could not broadcast input array from shape (636,732,4) into shape (636,48,4)

[zoldaten]

hi !
i am trying with
python scripts/sampling/simple_video_sample.py --input_path assets/berry.png --version sv3d_u

but have error (in title):

generative-models/scripts/sampling/simple_video_sample.py", line 155, in sample
    padded_image[
ValueError: could not broadcast input array from shape (636,732,4) into shape (636,48,4)

with test image all OK.

whats wrong ?

[merkol]

same issue here even though I provide an image with resolutions (576, 1024, 3) same as test image. I get broadcasting error

[Farenweh]

I got the very same question and still found no reason or workaround.

[Farenweh]

I've found a workaround, try modifing
side_len = ( int(max_size / image_frame_ratio) if image_frame_ratio is not None else in_w )
to
side_len = ( int(max_size / image_frame_ratio) if image_frame_ratio is not None else max(in_w, in_h))
，by applying this workaround, the script could avoid wrong segement mask from simple cv2.threshold( np.array(image.split()[-1]), 0, 255, cv2.THRESH_BINARY causing array be small incorrectly.

HOWEVERE, it's just a workaound which may lead to performance degrading cauz it warns "WARNING: The conditioning frame you provided is not 576x576. This leads to suboptimal performance as model was only trained on 576x576.", thus we may need an elegent fix.

[zoldaten]

I've found a workaround, try modifing side_len = ( int(max_size / image_frame_ratio) if image_frame_ratio is not None else in_w ) to side_len = ( int(max_size / image_frame_ratio) if image_frame_ratio is not None else max(in_w, in_h)) ，by applying this workaround, the script could avoid wrong segement mask from simple cv2.threshold( np.array(image.split()[-1]), 0, 255, cv2.THRESH_BINARY causing array be small incorrectly.

HOWEVERE, it's just a workaound which may lead to performance degrading cauz it warns "WARNING: The conditioning frame you provided is not 576x576. This leads to suboptimal performance as model was only trained on 576x576.", thus we may need an elegent fix.

it`s working -

000003.mp4