nodes/lquesada-ComfyUI-Inpaint-CropAndStitch
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Removed stray codepath

Browse Source
This commit is contained in:
Luis Quesada
2024-06-09 09:52:48 +02:00
parent 8368a3c7df
commit ac0d2ed056
1 changed files with 5 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files
inpaint_cropandstitch.py
+5 -3
View File
@@ -295,11 +295,13 @@ class InpaintCrop:
original_width = image.shape[2]
original_height = image.shape[1]
# If there are no non-zero indices in the context_mask, return the original image and original mask
# If there are no non-zero indices in the context_mask, adjust context mask to the whole image
non_zero_indices = torch.nonzero(context_mask[0], as_tuple=True)
if not non_zero_indices[0].size(0):
stitch = {'x': 0, 'y': 0, 'original_image': original_image, 'cropped_mask_blend': mask, 'rescale_x': 1.0, 'rescale_y': 1.0, 'start_x': start_x, 'start_y': start_y, 'initial_width': initial_width, 'initial_height': initial_height}
return (stitch, original_image, original_mask)
context_mask = torch.ones_like(image[:, :, :, 0])
context_mask = torch.zeros((mask_batch, new_height, new_width), dtype=mask.dtype)
context_mask[:, start_y:start_y + initial_height, start_x:start_x + initial_width] += 1.0
non_zero_indices = torch.nonzero(context_mask[0], as_tuple=True)
# Compute context area from context mask
y_min = torch.min(non_zero_indices[0]).item()