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Update curve_nodes.py

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kijai 2024-08-02 20:43:00 +03:00
parent dee4e8f1eb
commit 17f8d8db60
1 changed files with 13 additions and 10 deletions
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nodes/curve_nodes.py
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@ -1308,18 +1308,21 @@ output types:
normalized_y_values.append(norm_y) normalized_y_values.append(norm_y)
normalized.append({'x':norm_x, 'y':norm_y}) normalized.append({'x':norm_x, 'y':norm_y})
bboxes = json.loads(bboxes) # Create a blank mask
bboxes = [(int(bboxes["x"]), int(bboxes["y"]), int(bboxes["width"]), int(bboxes["height"]))]
# Create a blank mask
mask = np.zeros((height, width), dtype=np.uint8) mask = np.zeros((height, width), dtype=np.uint8)
bboxes = json.loads(bboxes)
print(bboxes)
if bboxes["x"] is None or bboxes["y"] is None or bboxes["width"] is None or bboxes["height"] is None:
bboxes = []
else:
bboxes = [(int(bboxes["x"]), int(bboxes["y"]), int(bboxes["width"]), int(bboxes["height"]))]
# Draw the bounding box on the mask # Draw the bounding box on the mask
for bbox in bboxes: for bbox in bboxes:
x_min, y_min, w, h = bbox x_min, y_min, w, h = bbox
x_max = x_min + w x_max = x_min + w
y_max = y_min + h y_max = y_min + h
mask[y_min:y_max, x_min:x_max] = 1 # Fill the bounding box area with 1s mask[y_min:y_max, x_min:x_max] = 1 # Fill the bounding box area with 1s
mask_tensor = torch.from_numpy(mask) mask_tensor = torch.from_numpy(mask)
mask_tensor = mask_tensor.unsqueeze(0).float().cpu() mask_tensor = mask_tensor.unsqueeze(0).float().cpu()