def p2prpc_analyze_large_file(video_handle: io.IOBase, arg2: int) -> {
"res_var": int
}:
p2p_progress_hook(80, 100)
time.sleep(5)
video_handle.close()
return {"res_var": 10}
def p2prpc_analyze_large_file(video_handle: io.IOBase, arg2: int) -> {
"res_var": int
}:
p2p_progress_hook(80, 100)
for i in range(100000):
print("asdasdasdasdaasdasdasdasdasdasdasdasdasdasdasdasd" + str(i))
time.sleep(0.001)
video_handle.close()
return {"res_var": 10}
def analyze_movie(
video_handle: io.IOBase) -> {
"results": io.IOBase,
"video_results": io.IOBase
}:
"""
Args:
video_handle: file object for the movie to be analyzed.
progress_hook: function that is called with two integer arguments. the first one represents the current frame index
the second represents the final index.
Return:
dictionary containing path to the .csv file and to .mp4 file
"""
model = create_model_efficient(
model_creation_func=partial(create_model, max_operating_res=320))
video_handle.close()
video_file = video_handle.name
frame_ids = p2p_load('frame_ids',
loading_func=lambda filepath: np.load(filepath))
if frame_ids is None:
frame_ids = movement_frames_indexes(video_file,
progress_hook=p2p_progress_hook)
p2p_save("frame_ids",
frame_ids,
saving_func=lambda filepath, item: np.save(filepath, item),
filesuffix=".npy")
image_gen = framedatapoint_generator_by_frame_ids2(video_file,
frame_ids,
reason="motionmap")
# TODO set batchsize by the available VRAM
pred_gen = compute(image_gen, model=model, batch_size=5)
filtered_pred = filter_pred_detections(pred_gen)
if p2p_progress_hook is not None:
filtered_pred = generator_hook(video_file, filtered_pred,
p2p_progress_hook)
df = pred_iter_to_pandas(filtered_pred)
destination = os.path.splitext(video_file)[0] + '.csv'
df.to_csv(destination)
if p2p_progress_hook is not None:
# call one more time the hook. this is just for clean ending of the processing. it may happen in case where the
# skip is 5 that the final index is not reached, and in percentage it will look like 99.9% finished
size = get_video_file_size(video_file) - 1
p2p_progress_hook(size, size)
visual_destination = os.path.splitext(video_file)[0] + '_results.mp4'
visual_destination_good_codec = os.path.splitext(
video_file)[0] + '_results_good_codec.mp4'
compare_multiple_dataframes(video_file, visual_destination, df)
subprocess.call(
["ffmpeg", "-i", visual_destination, visual_destination_good_codec])
return {
"results": open(destination, 'rb'),
"video_results": open(visual_destination_good_codec, 'rb')
}
def p2prpc_analyze_large_file(
video_handle: io.IOBase, arg2: int
) -> {
"results_file1": io.IOBase,
"results_file2": io.IOBase,
"res_var": int
}:
p2p_progress_hook(80, 100)
time.sleep(5)
video_handle.close()
return {
"results_file1": open(video_handle.name, 'rb'),
"results_file2": open(__file__, 'rb'),
"res_var": 10
}