ee602b6f68f0bdd19f449a86955697f8f0a2d54c,gluoncv/data/transforms/video.py,VideoMultiScaleCrop,forward,#VideoMultiScaleCrop#Any#,199

Before Change

        return crop_sizes

    def forward(self, clips):
        clips = clips.asnumpy()
        h, w, c = clips.shape

        crop_size_pairs = self.fillCropSize(h, w)
        size_sel = random.randint(0, len(crop_size_pairs)-1)
        crop_height = crop_size_pairs[size_sel][0]
        crop_width = crop_size_pairs[size_sel][1]

        if self.fix_crop:
            offsets = self.fillFixOffset(h, w)
            off_sel = random.randint(0, len(offsets)-1)
            h_off = offsets[off_sel][0]
            w_off = offsets[off_sel][1]
        else:
            h_off = random.randint(0, h - self.height)
            w_off = random.randint(0, w - self.width)

        scaled_clips = np.zeros((self.height, self.width, c))
        num_imgs = int(c / 3)
        for frame_id in range(num_imgs):
            cur_img = clips[:, :, frame_id*3:frame_id*3+3]
            crop_img = cur_img[h_off:h_off+crop_height, w_off:w_off+crop_width, :]
            scaled_clips[:, :, frame_id*3:frame_id*3+3] = \
            	self.cv2.resize(crop_img, (self.width, self.height))
        return nd.array(scaled_clips)

class VideoCenterCrop(Block):
    Crops the given numpy array at the center to have a region of

After Change

            h_off = random.randint(0, h - self.height)
            w_off = random.randint(0, w - self.width)

        new_clips = []
        for cur_img in clips:
            crop_img = cur_img[h_off:h_off+crop_height, w_off:w_off+crop_width, :]
            new_clips.append(self.cv2.resize(crop_img, (self.width, self.height)))
        return new_clips


class VideoCenterCrop(Block):
    Crop images at the center to have a region of

Instances