Halcon之多线程

Halcon之多线程Halcon之多线程Halcon之多线程

开多线程

par_start <ThreadID> : read_image (Image1, 'printer_chip/printer_chip_01')

等待多个线程都结束

* 开启两个子线程
par_start <ThreadID1> : producer_proc()
par_start <ThreadID2> : consumer_proc()
* 等到两个子线程都结束
par_join ([ThreadID1, ThreadID2])

示例1：

******************************************************************
************************* halcon实现多线程*************************
******************************************************************
* 开启多个子线程
par_start <ThreadID1> : read_image (Image1, 'printer_chip/printer_chip_01')
par_start <ThreadID2> : read_image (Image2, 'printer_chip/printer_chip_01')
par_start <ThreadID1> : read_image (Image3, 'printer_chip/printer_chip_01')
par_start <ThreadID2> : read_image (Image4, 'printer_chip/printer_chip_01')
par_start <ThreadID1> : read_image (Image5, 'printer_chip/printer_chip_01')
par_start <ThreadID2> : read_image (Image6, 'printer_chip/printer_chip_01')
par_start <ThreadID1> : read_image (Image7, 'printer_chip/printer_chip_01')
par_start <ThreadID2> : read_image (Image8, 'printer_chip/printer_chip_01')
par_start <ThreadID1> : read_image (Image9, 'printer_chip/printer_chip_01')
par_start <ThreadID2> : read_image (Image10, 'printer_chip/printer_chip_01')
* 等到多个子线程都结束（从这里开始执行子线程）
par_join ([ThreadID1, ThreadID2])

示例2：

* This is a simple example program that demonstrates the
* option to call several HALCON operators or procedures in parallel.
* In general, owing to the overhead of thread creation,
* not in all cases a speedup can be expected,
* especially, if the used operators are already parallelized
* internally using the automatic operator parallelization.
*
* Number of loops to get a more robust time measurement
Loops := 3
*
* Initialize visualization
dev_update_off ()
dev_close_window ()
read_image (Image, 'barcode/mixed/barcodes_datacodes_mixed_01')
dev_open_window_fit_image (Image, 0, 0, -1, -1, WindowHandle)
set_display_font (WindowHandle, 16, 'mono', 'true', 'false')
dev_display (Image)
disp_message (WindowHandle, 'Read codes sequentially and multithreaded (multiple times)', 'window', 12, 12, 'black', 'true')
*
* Part A
*
* Show thread creation overhead
*
* Thread creation causes a significant overhead.
* Therefore, it is not advisable to create threads for fast tasks.
*
count_seconds (T1)
for L := 1 to Loops * 10 by 1par_start<Thread1> : do_nothing ()par_start<Thread2> : do_nothing ()par_start<Thread3> : do_nothing ()* par_join basically takes as long as the slowest thread (plus overhead).* Use the profiler to check execution times.par_join ([Thread1,Thread2,Thread3])
endfor
count_seconds (T2)
* Time needed to create and join the three threads in milliseconds
TimeOverhead := 1000.0 * (T2 - T1) / (Loops * 10)
*
* Part B
*
* Show perfect parallelization
*
* The best speedup can be achieved for long running tasks
* that are not parallelized internally.
*
count_seconds (T1)
for L := 1 to Loops by 1par_start<Thread1> : wait_seconds (1)par_start<Thread2> : wait_seconds (1)par_start<Thread3> : wait_seconds (1)* par_join basically takes as long as the slowest thread (plus overhead).* Use the profiler to check execution times.par_join ([Thread1,Thread2,Thread3])
endfor
count_seconds (T2)
* This should be about 1000 milliseconds
TimeWaitSeconds := 1000.0 * (T2 - T1) / Loops
*
* Part C
*
* Read bar codes and data codes in parallel
*
*
* Create the bar code and data code models
create_data_code_2d_model ('QR Code', [], [], QrCodeModel)
create_data_code_2d_model ('Data Matrix ECC 200', 'default_parameters', 'maximum_recognition', Ecc200Model)
create_bar_code_model ([], [], BarCodeModel)
*
* Training
find_data_code_2d (Image, QrCodeXldsSeq, QrCodeModel, ['stop_after_result_num','train'], [2,'all'], QrCodeHandlesSeq, QrCodeStringsSeq)
find_data_code_2d (Image, Ecc200XldsSeq, Ecc200Model, ['stop_after_result_num','train'], [2,'all'], Ecc200HandlesSeq, Ecc200StringsSeq)
find_bar_code (Image, BarCodeRegionsSeq, BarCodeModel, ['EAN-13','Code 128'], BarCodeStringsSeq)
*
* Execute once to fill cache
find_qr_codes (Image, QrCodeXldsSeq, QrCodeModel, QrCodeHandlesSeq, QrCodeStringsSeq)
find_ecc200_codes (Image, Ecc200Xlds, Ecc200Model, Ecc200Handles, Ecc200Strings)
find_bar_codes (Image, BarCodeRegions, BarCodeModel, BarCodeStrings)
*
* Read codes sequentially
count_seconds (T1)
for L := 1 to Loops by 1find_qr_codes (Image, QrCodeXldsSeq, QrCodeModel, QrCodeHandlesSeq, QrCodeStringsSeq)find_ecc200_codes (Image, Ecc200Xlds, Ecc200Model, Ecc200Handles, Ecc200Strings)find_bar_codes (Image, BarCodeRegions, BarCodeModel, BarCodeStrings)
endfor
count_seconds (T2)
*
TimeSeq := 1000.0 * (T2 - T1) / Loops
*
* Read codes in parallel
count_seconds (T1)
for L := 1 to Loops by 1par_start<ThreadQRCode> : find_qr_codes (Image, QrCodeXlds, QrCodeModel, QrCodeHandlesSeq, QrCodeStringsSeq)par_start<ThreadECC200> : find_ecc200_codes (Image, Ecc200Xlds, Ecc200Model, Ecc200Handles, Ecc200Strings)par_start<ThreadBarcode> : find_bar_codes (Image, BarCodeRegions, BarCodeModel, BarCodeStrings)* par_join basically takes as long as the slowest thread (plus overhead).par_join ([ThreadQRCode,ThreadECC200,ThreadBarcode])
endfor
count_seconds (T2)
TimePar := 1000.0 * (T2 - T1) / Loops
*
* Calculate speedup
Speedup := 100 * ((TimeSeq / TimePar) - 1)
*
* Display result
dev_set_draw ('margin')
dev_set_line_width (4)
dev_set_color ('yellow')
dev_display (QrCodeXlds)
dev_set_color ('green')
dev_display (Ecc200Xlds)
dev_set_color ('cyan')
dev_display (BarCodeRegions)
Color := ['forest green','red']
disp_message (WindowHandle, 'Multithreading speedup: ' + Speedup$'.2f' + '%', 'window', 42, 12, Color[Speedup < 1], 'true')
*
clear_bar_code_model (BarCodeModel)
clear_data_code_2d_model (Ecc200Model)
clear_data_code_2d_model (QrCodeModel)

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Halcon之多线程

Halcon之多线程Halcon之多线程Halcon之多线程

开多线程

等待多个线程都结束

示例1：

示例2：

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