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In preprocess_image, using consistent cutoff value for bounding box and pre-multiplied alpha #186

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In preprocess_image, using consistent cutoff value for bounding box and pre-multiplied alpha #186

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5 changes: 3 additions & 2 deletions trellis/pipelines/trellis_image_to_3d.py
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Original file line number Diff line number Diff line change
Expand Up @@ -105,7 +105,8 @@ def preprocess_image(self, input: Image.Image) -> Image.Image:
output = rembg.remove(input, session=self.rembg_session)
output_np = np.array(output)
alpha = output_np[:, :, 3]
bbox = np.argwhere(alpha > 0.8 * 255)
alpha_cutoff = 0.8
bbox = np.argwhere(alpha > alpha_cutoff * 255)
bbox = np.min(bbox[:, 1]), np.min(bbox[:, 0]), np.max(bbox[:, 1]), np.max(bbox[:, 0])
center = (bbox[0] + bbox[2]) / 2, (bbox[1] + bbox[3]) / 2
size = max(bbox[2] - bbox[0], bbox[3] - bbox[1])
Expand All @@ -114,7 +115,7 @@ def preprocess_image(self, input: Image.Image) -> Image.Image:
output = output.crop(bbox) # type: ignore
output = output.resize((518, 518), Image.Resampling.LANCZOS)
output = np.array(output).astype(np.float32) / 255
output = output[:, :, :3] * output[:, :, 3:4]
output = output[:, :, :3] * (output[:, :, 3:4] > alpha_cutoff)
output = Image.fromarray((output * 255).astype(np.uint8))
return output

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