I am trying to run video through YoloV3
using this post as reference A Hands on Guide to Multiprocessing in Python
I took out the part where the predictions happen from inside a loop and placed it in a function
def yolo_detect1(CUDA,inp_dim,frame,confidence,num_classes,frames,nms_thesh):
img, orig_im, dim = prep_image(frame, inp_dim)
print(img, orig_im, dim)
im_dim = torch.FloatTensor(dim).repeat(1,2)
print('MIDDLE')
if CUDA:
im_dim = im_dim.cuda()
img = img.cuda()
with torch.no_grad():
output = model(Variable(img), CUDA)
output = write_results(output, confidence, num_classes, nms = True, nms_conf = nms_thesh)
im_dim = im_dim.repeat(output.size(0), 1)
scaling_factor = torch.min(inp_dim/im_dim,1)[0].view(-1,1)
output[:,[1,3]] -= (inp_dim - scaling_factor*im_dim[:,0].view(-1,1))/2
output[:,[2,4]] -= (inp_dim - scaling_factor*im_dim[:,1].view(-1,1))/2
output[:,1:5] /= scaling_factor
for i in range(output.shape[0]):
output[i, [1,3]] = torch.clamp(output[i, [1,3]], 0.0, im_dim[i,0])
output[i, [2,4]] = torch.clamp(output[i, [2,4]], 0.0, im_dim[i,1])
for x in enumerate(output):
write(x[1], orig_im)
print('DONE')
cv2.imshow('frame1',orig_im)
return orig_im
Loop
time_interval = 15
processes0 = []
processes1 = []
start_time1 = time.time()
frames = 0
start = time.time()
selection_setter = 0
while cap.isOpened():
ret, frame = cap.read()
if ret:
current_time = time.time()
time_difference = current_time - start_time1
process_selector = (int(time_difference)//time_interval)%2
# odd
if process_selector == 1:
selection_setter = 2
elif process_selector == 0:
selection_setter = 1
print('process_selector ',process_selector)
print('selection_setter ',selection_setter)
if selection_setter == 1:
try:
if processes1:
for process in processes1:
process.join()
p = Process(target=yolo_detect1, args=(torch,CUDA,inp_dim,frame,confidence,num_classes,frames,nms_thesh))
processes0.append(p)
p.start()
except Exception as e:
print(traceback.format_exc())
elif selection_setter == 2:
if processes0:
for process in processes0:
process.join()
p = Process(target=yolo_detect2, args=(torch,CUDA,inp_dim,frame,confidence,num_classes,frames,nms_thesh))
processes1.append(p)
p.start()
# yolo_result = yolo_detect(frame,confidence,num_classes,frames,nms_thesh)
# list(map(lambda x: write(x, orig_im), output))
# cv2.imshow("frame", yolo_result)
key = cv2.waitKey(1)
if key & 0xFF == ord('q'):
break
frames += 1
# print("FPS of the video is {:5.2f}".format( frames / (time.time() - start)))
else:
break
The code stops without any warning, I tried to find out where the code got stuck
I altered this prep_image to know what exactly was the issue
def prep_image(img, inp_dim):
"""
Prepare image for inputting to the neural network.
Returns a Variable
"""
print('PREP IMAGE')
try:
orig_im = img
dim = orig_im.shape[1], orig_im.shape[0]
print('HERE1')
img = (letterbox_image(orig_im, (inp_dim, inp_dim)))
print('HERE2')
img_ = img[:,:,::-1].transpose((2,0,1)).copy()
print('HERE3')
img_ = torch.from_numpy(img_).float().div(255.0).unsqueeze(0)
print('HERE4')
print('RETURN VALUES')
return img_, orig_im, dim
except Exception:
print(traceback.format_exc())
But this is all the code outputs and it gets stuck
process_selector 0
selection_setter 1
STARTED
PREP IMAGE
HERE1
HERE2
HERE3
process_selector 0
selection_setter 1
STARTED
PREP IMAGE
HERE1
HERE2
HERE3
The function is getting stuck at this line img_ = torch.from_numpy(img_).float().div(255.0).unsqueeze(0) inside prep_image