<jupyter_start><jupyter_text>Old test with old code implemented.<jupyter_code>video = None
for v in dataset.get_subset_videos('validation'):
    if v.video_id == 'Uw_0h2UrfyY':
        video = v
print(video.serialize())
video.get_video_instances(16, 0)
ground_trouth = np.array([instance.output for instance in video.instances])
print(ground_trouth)
detection_prediction_path = detection_predictions_path + video.video_id + '.npy'
classification_prediction_path =  classification_predictions_path + video.video_id + '.npy'

class_prediction = np.load(classification_prediction_path)
detection_prediction = np.load(detection_prediction_path)

print(class_prediction)
print(detection_prediction)
mix = np.zeros(class_prediction.shape, dtype=np.int64)
for pos in range(class_prediction.size):
    if detection_prediction[pos] == 1:
        mix[pos] = class_prediction[pos]

print(mix)

prediction = get_temporal_predictions_2(mix, fps=video.fps)
pprint.pprint(prediction)<jupyter_output>[  0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
   0 105 105 105 105 105   0   0   0   0   0   0   0   0 105 105 105 105
 105 105 105 105 105 105 105 105 105   0   0 105 105 105 105 105 105 105
 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105
 105 105 105 105   0 105 105   0 105   0   0   0   0   0   0   0   0   0
   0 177 177 177   0   0 177   0   0 177 177 177 177 177 177 177 177 177
 177 177 177 177 177 177 177   0   0   0   0 177   0 177 177 177 177 177
 177 177 177 177 177 177 177 177 177 177   0 177   0   0 177 177 177 177
 177 177 177 177 177   0   0 177 177 105 105 177 177 105 105 105 105 177
 177 177 105 177 177 177 177 177 177 177 177 177 177 177 177 105 105 105
 105 105 105   0   0 105   0 177 177 177 177 177   0 177 177 177 177 177
 177 177 177 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105
 105 105   0   0   0 105 105 105 105 105 105   0   0   0   0   0   0   0
   0   0   0   0   0   0   0   0 105 177 177 177 10[...]
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