xinyun/ComfyUI-KJNodes
1
0
Fork 0
mirror of https://git.datalinker.icu/kijai/ComfyUI-KJNodes.git synced 2026-01-27 13:54:44 +08:00
Code Issues Packages Projects Releases Wiki Activity

BatchCropFromMaskAdvanced: Fixing bounding boxes being bigger than the input images when using crop_size_mult

Browse Source
This commit is contained in:
David Bielejeski 2024-04-02 18:10:16 -05:00
parent 776bf61380
commit b14620f227
1 changed files with 4 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
nodes.py
View File

@ -1889,6 +1889,10 @@ class BatchCropFromMaskAdvanced:
# Make sure max_bbox_size is divisible by 16, if not, round it upwards so it is
self.max_bbox_size = math.ceil(self.max_bbox_size / 16) * 16
if self.max_bbox_size > original_images[0].shape[0] or self.max_bbox_size > original_images[0].shape[1]:
# max_bbox_size can only be as big as our input's width or height, and it has to be even
self.max_bbox_size = math.floor(min(original_images[0].shape[0], original_images[0].shape[1]) / 2) * 2
# Then, for each mask and corresponding image...
for i, (mask, img) in enumerate(zip(masks, original_images)):
_mask = tensor2pil(mask)[0]
@ -1916,7 +1920,6 @@ class BatchCropFromMaskAdvanced:
# Create bounding box using max_bbox_size
half_box_size = self.max_bbox_size // 2
half_box_size = self.max_bbox_size // 2
min_x = max(0, center[0] - half_box_size)
max_x = min(img.shape[1], center[0] + half_box_size)
min_y = max(0, center[1] - half_box_size)