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I use run.py to generate novel views. However, the results look a bit weird with artifacts in the images. I tried with other samples from the GSO dataset and even with the hamburger and chair images in this repo, but the issue persists.
Do you have any hypotheses about this behavior?
We only modify image processing to use the alpha channels in RGBA image.
for i, image_path in enumerate(args.image):
if args.no_remove_bg:
image = np.array(Image.open(image_path))
image = image / 255.0
image = image[:, :, :3] * image[:, :, 3:4] + (1 - image[:, :, 3:4]) * 1.0
image = Image.fromarray((image * 255.0).astype(np.uint8))
if not os.path.exists(os.path.join(output_dir, str(i))):
os.makedirs(os.path.join(output_dir, str(i)))
image.save(os.path.join(output_dir, str(i), f"input.png"))
images.append(image)
timer.end("Processing images")
The text was updated successfully, but these errors were encountered:
I use run.py to generate novel views. However, the results look a bit weird with artifacts in the images. I tried with other samples from the GSO dataset and even with the hamburger and chair images in this repo, but the issue persists.
Do you have any hypotheses about this behavior?
We only modify image processing to use the alpha channels in RGBA image.
The text was updated successfully, but these errors were encountered: