouvjvmUbL6R9Bc+j5iIXwO4he9wOUIpI5JgDZ0xjofYO9bYPS16g7lyRW72uGPxw2+8++CHRTHf5grgWkN7tz9o/j5iHa848YitxbeH2yVD/eLzv/AkFewvPnzw0QmfmNeHaprBLZnbL1RNjOMNy2UP7depguxpDb/xh3hk5En0f0mS4QO/if63ZPfvwtfE9qB89bFZ7ZHX8Texv1qCVBTm72n7u8Ic5gqvP0sWv/C7VHy/+Eou/savwo+IlCP8whWdVSL+rS6LhY+28881RD8RlztDc2RhJxlYlvkgxvkiHovGFfrEN+Y4f/U/VSvQH3x04l+Ad+Ifjsb2iP6n+U1eoHFFDDGON/Q1sL4u23wDdFesTX5xd4V74lW/YrN51d+l8Xz0oajaJ+ojYmM+E/ZyPrTGETqeb3qCLnTdcfzg9acLOZX0jkDGYPxSw/PfoU/Vwj27yJknv1hEfIi+ZXmR+AOLv8ryVA4x7jfiSFvnh7lFIqgZoz9EjPuBGNcL8SFPmhdZv+En2Z+LP9aIWCuU6K+VH+fHZp0n28M36zxRXjH6S43oRoZ8WP5aIzrFVeyZ0nzD7ikts7+bI+IdIuIMvOIm53Fs8wuCLhGzfn9tbr7hlxs49Aca8RaJeDGeUb7fFew5nrn7Q4ap/kgjZsUYb928vuACe9f13zVjBntVPkPEvUDEvUDEnSGiVoz2rBG1kxsQ1FflK0TcFSJuxcqvwCtOot8xsb6rfje54c9iH0eaXxAQvAAgeIFAcMMfgFes8XIG/Xei/xiPPBkjt8d45M6IIIOuYD8VMtIk8ZLyijGeujMq5SEf0O8vYn+YDyjfJGPFfOPWL63IQjz0vCCZX7A0yJgVY76jPAE/5rtO+isY86nX+HyDpP4B/E97MnS+kZf5K093BV9u9IFf4IWQzqc//Dq/IJhfKCne5Ptbmv3XsPbDyjeejF5eQApfk58y/gj5TIcXWB1eOBTgC/CaLz0VAx+sfKnf/pUxxnNPRcRN69+ai3O8IPGfnh/AL8JjPPy8AJtfUKzAr8BrPN7v88mtVjz+nE8an8/5pvr/BC8wNF9W/64Y41nlFav9kcSDt/3eN8ZzvPi80JpfMBL4f3LzC4sOLyg7vKAk4BWP7OE6P4KcT1qxaXL+dGK+t/mFJwmfhVf5lL/le8YvMP5UQQ5wfgU43zq8UO3wQpWAV6y/l+tSz9HzLROfd1jveX6qW5IVL7v7dySMlW/wgldxkxuNI1wvtP8P1o38Ug==###4660:XlxV32DM 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###4532:XlxV32DM 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###4912:XlxV32DM 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M6ccQ7+F5RSe5BPsjfg7iBCpafx/fj8Qug==###4820:XlxV32DM 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###4752:XlxV32DM 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###4628:XlxV32DM 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###4716:XlxV32DM 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###4528:XlxV32DM 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###4508:XlxV32DM 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###4572:XlxV32DM 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###4632:XlxV32DM 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###4564:XlxV32DM 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11bceNp9W1uW7SYOnRI2YIvb4+gBmNdn/vorK3NvjKRToNond2WlslOwLQn0QHCdi5Fqf/9QJjf+NKL8wn/++YuKK+WP++P//t/R6flz/uev8TP/OWJr//nv+M/05zj/9od/dPLlqKxknhgLWcVkAZORIQtuI2uQrJad7KByT7UcHe9kxZkYC1nHZAGTDdnOlay4law6SOaMzZI7yR2vZDm+kxVnYixkByYLmGxMv1ay4jayc5AFS1byLWT3ILv9Qy5OtU7nnvfnkUKfP2WnWOzpnuNSzgXhetyyoE9COKe7sVlTQfhxjO+a5getfIrHoPT+tOMvd7O8wifG8NgYtBtjbOo4Scd2nKQUy1zzXJ+XzOLLXXWuw509wk9V5UU5g1X5IUJG+BblamTlrHyKyYm8Zrwa46LNGAFvs3vfZjq5ymTFebdshGTdYbJuyXbJLhw0Hhw0hl9v4Sw5xkJ2Y7ILk1VLRhsZQTJvyG7qZY2NivfYWBMkOx9MRoZsj431wWQOB42LSliDRnCMhSxDsuPCZGTJaCMr2OmqkNEgo3drXGFuDdfv1clSLhVhGn9mBMjPgXDKNJ0iUnIIF5cmHsQB4ZxS4n0+xfmFhz9M3CrGl0sSqe4mQWHTT3EWLMbC+bJf1o+Y3Lv9Y44YCxnOl/3EZNGQHW4jw/mSzAbz7kzvHqjUZ+xSPNRcaoyG8+UdMFm3ZLSR4Xx5GT/Kzl/v5Jva3CCKR5ZeMnk7MZnDZMmS0Ubmcbj4YrNRlMRVzURlyeQNx+vzwmTNkD1uI4vYKePulOrR9/xn7Ld0Hry6dW5qi50/HduUnczig/p00vOgB+HsyqxororxGOb/DSfHTjhwWyOSyq/Yf/A+/uNHWwppFzbWhWsoJzWK1kTvkiAcpCbKYrxf2N83+yUb7xd2HPFCZ+UtviUiPaKclU9xJa6h7Hg1RtiNgfPpQTioaHJWvCfnhvPp4TBZtWRbcm44nxJhBzlGObg6SB218kKG8+n94BRYZM0UP46xkOF8en9Jzs2S0UaGz2fXicnCUGwlGxW8W8hwvvFf1LwM2ek2sob9JOx+opOjOGFJHCT0bGHx6Y++BhGLK42q9Q2XPZ0Il5FhOXhh3KnNcr3EPWhEEzTGv28uXvfxAzeuLLbdiPPlSbbu5Mk/RSzj3U86zpdHwWTVkm2SdZwv6cF+co5UsvpJF24hw/mSvmTyYMicYCHD+fL+srUT1WOP8nVJvh3ny+tLEZstGW1k+HyTvpANSepeEdd1AfD5Jn1T05BFt5HBeFy6aT0EOipH/jirOsWjrF7Kzw7j8RiIyYohI7eRJSyZ2WdNJo9iYe4rxYX8us8eTFYw2TF22kpW3UaWMdllyby2tDyTMT4cYyErmIwwWbRktJFVTHZistOFupJ1CsuZsDdMFjBZMGROsJDBeFZsW1AN/mMzXZBFzbGJsWQOk0VLRhsZjGdj++AQlCjI2Ynx7RgL2YnJIibLlow2MhjPyt13Mu3fjK/caz/nkQJNyAKW7MBkzZLRRgbjWbmMZBedmaPEHbiDxHgcFcNCdmE1D0yWLBltZDie3dmWhHx8vt04m81WC+NAjIWMMFnFZMmQRbeR4Xh2Gcmauw/pwjlOcIwDMRYyHM+uismSIYtuI8PxLBrJCp2PNEslwjIeq1sXMhzPYsVkxZCR28hwPLtvHILUAxQbD8Dx7E6YrFmy3QNwPLtu604cCx+iQ06G8m/GTHbgeHYlTFYsGW1kOJ7F2yZhTSh8bFPs5UwrZDiexYTJbktGG9mXeOa/SXa6XbJz2bQHjmd3/CaZIaON7Es8M5KNzXnK6knBwvgt3RcyHM+uiMkeQ3a5jQzHs9ixo1dHz+roY98tCeXA8ew6MFk3ZNltZG88K5YshE8VlPzf/vTx7Xb1xienwn1tKhO3WE+E3xg/jx8HxvdI4NyRmHS/cKPEPVJf9GKDT2Ke56s8pyuV9eOesE/atK9y0sunnNhmv3CcDbkTM85A23zzvSTXEYmynOwe7qV1vePki5WDclj5j7t6XkTmv4ddkPzesaL6/U97SuSr8vvqSv+3+YVK/jf99Pcjdc0rQl/Lg/Tps7577VcJjo/cox4n8guNt/vDjre/t/La31t9K/Vp71xrRPay8+14i+16PVTnraSP5UH7ycprx4s/wZQeusagOJxzcaYqwnoxVnJ8s2xxc3zL2G7enL8xy/YN94Pvhz0Vj7CnTCsWZVBJkYtW+37o4t/b8V45KLsp06hLTj6yuojw27ifCxxdQljvto4RoH8K/KNAWQqWZazINECsPchmigiT4283+bbFKsu9y1KhLM8ui84d3j/n5oO//bx3De03HvabLauSW0RY+SK1uXtEFlQP5drx/eH0l0Wv4ja93nLo+rV5f/qd3r9syT+jjOKr9dSmc0f2qdcpMsJ3ZOw12BscScbX50TYu3Dw97jXb/E4sk05/IHxI227Fp8H4ur49DXCPsKUXJZDZ12LtkqN2+OR2/KjPL0Qtvay81ulwMmAf2+xvga4ZLzFyqfYyqvJRLHOH/Jt8xX7xIee7lparwkUW33seNW/Spv02/es/XQ878cTVtShfSnPmzHGI1jIUEU9UphwXYPr+umejkNLeJ1s6MlHTBr5A+BxfvWzIepHNgC4u8A9z9QI4Uq+zYuHg53c4pbCyTd5HCQsHo4QViy6ooK/fG5UjK5edB2bbeKQakY40zHvNy/fLoQj+TKfAhw9Iqyy344D2DccXDsRVl0Vi64eBuNfN6I8d+yJjYt2rgC5CHMVy0UbV4T77dkLAU1Y74OXabPEyXJUTRnhcY6d9yJ3ZptbTBSmzZ/K+8fixaYe4cXGftHlgrpUrEsTXfqbvqaN2VcsVtlrrgXhKLL3VCvCKnuiXRfFqoti0eWGa3ziNR7ahJWr7lwEuQLmOg1X222coI3v3cY/xVGrq02HB50Iq02Dbw/CQWzqY8sIX++DmNnT7A7h7OKxYtHlgbokrIsXXbRQHLvjRFhlj74HhHV/uKN7hFX26nZdFKsuikUXWATnZt+C8Nx56lq4Rnm1xmVcxDrMFQ3X4TauCm1s3iOMvd/X+HLoPeXB8cTiJvem7RNfdtwzx/TxfxrCF/kp64j4J8TJR74b5zX/hoevdIT1jY1isUWDtqA936ktND6NDB3kPWtGWHO5xlaL39uMNbZafOezr7axWHW7jK6X0fXade1wP3556DSfcSxceePyDnIVzNUtF21cuL7yuObIb3fmtYkcgsr7IgFgtXnzpSPcPNdTz/saDGCtp2LqhHAitvk4DmaEj88br54WXWF95cwbh5+beNa1yP56qFSEf/ZXOREe0Tnxu03xPYOb6HbUlhFOXfdfh/h2rHuMGKst2m4LWH9lU38dn7dx/Vm5Rrx8Fi5Yf2XCXLfloo0L1V+2sfxJX+6SJpWG8Wu59PGwF9yi7u3zfHuky0VZmOt1HnwbclHwCOt4xfKxtz6J5mOfv5HwzBO4+/lYczz5SZ5PcBQI4ZHYuZd8xxPh5vhE9w0PC3m+Dg7T8Z56chedQlyVG15wrMp95DPjv82/3G4sy6fYyqPXde29sAZ8H2O7zdgEjH20z0Xjx9wPec/P+f2kf8Y6iXnPlb6qunb8Lxz5Di9jrAfqaPaK8h9ve+xVR/gsnj76Nhgjxv6t197ud2T5rT4/LxMYW3m0IaDY8mn3OVNYaimPatzq8RVxNyuX95V7wDuzT2tSnq76YS622jWlGI7Nt879OhDOKcpdAG+i35g3XaKYISbGZ4wF4c97b4ozUjnuEYxKNfIJx3GHWfEv+b+MH84Kx4upMmrrtU9bL89NPg8qvGhBfc7xotYYxFydX9zmmFg9bqnflT9vf6/idmL1LdaWvI8ivvl+vdvDXVk2v8W/vvfl+5eYx2I1n2Irz+dK4bO8u776+8Pp8u72Un2u3QkKXg6tuupcDv9zu67mSBIyk+OQafFzHPKXQvhzFpNjXKosp5rD7CbFTdQ9jTmymMPy6QuwS77X6Uz8V5D496qPmuMkXq4a992t39eYdtzsnXZ8vE9poAc43trPjrd8Vl873+ojywnPYeahhJq2m52XBQsVejv7uVaQqlJX4RInGjJJq5g3vcVqlTNHj3AULVMN2yorf4r94ns85rO4ObGaOIXlUyt6Fwoa/3Nvx7tKTNGRKcp+mNCpJKLSwao7ihFi6YqPBe3rp3W+hs9TVLO4yAa5qm6QHSufk3hgv6ddeMWsanDoxXQ7677uP/fJnGFDajcLz95v8SUZWb3T4k9wEm8tsi638XanxpHgWvqFx3cOzupddryV344XY8BTZLJVO4t2i2iKo9hdqOAhLWOqZKloo/L4AHDuBwCd3N6XiVu65srF4p90v1Y2IYCa9NPP/iRr9cNxxJboJ34UeT1/agMmr7Je8eADgcVJrsw0Llhc5ECQOx8ILNYKcTiL+zf8uAjls/pY/JMddmNexpiK7fe0YlVs7fWz8n51TnSKPM+e9rte/biW5/pYQMtxi5NUCvpxi9U5jTCwDR+/pZrdLmv5/H+BRvJk###4368:XlxV32DM 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###4684:XlxV32DM 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xkrlMkYLX5WKrb0w6HrO9BfdHIsczQjvogtNDOHg6/5QdRnzc7G3OW4a/x/9XgTq###5084:XlxV32DM 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###4876:XlxV32DM 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###4880:XlxV32DM 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###4544:XlxV32DM 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###4564:XlxV32DM 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###4736:XlxV32DM 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###4664:XlxV32DM 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###4384:XlxV32DM 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10f0eNqNW0na7agN3RKtDS/ryAJsmmFmGeXL3sO1JBvk46q8ya1TmCOJTg38xYx///3vv1JJR/lj/vj//Nv2dPxx//jX+D3/+N7Of/xz/Gf+Y91/vPWHS6X01vuWUv11FhwYM1nFZBmTFZPaTBZXsgbIQtp2JnODzPljN9318S8n53+dWyJssq0Iy/fRODcJ61iYGgbp3Lmz4LqQnQaTZUwWkgszWVvJLCRrahhqqv7X2Zp+knk1/H6T7QFh+b6knn+/LMxhYWoYpPOW+jGTBcZM5jFZxmSFNRccV7KAyLJeDTGV7dfpNM3QxBB2th4Iy/dbqn0SFrEwNQzS+beMZ7K2km2YLGOyzTQ7k/WVbB9kQZHZ4IVsG2SbP7zpljqbaK5/NJblNCfCKdPvWHf5b3CccUlj1YJ2LV9w/eg//n+ZMRub4Mi9l36u69LPbV36K5bv1dLPWNhr6VPnZ+kTVkv/wGQZkz1Ln7Ba+iciO95L/zjXpU/4Wforlu/V0i9Y2GvpU+dn6RNWS79isozJnqVPWC196A+8HoZi4rVvbBqL0Y6ll+J+cWWbEZbvq7Hth1lYx8LUMEjn3dg+k0XGRFYMJsuYrLDmgreVDPoD316rIRt2LvXXuRrCZ3YbwvL92MNlEuawsNdqoM4HdxacVjKPyTIm66y54LySBXwQyjCEQRbGDuODJ5p2raWz9mtMjzTiAoBN7o0mtBVaFWt/wS4R1t9HUv3GrGzEyqb11A6JQpRk7BUQhGyvkMYmaxFufICNMzUg7HNPNA19NS4pZRm/5DOOyf5ffGws9HdB79NsjvrrXk2Mv2k1I+C7IkobOsLyfUoxTMtgx8LUApXOLpEwwYYxkyVMljHZ8G3bTGZXMuhPQvsIWFIafJcnZLefu0VYvg+mT56yHFjYR8DSuLPgspKdmOwjYPFj1c1kdSUreOlHFbBw0NdNvWJgF2tiHBEeruHCxbYP3Mgfnd0gnDL9Ft7HWr6/w2PC+ns5BwSzsRUbu7Gx+zB2fw6lnMJB+4zIQw4eYWvbwV4mIOw4mkueDjGNb+VNyzOu6lDTWPQTvBvCf8fHgwH9dfw+B8qV9Tz7/iwIP+dAsdMy61jY5zlAwp5zoEwpVzWY7PMcKH4msysZ8tdu18PAy3SMad5/h8iWKE73NluE+3125+05dKrDwtQwSGebSJjgvpJ5TJYx2W5ymskMkzMZyt/8K39zI2QgF0P7b6w3SrhtKQjL9573KQuLWNirqEGdK3cWfK5kGybLmMxzoi24rGTIXznX4joMki/ZZLbfrB98IpwRY/k+cL7FwhLUXLsgaw7zW7eNt29KhKNtO8LyfV7cfs1YmBpz6ez54BRsl4O0HpgsY7JsWpvJ3EqG/Jmze1Bp5J2z2jifcs5gfIeCjFlYwcJkguMQFh9hlYUdmeJQx6GdxslQYnwn7Aqf3m50QJBL0HjsxOv09JXkaSyh3oi4/WQMyt+G87HryEnnEQBlOpOI/KgYy/dhxAzTNCF/YatVcy6de6LOj+YLWYea26aKhyNmoeEIl5M5Rqh+jVocexhg+X54xuuoJ2EN+Ytzi6rcx30jyxLsEmHmsiiEGBtvXT/Dx1zzP2L9S5FxHnIBJmaEo60USvD3un+1ZOiYwoq+z+MAn7H+XvgEszEOzkJSO086j+i8z+S7ErYr5QWzMA9nYVdHBvetiutYFQ9Q8ZhV7MKjElhxGbU9xYawfC+YhUWouFfRBveVQRI8FlSfuDbsX2TE/SDzzyY6+HjYrOXiuU0IJz4uHB8XGgtfWY6PtuOz0GFndyvDIYSPRK6xv2PvRVjCwvy6caSz5LhHpVj6FE/7gTdDCYTGj1f4a3xwQUDjehs/O9OW4frLfR25lnyiXbxfpZHDet6FGMv3glnYgdeMx/5xlzCBLZEwQOMni1gsO+EV0X6sq92MeOI6x8zJWQHhI51T1N9QcjnIlOY3GXcWXBSW9oPxns4wCatYmFm3lpCZdGt+XNFVPf0Hvr53BreLMtWcU5jRGlYmYMubsvRUuCnLt9XyjreWwQukJJPmgKkbuSRY8R1wmbno3w0WZteCwb1vWFjkiHgfsSDCPVGuelqX/gpbSzm3xqK8NeH8K1xTyAg/AR9hNtbC3dDVbkjjtKJDhVNixjWdbSJzcE10tRtusnT2mawzmW6XROZYEu7usTC1G4TMP8IuMluJDGCut96WLu2ijOGcm5UJWJmALbfK8qYst8ryvFoOLweTnrN6p3CuLQvgV8Z+yDag+SD7OHvd8Ljr1iEy3S5XyccwYBK2Y2FqzoTMP8JoDiKRAczJ523p0n5fmic64FiZhJX5yMqssrwpy62yPK+W48s97XXGKqXCtqmNV23igsDkwvqBNM/a69xkI42aySqT6fbKOC23Xv3EwtScCZl9hF3HV6+3JRonrlbAdlGm8WUiK1OwMgFb3pWlRWFpF2H7ajm8PIx6zpzZ5cSglymMTSrzPkP+cpCpObvJuLNgp7C0F8Y1lfkg7liYmjMh2x5yeg9SiQxgDl1vS5d2Ucab+uyz4WywMgFbHpSlVuGgLC+z5dnAy8nYP/ZZHYfpFdEzzqaHicxBzfvHPmvc+d60Cku7rLZtvqfIxmNhH/usP+TXvqmxbx+YNzlur/cJQ9c/rEzAynzss6osPRSuyvK4Wg79Wdg//JnEIE9Ac84LAPqzsH/5M/a0T+3tXJyltN/+bPbE2exY2Jc/e4QtMQXASwyi20WZJQbJJmFlvvyZsrwpy62yPK+WZ1ia13N2phLpsnDs79Fd8Ohl7vwvG+TPBpmas5ssHXYmswpL+325mEbS/Qg7sTA1Z0IWH3K6bKxEBnCk5PS2dGkXZZw54qRMwcoEbLlXlhqFvbL8XC2vcM7ecaM8hfI7PdQgnIzfJrIGNX/HjYajJL/NZIfC0r4b8h3R+DwJ61jYa58RWXvIqSgUffrAhVKt29KlXZQ50khkb2WswcoEbHlRlmaFi7I8LJZb/Njm7c/o3VZO7qA3RvyOy7iZDPoz//Zn1PngzoJ3haVdHo25+X1Mth4Le/kz6nw+5Ff8l6M7PzC/nbstXdpFmZ0f77AyASsTsOVZWbopnJXldrUc+7P+qjBRMWIziZ5EMra/6677oLXYn/VXhYnJuLNgr7C0H4xbSmUShv1Zf1WYDF/9CrmlN3g1FYzp+3xburaLMoGfY7My2J/1gC2PylKncFSW19VynJ+99xndCnsurgpuXKxhMpyfvfcZkyWq6Ao2Cku7vEs+53pmtjg/e+8zeSF9k9MtcW3lA/u5zKzbn+fedPPJyuD87L3PqLNTlkrNS7eLsGO1HD/u1DHIOKZ4E2+Rjy3atGkLExnMzw4dg9xk3FmwV1jag3GNFsi2TcI6FqbmTMj2h7zRviEygPl4ui1d2kWZYLbnpjI7g5UJ2PKoLHUKR2V5XSx30J8dX/6s/sLRa3gzvwwofSKD/uz48meVO9/+S2Fpfx5BTw8nsvNY2Ic/aw/5NQylVvuBK1d8YHu9/SNtAVYmYGU+/FlRlmaFi7I8rJbDxyxNz9lucqd7BDr0Ba/5mUP+bJB5/Uc1THZnIYQlP9Pt8vBizc/cjoWpORMyfwvjJyF3vqUxfR9vS9d2UWbNz1zCygRsuVWWN2W5VZav+ZnDj2Hedf22XW/bfu89rv1FePTapwWA/JnP77o+k6UjzWRWYWkfp/tOt2DHMQk7sbBXXZ/I4kN+kY186/jA1/f7Y+nSLsqM/GxyMa5gZQK23CtLjcJeWX6ulld8DepwAn+m9TFkM+vFj+CnYD1d/GT3cX9n8f1dMOtloVVY2uX+rsyXhdl1fD1i8fXIrm6ZgsLSLtcj3UzvHbPH93dbfT2dkLd2XEek31CrQ1i+b+ySWJjFwvr6VwDSOTPpnir99cpeN4THUUJKsbAvHPi1sMZ3tGfmg9w7fAJZfALt6iAPCku7nEBqGjy+XrF4NW/qlsorLO333yjOdznZB3wvYHG9MqrrFaewtNe7ftnmOUf+sNn1ZG2/t/nTYyvBy2Or7Ddc/7G4/pNVGW1TWNql/mOXYpPfcSHe4kL8oe4zdoWlXQrxbqn6e/QaplY1SPwcpJqRi18+jvCRCDNVxsXoj8l1aa18d1Xjl3aZ3GOpfHtci3wvW1r8Nq2lpKaKZtIu1Z28lJL8iUu29uvhy1r5Dgo/G7ajc/EjN7M4N0sqxY0KS7vkZmZJBH3FSYXFScWpcrOksLRLUuGXDMbj3O1tmdSp1tC7qyRD2utd55pDb9+xl/4YRsud5YSWd+IaP8n+fGIHg+MPi+OPrMK4TWFpl/jDLsFOsLhI9jGMTdUaT4Wl/fmD1bsi9z+0+6sy###4660:XlxV32DM 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###4364:XlxV32DM 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###4476:XlxV32DM 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###4536:XlxV32DM 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###4092:XlxV32DM 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###4588:XlxV32DM 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###4332:XlxV32DM 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###4200:XlxV32DM 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###4156:XlxV32DM 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###3908:XlxV32DM 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###4692:XlxV32DM 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###3852:XlxV32DM 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###3776:XlxV32DM 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ea8eNp1mzsWLKGtRadU/OF6NHxDZ4683twf7qPrwGsTdbDXoauEhACp/uVO7X/8P/55f8efWOM//u+fzruZ/3x/3L//9T80/ah3C2kT9Q5pFy2NaPNGceTmRBdrq1HWlh8NoRPtzehGqpFDY+0yytotelDbTHsOUmljGjiyrBHzh1SWjAOtMYxOj1QjJ4d2Htkovu+QnVMhz/FnGO1I5Rtp0fuG7/vRHApRF4xOpHrf3CrSanQh1RtlnMHwyRolMZ1GN1JZowzUOtOOg1Ta6sjOwTujOLJX/NbikU6jPPIRXYFo8EZxjoKeqoVINHqjOEfRtK0h1Sy0g88c/lJ+Klmjp4R0GMX/DfLYzjMYRYejlTAkZxT/N8nbR0af7DZywZFtRRoTvW4oUsbC2beVYXr0uqm8MHkGp0ae7UNajbJWdp4H38hWlXnQVrYircTaY5S1WmPXQGuszyj61dTI+0M7L1ljO4yUJTvvjGvdakZxFpYsuSdrFb974Sws2fl4XCe3POcE1B5Z41TUHvnGaTgLR1F2NvrzViwcnv39s1X4ImuzaMIZ3EW04xydJjpwjs7PzsF9GN1nGcU5Ols005oTv2gUM/unZ3aTtd3oRKo38p5W0eiWUdQq4wRfMe/7zyjmfXdEN+5znDOK+xynkUNEa7hklLWa/dBR6007cI/kpb32RtqNoq38EM20qsQQjKIllSVDnKwtRlmr/00ed+ZxGcVZiJrfVPF9lXEuRUtGzW/aqI2m3ayVNXJEn1TuvhR3qlEzmDtaI/2lqE0auXwRaTeKT5Vk55I5dzejnLu1bpTJ2mkUc4r9b/W4IuVjFHcyWWtOrZhhizeKO5miCK0bnypL2yLTahTzUZY/t477upKNYk4pmt/+oTVKM8oj66k6no9CdUbRVlX+3Cdri1Gc/ao3Gnj+De0vRa1OqWFU1najOAtNnjM22qr+pWgrncrv9o6tcYyi5zTZanbMkl10fZidezSK/ty1bqxEK39Jps0BqSy5Bmv1vmuyVrbaDrUWZRsjtFgc7fohzUYjUnn73qjNn1HUZtnqRNYWowmpIuV0h081jGakWs3OoRW4KI7ih7NfFIPxw7NzqdXoRtpFB2uXUdTKY++mBLW6V7kUtfLY6Aprq1HWDtGF2paM8jP/ZjD6wNpuFD1WK0P0jdbnMj6jqNVpMXo8WZdhT4V3I2XoqUKiSKk5i46EtBltSGXn6Fi7jXakRxRvP2qJRjNSWSPiyfqeE02MR+uLZa3kH2pNUwoPtd4qVVZvPVpqrNYpKabdGHfDi7HiKeP6EbQHjxlXiKqbqksHUv1xwQxQ3TaKOwsvc5eMM6k7sEvxqbzMVXCFCLrhjgXzQ02/3VCs/kOajKJvKmvFihm+al95KWtlybomUtmqYvaoyh6Rb9eS7nUuJe9IQ7PfWkFtMTqRyjfawZF163PpQirf4Ju5NLfRjlTP3PFex90F2nBGbJlpOFabewz3UGt1GuWhXoZZbdlpzMVYUzWWY6zZmB7j3OmgdjEPrpNanPWhtsHrQ635mvuhPoZZbVG1cA96cTZcGStyVv8Q22KwOg9uK8n+Hupq+KGWF+/M6vAZZrXuCuIeg3ExfBjL5sdRbLovRsODsQY/5aEehh9qBdFZrE7BMKs1oenjdPdpi35xZryEORu6dIQ5GzqdZ9O3WZ3t0c5D/fO1dCeF8RZOj6XHCXeOEh0CLuYo0ak2+S+hWXThdXFjbOr8UE/DD7WM6ierQzTMajny3d18jIfhyFhGDWWiWT5NaKgcgp/MEtZDrQkN+6GWWWJgtS43U4ysdjJLxOx5cTXM4a/dU4onoFlUfryYQ9BeLKWHehlmte5lUxqs1sXsxQ+1XixjdeRiGTVziv10n5xypuy+9zC6kcpX8kTt8UZRqzpFKp613ShrZc6Cu7fzOaMNqbykbEzrn3b3F3PoaXefanyou+GHWs9dO6vNYLWz2ixWz2QsF2ycWr8jN2iJ0vpR9ebSiVSv1QZrt1HUHs1Gd6g92Shr9Uq9BKTL6CMkFVR9Uj7fU+boWF7fKjimgcXZrYLjjVbULr3SqKxVQI3GWplybA5Gb5SDUe4xI+dxnTwu7ozlALM/1MPwQ63nXh+rzWDrY7VZbGUOi9UNc1gsucHCBpyjhqO0sERwurxgY4PV0YVN2njBfHRhk3ZhrRblXVkrc+6FQaFC+qUYFFNecLA14KhoeSmObHnoYGvAsfx6sHnnWHo9h7XNKGt/ds4flhaPCp75w+R5dIGQv867254MH8a/ecjue6in4Yf6CGdWj2iY1bq0y9zcd/EwzFGhhonsPeXto2vZSzPSJVpRq/a+S1Grc2/2m7XNKGtlzhA4FjXPIXIsap4DNh5ttdpcSiPvYSPj5ce2aQqHtZqlmFg7jbJW/hFHxCwSjFakv1UvJ8f5uv7FvE1X82dO5aFehlmtq4+cFqt1Q37xQ62Yyp6jwpwge46KJptlLI6faWNjcfwoDd3dKGttZCyOHzUC5RJRqyvjS1mraCsdY0JZ+1KMCbXc5HIwa1dpKxZutkVqxdLMtmmqmbWyZB2slYNUbEzdFqnNcSxGoxgTXZZshdN1NnHhw2s29Xqop+GHWh7QA6t15L+Y1Try5944KlSBu5ijoth/b8zaWZ7bz4dUXjAiatVQkEdCrb3U6KyV547BWnnBxKLA0eXspRgTal3PE8vC22ZiYlvWtjeaeO2/Vby9lLVa+ZZn7TaKWnujVTgWZcmFWXPrsjkvLCoetfxcupHKGhuLikf3d5eiVtd3eTfWDqOslTU2tnMeXc5digflLGscbPbcamK6NCHVG53B2mKUtT+PLZ9j7TGKWr1RucsE0iyKOXPrsrF8E3ew3p4KmwGP/8VRcdgMeNSGdilq1RZdXGXtMMraLYqtKCfa/3K2VMNX4VL2ViN/8RGjzJm2sVaW9J21UxQ/xdiqH5SAjUhb5YMSsBS1del6KUa3igclYCVqqeX20o70588lOtZWo6zV/3Khe+uy6lJ8I11WlYg1qP3Z/2Ku3ProoSSsQG19IlBSwJF1w1xSZa3+NzXW2v9i9WmrLlYSNiBvlcUKNzBuFVEuxehWUaxkrjx5HVwurozlldzC6Lw2RIV7GC/Wc5f8UFfDD7Usxh+gXKwlj2vkzutDglK58uS1AbiYB9cOoFSuPHklzItZrT1AqeuhboYfatm8ceXJ65BycWcsm7dHH4YS48U8uDJjaVx58pZI+DuXi7X+9fRQd8MPtWzeufLkVbcqHZPnxbL54MqTD9MwDx7kTIMrT94CkL+G+c83cMLzoR6GH2rZfHLlyasufTFHido9ynxUno4NXnlwW2cnV578Z4Pvh1oBvOJDvQyzWuWdsrjy5HWxdjFHiT6LK4srT24dw1zW0p1x2Vx5cqpnXPxQK4D3eKi3YVbr6r+cR3OH6hkXc3uGZdWTuQ1LX1iUw70fXneK5TwayGwjcR4NZP5n83sof6in8KOBTOXb+tVHhAbDjwjNwlyBcvMzzFVt3TlVFx/qYvih7sL9oT6GWa0bluofzR265r+Y2zP0KVb1iYu/+ka3+kfvh5pJqx+s7vbf86HWfwf3UOu9HxV1pwxcAxeinL6au5ijZNh/42VbMlcLWClI2tPWiJ+RJfPDiJWCpB1gjXiySN4bPUjlZXHXP+6/1MbD2lXSJ0A14Qqa1GRyKT6pWq5rwvUzqUX1UnzSbCPj6pmULC/FkfUpbM2Y5ZM6fi7NSPVU+X8+h/t/b+9L+w==###3804:XlxV32DM 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###3488:XlxV32DM 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###8288:XlxV32DM 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###9492:XlxV32DM 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###9668:XlxV32DM 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###9712:XlxV32DM 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###2196:XlxV32DM ed6 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
/image_component_labeling_and_feature_extraction/trunk/compuSequencer.vhd
0,0 → 1,248
----------------------------------------------------------------------------------
-- Company:
-- Engineer:
--
-- Create Date: 20:03:49 06/11/2009
-- Design Name:
-- Module Name: compuSequencer - Behavioral
-- Project Name:
-- Target Devices:
-- Tool versions:
-- Description:
--
-- Dependencies:
--
-- Revision:
-- Revision 0.01 - File Created
-- Additional Comments:
--
----------------------------------------------------------------------------------
library IEEE;
use IEEE.STD_LOGIC_1164.ALL;
use IEEE.STD_LOGIC_ARITH.ALL;
use IEEE.STD_LOGIC_UNSIGNED.ALL;
 
---- Uncomment the following library declaration if instantiating
---- any Xilinx primitives in this code.
--library UNISIM;
--use UNISIM.VComponents.all;
 
entity compuSequencer is
Port ( clk : in STD_LOGIC;
reset : in STD_LOGIC;
tableReady : in STD_LOGIC;
computeDone : in STD_LOGIC;
featureDataStrobe : out STD_LOGIC;
acknowledge : in STD_LOGIC;
indexMax : in STD_LOGIC_VECTOR (9 downto 0);
eqData : in STD_LOGIC_VECTOR (9 downto 0);
eqAddress : out STD_LOGIC_VECTOR (9 downto 0);
compuCode : out STD_LOGIC_VECTOR (9 downto 0);
cntObjects : out STD_LOGIC_VECTOR (9 downto 0);
mergeEnable : out STD_LOGIC;
compute : buffer STD_LOGIC;
tablePreset : out STD_LOGIC);
end compuSequencer;
 
architecture Behavioral of compuSequencer is
 
signal mergeAddressDelayed, calcAddressDelayed : std_logic_vector(9 downto 0);
signal mergeAddress, calcAddress, calcCode, mergeCode : std_logic_vector(9 downto 0);
signal runCalc, computeDoneDelay : std_logic;
type calc_state_type is (idle, initSearch, objectSearch, waitOnCompute1, waitOnCompute2, waitOnCompute3, waitOnComm1, waitOnComm2, waitOnComm3); --state declaration
signal calc_state : calc_state_type := idle;
begin
 
eqAddress <= calcAddress when runCalc = '1' else mergeAddress;
compuCode <= calcCode when runCalc = '1' else mergeCode;
 
resolve: process(clk,reset)
variable cnt : std_logic_vector(9 downto 0) := (others=>'0');
variable destination : std_logic_vector(9 downto 0) := (others=>'0');
variable cindex : std_logic_vector(10 downto 0) := (others=>'1');
variable found : boolean := false;
begin
if reset = '1' then
cindex := conv_std_logic_vector(1,11);
mergeAddress <= cindex(9 downto 0);
cnt := (others=>'0');
mergeCode <= (others=>'0');
mergeEnable <= '0';
found := false;
runCalc <= '0';
elsif clk'event and clk = '1' then
mergeCode <= (others=>'0');
mergeEnable <= '0';
if tableReady = '0' then
cindex := conv_std_logic_vector(1,11);
mergeAddress <= cindex(9 downto 0);
cnt := (others=>'0');
found := false;
runCalc <= '0';
else
if cindex < indexMax+1 then
if mergeAddressDelayed /= eqData and cindex > 1 and not found then
cnt := cnt + 1;
--mergeDest <= eqData;
mergeCode <= mergeAddressDelayed;
destination := eqData;
--mergeEnable <= '1';
found := true;
elsif found then
found := false;
cindex := cindex + 1;
mergeCode <= destination;
mergeEnable <= '1';
else
cindex := cindex + 1;
end if;
elsif cindex = indexMax+1 then
runCalc <= '1';
cntObjects <= indexMax - cnt - 1;
cindex := cindex + 1;
end if;
mergeAddressDelayed <= mergeAddress;
mergeAddress <= cindex(9 downto 0);
end if;
end if;
end process resolve;
 
calc: process(clk,reset)
variable cindex : std_logic_vector(10 downto 0) := (others=>'1');
begin
if reset = '1' then
cindex := conv_std_logic_vector(1,11);
calcAddress <= cindex(9 downto 0);
tablePreset <= '0';
compute <= '0';
calcCode <= (others=>'0');
elsif clk'event and clk = '1' then
 
case calc_state is
when idle =>
tablePreset <= '0';
compute <= '0';
featureDataStrobe <= '0';
calcCode <= (others=>'0');
when initSearch =>
cindex := conv_std_logic_vector(1,11);
calcAddress <= cindex(9 downto 0);
tablePreset <= '0';
compute <= '0';
featureDataStrobe <= '0';
calcCode <= (others=>'0');
if computeDone = '1' then
calc_state <= objectSearch;
end if;
when objectSearch =>
compute <= '0';
if cindex < indexMax then
if calcAddressDelayed = eqData and cindex >= 1 then
calcCode <= calcAddressDelayed;
compute <= '1';
calc_state <= waitOnCompute1;
end if;
cindex := cindex + 1;
else
tablePreset <= '1';
calc_state <= idle;
end if;
when waitOnCompute1 =>
compute <= '0';
calc_state <= waitOnCompute2;
if calcAddressDelayed = eqData and eqData /=calcCode then--for two objects on consecutive codes
cindex:= cindex-1;
end if;
when waitOnCompute2 =>
compute <= '0';
calc_state <= waitOnCompute3;
when waitOnCompute3 =>
compute <= '0';
if computeDone = '1' then
featureDataStrobe <= '1';
calc_state <= waitOnComm1;
end if;
when waitOnComm1 =>
compute <= '0';
featureDataStrobe <= '0';
calc_state <= waitOnComm2;
when waitOnComm2 =>
compute <= '0';
featureDataStrobe <= '0';
calc_state <= waitOnComm3;
when waitOnComm3 =>
compute <= '0';
featureDataStrobe <= '0';
if acknowledge = '1' then
calc_state <= objectSearch;
end if;
end case;
if runCalc = '0' then
calc_state <= initSearch;
end if;
calcAddressDelayed <= calcAddress;
calcAddress <= cindex(9 downto 0);
 
end if; -- Syncronolus statements
end process calc;
-- calc: process(clk,reset)
-- variable cindex : std_logic_vector(10 downto 0) := (others=>'1');
-- begin
-- if reset = '1' then
-- cindex := conv_std_logic_vector(1,11);
-- calcAddress <= cindex(9 downto 0);
-- tablePreset <= '0';
-- compute <= '0';
-- calcCode <= (others=>'0');
--
-- elsif clk'event and clk = '1' then
--
-- if runCalc = '0' then
-- cindex := conv_std_logic_vector(1,11);
-- tablePreset <= '0';
-- calcAddress <= cindex(9 downto 0);
-- compute <= '0';
-- calcCode <= (others=>'0');
-- elsif computeDone = '1' and acknowledge = '1' then
-- compute <= '0';
-- if cindex < indexMax+1 then
-- if calcAddressDelayed = eqData and cindex > 1 then
-- calcCode <= calcAddressDelayed;
-- compute <= '1';
-- end if;
-- cindex := cindex + 1;
-- elsif cindex = indexMax+1 then
-- tablePreset <= '1';
-- cindex := cindex + 1;
-- else
-- tablePreset <= '0';
-- end if;
-- calcAddressDelayed <= calcAddress;
-- calcAddress <= cindex(9 downto 0);
-- else
-- compute <='0';
-- end if;
--
-- if computeDone = '1' and computeDoneDelay = '0' and acknowledge = '1' then
-- featureDataStrobe <= '1';
-- else
-- featureDataStrobe <= '0';
-- end if;
--
-- computeDoneDelay <= computeDone;
-- end if;
-- end process calc;
end Behavioral;
 
/image_component_labeling_and_feature_extraction/trunk/ram_num.vhd
0,0 → 1,60
----------------------------------------------------------------------------------
-- Company:
-- Engineer:
--
-- Create Date: 10:00:30 02/25/2009
-- Design Name:
-- Module Name: ram_num - Behavioral
-- Project Name:
-- Target Devices:
-- Tool versions:
-- Description:
--
-- Dependencies:
--
-- Revision:
-- Additional Comments:
--
----------------------------------------------------------------------------------
library IEEE;
use IEEE.STD_LOGIC_1164.ALL;
use IEEE.STD_LOGIC_ARITH.ALL;
use IEEE.STD_LOGIC_UNSIGNED.ALL;
 
---- Uncomment the following library declaration if instantiating
---- any Xilinx primitives in this code.
--library UNISIM;
--use UNISIM.VComponents.all;
 
entity ram_num is
Port ( addrW : in STD_LOGIC_VECTOR (9 downto 0);
din : in STD_LOGIC_VECTOR (33 downto 0);
we : in STD_LOGIC;
addrR : in STD_LOGIC_VECTOR (9 downto 0);
-- ramreset : in std_logic;
dout : out STD_LOGIC_VECTOR (33 downto 0);
-- test : out std_logic_vector (33 downto 0);
clk : in STD_LOGIC);
end ram_num;
 
architecture Behavioral of ram_num is
 
type ram_type is array(1023 downto 0) of std_logic_vector(33 downto 0);
signal ram_array : ram_type:=(others=>(others=>'0'));
begin
process(clk)
begin
if clk'event and clk ='1' then
if we='1' then
ram_array(conv_integer(addrW)) <= din;
end if;
dout <= ram_array(conv_integer(addrR));
end if;
end process;
 
 
end Behavioral;
 
 

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