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Solved error in FastSAMPredictor.postprocess method #251

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Solved error in FastSAMPredictor.postprocess method #251

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3cb96ea
Returning the indices sorted by IoU in descending order
javierganan99 Sep 16, 2024
9e9899d
Taking the first IoU index to avoid Exception
javierganan99 Sep 16, 2024
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1 change: 1 addition & 0 deletions fastsam/predict.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,7 @@ def postprocess(self, preds, img, orig_imgs):
full_box = full_box.view(1, -1)
critical_iou_index = bbox_iou(full_box[0][:4], p[0][:, :4], iou_thres=0.9, image_shape=img.shape[2:])
if critical_iou_index.numel() != 0:
critical_iou_index = critical_iou_index[:1]
full_box[0][4] = p[0][critical_iou_index][:,4]
full_box[0][6:] = p[0][critical_iou_index][:,6:]
p[0][critical_iou_index] = full_box
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5 changes: 3 additions & 2 deletions fastsam/utils.py
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Expand Up @@ -44,7 +44,7 @@ def bbox_iou(box1, boxes, iou_thres=0.9, image_shape=(640, 640), raw_output=Fals
box1: (4, )
boxes: (n, 4)
Returns:
high_iou_indices: Indices of boxes with IoU > thres
high_iou_indices: Indices of boxes with IoU > thres sorted in descending order
'''
boxes = adjust_bboxes_to_image_border(boxes, image_shape)
# obtain coordinates for intersections
Expand Down Expand Up @@ -72,8 +72,9 @@ def bbox_iou(box1, boxes, iou_thres=0.9, image_shape=(640, 640), raw_output=Fals

# get indices of boxes with IoU > thres
high_iou_indices = torch.nonzero(iou > iou_thres).flatten()
sorted_high_iou_indices = high_iou_indices[torch.argsort(iou[high_iou_indices], descending=True)]

return high_iou_indices
return sorted_high_iou_indices


def image_to_np_ndarray(image):
Expand Down