# i.e. a single-column array, where each item in the column has the pixel RGB value
frame = np.copy(frame1.array)
frame.setflags(write=1)
frame_expanded = np.expand_dims(frame, axis=0)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
if counter%5 is 0:
if p is None:
p = Process(target=classify_frame, args=(detection_boxes, detection_scores, detection_classes, num_detections,image_tensor, frame_expanded,))
p.start()
#print("get in")
if not p.isAlive():
p.join()
print("finishes")
#print(finalBoxes)
#print(boxes
p = Process(target=classify_frame, args=(detection_boxes, detection_scores, detection_classes, num_detections,image_tensor, frame_expanded,))
p.start()
firstTime = False
if not firstTime:
vis_util.visualize_boxes_and_labels_on_image_array(
frame,
np.squeeze(finalBoxes),
np.squeeze(finalClasses).astype(np.int32),
np.squeeze(finalScores),
category_index,
