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Making object picklable

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-2

I'm trying to do multiprocessing, but I'm facing type error object is not pickable
1. I'm using tensorflow
2. OpenCV
3. Numpy
4. Pandas

I have two classes detection of tensor flow and tracking using kalman filter.

I'm not sure how to make those objects picklable or how to trace them or know how to fix them.
I googled a lot on that issues, couldn't find anything find usefull

if __name__ == "__main__":
 video_name = '2016-11-18_07-30-01.h264'

 cap = cv2.VideoCapture(video_name)

 det = detector.CarDetector()
 car_tracker = Sort_Algorithm.Sort()
 ped_tracker = Sort_Algorithm.Sort()
 df_region, df_line = load_filter()
 threadn = cv2.getNumberOfCPUs()
 pool = Pool(processes=2)
 pending = Queue()
 threaded_mode = True

 while True:
 while pending.qsize() > 0:
 res = pending.get()
 cv2.imshow('video ', res)

 if pending.qsize() < 2:
 ret, frame = cap.read()
 if threaded_mode:
 t1 = time.time()
 H = [-2.01134074616, -16.6502442427, -1314.05715739, -3.35391526592, -22.3546973012, 2683.63584335,
 -0.00130731963137, -0.0396207582264, 1]
 matrix = np.reshape(H, (3, 3))
 dst = cv2.warpPerspective(frame.copy(), matrix, (frame.shape[1], frame.shape[0]))
 task = pool.apply_async(pipeline,
 (frame.copy(), car_tracker, ped_tracker, df_region, df_line, det, dst, matrix))

 cv2.imshow('dst', dst)
 else:
 task = DummyTask(pipeline,
 (frame.copy(), car_tracker, ped_tracker, df_region, df_line, det, dst, matrix))

 pending.put(task)
 ch = cv2.waitKey(1)
 if ch == ord(' '):
 threaded_mode = not threaded_mode
 if ch == 27:
 break




class DummyTask:
 def __init__(self, data):
 self.data = data
 def ready(self):
 return True
 def get(self):
 return self.data

python multiprocessing

share|improve this question

edited Mar 22 at 8:13

Waleed Saleh

asked Mar 21 at 21:26

Waleed SalehWaleed Saleh

85

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  share DummyTask() code. Picking has strict rules, for an object being pickable all its attributes need to be pickable. Checkout the docs: docs.python.org/3/library/…
  
  – geckos
  Mar 21 at 22:09
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @geckos I shared the DummyTask()
  
  – Waleed Saleh
  Mar 22 at 8:13
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  You are passing 2 parameters to DummyTask, but only declared one? You can try to pickle.dumps(DummyTask(...)) with the same parameters and see if you got a error
  
  – geckos
  Mar 22 at 10:20
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  still TypeError: can't pickle _thread.lock objects
  
  – Waleed Saleh
  Mar 22 at 10:48
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Now we have something. I guess _thread.lock is coming from pipeline?
  
  – geckos
  Mar 22 at 12:39
  

  
  
  
  

 | 
show 3 more comments

-2

I'm trying to do multiprocessing, but I'm facing type error object is not pickable
1. I'm using tensorflow
2. OpenCV
3. Numpy
4. Pandas

I have two classes detection of tensor flow and tracking using kalman filter.

I'm not sure how to make those objects picklable or how to trace them or know how to fix them.
I googled a lot on that issues, couldn't find anything find usefull

if __name__ == "__main__":
 video_name = '2016-11-18_07-30-01.h264'

 cap = cv2.VideoCapture(video_name)

 det = detector.CarDetector()
 car_tracker = Sort_Algorithm.Sort()
 ped_tracker = Sort_Algorithm.Sort()
 df_region, df_line = load_filter()
 threadn = cv2.getNumberOfCPUs()
 pool = Pool(processes=2)
 pending = Queue()
 threaded_mode = True

 while True:
 while pending.qsize() > 0:
 res = pending.get()
 cv2.imshow('video ', res)

 if pending.qsize() < 2:
 ret, frame = cap.read()
 if threaded_mode:
 t1 = time.time()
 H = [-2.01134074616, -16.6502442427, -1314.05715739, -3.35391526592, -22.3546973012, 2683.63584335,
 -0.00130731963137, -0.0396207582264, 1]
 matrix = np.reshape(H, (3, 3))
 dst = cv2.warpPerspective(frame.copy(), matrix, (frame.shape[1], frame.shape[0]))
 task = pool.apply_async(pipeline,
 (frame.copy(), car_tracker, ped_tracker, df_region, df_line, det, dst, matrix))

 cv2.imshow('dst', dst)
 else:
 task = DummyTask(pipeline,
 (frame.copy(), car_tracker, ped_tracker, df_region, df_line, det, dst, matrix))

 pending.put(task)
 ch = cv2.waitKey(1)
 if ch == ord(' '):
 threaded_mode = not threaded_mode
 if ch == 27:
 break




class DummyTask:
 def __init__(self, data):
 self.data = data
 def ready(self):
 return True
 def get(self):
 return self.data

python multiprocessing

share|improve this question

edited Mar 22 at 8:13

Waleed Saleh

asked Mar 21 at 21:26

Waleed SalehWaleed Saleh

85

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  share DummyTask() code. Picking has strict rules, for an object being pickable all its attributes need to be pickable. Checkout the docs: docs.python.org/3/library/…
  
  – geckos
  Mar 21 at 22:09
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @geckos I shared the DummyTask()
  
  – Waleed Saleh
  Mar 22 at 8:13
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  You are passing 2 parameters to DummyTask, but only declared one? You can try to pickle.dumps(DummyTask(...)) with the same parameters and see if you got a error
  
  – geckos
  Mar 22 at 10:20
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  still TypeError: can't pickle _thread.lock objects
  
  – Waleed Saleh
  Mar 22 at 10:48
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Now we have something. I guess _thread.lock is coming from pipeline?
  
  – geckos
  Mar 22 at 12:39
  

  
  
  
  

 | 
show 3 more comments

I'm trying to do multiprocessing, but I'm facing type error object is not pickable
1. I'm using tensorflow
2. OpenCV
3. Numpy
4. Pandas

I have two classes detection of tensor flow and tracking using kalman filter.

I'm not sure how to make those objects picklable or how to trace them or know how to fix them.
I googled a lot on that issues, couldn't find anything find usefull

if __name__ == "__main__":
 video_name = '2016-11-18_07-30-01.h264'

 cap = cv2.VideoCapture(video_name)

 det = detector.CarDetector()
 car_tracker = Sort_Algorithm.Sort()
 ped_tracker = Sort_Algorithm.Sort()
 df_region, df_line = load_filter()
 threadn = cv2.getNumberOfCPUs()
 pool = Pool(processes=2)
 pending = Queue()
 threaded_mode = True

 while True:
 while pending.qsize() > 0:
 res = pending.get()
 cv2.imshow('video ', res)

 if pending.qsize() < 2:
 ret, frame = cap.read()
 if threaded_mode:
 t1 = time.time()
 H = [-2.01134074616, -16.6502442427, -1314.05715739, -3.35391526592, -22.3546973012, 2683.63584335,
 -0.00130731963137, -0.0396207582264, 1]
 matrix = np.reshape(H, (3, 3))
 dst = cv2.warpPerspective(frame.copy(), matrix, (frame.shape[1], frame.shape[0]))
 task = pool.apply_async(pipeline,
 (frame.copy(), car_tracker, ped_tracker, df_region, df_line, det, dst, matrix))

 cv2.imshow('dst', dst)
 else:
 task = DummyTask(pipeline,
 (frame.copy(), car_tracker, ped_tracker, df_region, df_line, det, dst, matrix))

 pending.put(task)
 ch = cv2.waitKey(1)
 if ch == ord(' '):
 threaded_mode = not threaded_mode
 if ch == 27:
 break




class DummyTask:
 def __init__(self, data):
 self.data = data
 def ready(self):
 return True
 def get(self):
 return self.data

python multiprocessing

share|improve this question

edited Mar 22 at 8:13

Waleed Saleh

asked Mar 21 at 21:26

Waleed SalehWaleed Saleh

85

if __name__ == "__main__":
 video_name = '2016-11-18_07-30-01.h264'

 cap = cv2.VideoCapture(video_name)

 det = detector.CarDetector()
 car_tracker = Sort_Algorithm.Sort()
 ped_tracker = Sort_Algorithm.Sort()
 df_region, df_line = load_filter()
 threadn = cv2.getNumberOfCPUs()
 pool = Pool(processes=2)
 pending = Queue()
 threaded_mode = True

 while True:
 while pending.qsize() > 0:
 res = pending.get()
 cv2.imshow('video ', res)

 if pending.qsize() < 2:
 ret, frame = cap.read()
 if threaded_mode:
 t1 = time.time()
 H = [-2.01134074616, -16.6502442427, -1314.05715739, -3.35391526592, -22.3546973012, 2683.63584335,
 -0.00130731963137, -0.0396207582264, 1]
 matrix = np.reshape(H, (3, 3))
 dst = cv2.warpPerspective(frame.copy(), matrix, (frame.shape[1], frame.shape[0]))
 task = pool.apply_async(pipeline,
 (frame.copy(), car_tracker, ped_tracker, df_region, df_line, det, dst, matrix))

 cv2.imshow('dst', dst)
 else:
 task = DummyTask(pipeline,
 (frame.copy(), car_tracker, ped_tracker, df_region, df_line, det, dst, matrix))

 pending.put(task)
 ch = cv2.waitKey(1)
 if ch == ord(' '):
 threaded_mode = not threaded_mode
 if ch == 27:
 break




class DummyTask:
 def __init__(self, data):
 self.data = data
 def ready(self):
 return True
 def get(self):
 return self.data

share|improve this question

edited Mar 22 at 8:13

Waleed Saleh

asked Mar 21 at 21:26

Waleed SalehWaleed Saleh

85

share|improve this question

edited Mar 22 at 8:13

Waleed Saleh

asked Mar 21 at 21:26

Waleed SalehWaleed Saleh

85

asked Mar 21 at 21:26

Waleed SalehWaleed Saleh

85

asked Mar 21 at 21:26

Waleed SalehWaleed Saleh

85