fdd55d36c05c747643fc98430a7f9b787b6cec16,gluoncv/data/kinetics400/classification.py,Kinetics400,_TSN_RGB,#Kinetics400#Any#Any#Any#Any#Any#Any#Any#,167

Before Change

                frame_path = directory + "/" + frame_name
                cv_img_origin = cv2.imread(frame_path, cv_read_flag)
                if cv_img_origin is None:
                    raise(RuntimeError("Could not load file %s. Check data path." % (frame_path)))
                if new_width > 0 and new_height > 0:
                    cv_img = cv2.resize(cv_img_origin, (new_width, new_height), interpolation)
                else:
                    cv_img = cv_img_origin

After Change

            for length_id in range(1, skip_length + 1, new_step):
                frame_path = os.path.join(directory, name_pattern % (length_id + offset))
                cv_img = self.cv2.imread(frame_path)
                if cv_img is None:
                    if length_id == 1:
                        raise(RuntimeError("Could not load file %s starting at frame %d. Check data path." % (frame_path, offset)))
                    sampled_list.append(np.zeros((new_height, new_width, 3)))   // pad black frames if this video clip does not have `skip_length` frames
                    continue
                if new_width > 0 and new_height > 0:
                    h, w, _ = cv_img.shape
                    if h != new_height or w != new_width:
                        cv_img = self.cv2.resize(cv_img, (new_width, new_height))
                cv_img = cv_img[:, :, ::-1]
                sampled_list.append(cv_img)

Instances