mlbench123 commited on
Commit
2b1a638
·
verified ·
1 Parent(s): ab757bd

Update app.py

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Files changed (1) hide show
  1. app.py +4 -4
app.py CHANGED
@@ -979,14 +979,14 @@ def predict_with_paper(image, paper_size, offset, offset_unit, finger_clearance=
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  if not results or len(results) == 0 or not hasattr(results[0], 'boxes') or len(results[0].boxes) == 0:
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  logger.warning("No objects detected by YOLOv8, proceeding with full image")
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- cropped_image = masked_input_image
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  crop_offset = (0, 0)
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  else:
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  boxes = results[0].boxes.xyxy.cpu().numpy()
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  confidences = results[0].boxes.conf.cpu().numpy()
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  # Filter out very large boxes (likely paper/background)
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- image_area = masked_input_image.shape[0] * masked_input_image.shape[1]
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  valid_boxes = []
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  for i, box in enumerate(boxes):
@@ -998,7 +998,7 @@ def predict_with_paper(image, paper_size, offset, offset_unit, finger_clearance=
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  if not valid_boxes:
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  logger.warning("No valid objects detected, proceeding with full image")
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- cropped_image = masked_input_image
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  crop_offset = (0, 0)
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  else:
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  # Get highest confidence valid box
@@ -1017,7 +1017,7 @@ def predict_with_paper(image, paper_size, offset, offset_unit, finger_clearance=
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  resized_mask = cv2.resize(objects_mask, (cropped_image.shape[1], cropped_image.shape[0]))
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  else:
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  resized_mask = objects_mask
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- if x_min == 0 and y_min == 0 and cropped_image.shape[:2] == masked_input_image.shape[:2]:
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  full_mask = resized_mask # No cropping occurred, use mask directly
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  else:
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  full_mask[y_min:y_min+resized_mask.shape[0], x_min:x_min+resized_mask.shape[1]] = resized_mask
 
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  if not results or len(results) == 0 or not hasattr(results[0], 'boxes') or len(results[0].boxes) == 0:
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  logger.warning("No objects detected by YOLOv8, proceeding with full image")
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+ cropped_image = image
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  crop_offset = (0, 0)
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  else:
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  boxes = results[0].boxes.xyxy.cpu().numpy()
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  confidences = results[0].boxes.conf.cpu().numpy()
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  # Filter out very large boxes (likely paper/background)
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+ image_area = image.shape[0] * image.shape[1]
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  valid_boxes = []
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  for i, box in enumerate(boxes):
 
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  if not valid_boxes:
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  logger.warning("No valid objects detected, proceeding with full image")
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+ cropped_image = image
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  crop_offset = (0, 0)
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  else:
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  # Get highest confidence valid box
 
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  resized_mask = cv2.resize(objects_mask, (cropped_image.shape[1], cropped_image.shape[0]))
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  else:
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  resized_mask = objects_mask
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+ if x_min == 0 and y_min == 0 and cropped_image.shape[:2] == image.shape[:2]:
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  full_mask = resized_mask # No cropping occurred, use mask directly
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  else:
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  full_mask[y_min:y_min+resized_mask.shape[0], x_min:x_min+resized_mask.shape[1]] = resized_mask