ee602b6f68f0bdd19f449a86955697f8f0a2d54c,gluoncv/data/transforms/video.py,VideoNormalize,forward,#VideoNormalize#Any#,69

Before Change

        num_images = int(c / 3)
        clip_mean = self.mean * num_images
        clip_std = self.std * num_images
        clip_mean = nd.array(np.asarray(clip_mean).reshape((c, 1, 1)))
        clip_std = nd.array(np.asarray(clip_std).reshape((c, 1, 1)))
        return (clips - clip_mean) / clip_std

class VideoRandomHorizontalFlip(Block):

After Change

        self.std = np.asarray(std).reshape((len(std), 1, 1))

    def forward(self, clips):
        new_clips = []
        for cur_img in clips:
            new_clips.append((cur_img - self.mean) / self.std)
        return new_clips

Instances