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Dense-Captioning-Platform

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hanszhu commited on about 1 month ago

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d1c88af

1 Parent(s): 61e2e2c

perf(medsam): reduce fallback candidate boxes to 8

Files changed (1) hide show

app.py CHANGED Viewed

@@ -727,7 +727,7 @@ def analyze_with_medsam(base_result, image):
                     masks_for_overlay.append({"mask": seg_u8})
             else:
                 # Fallback: derive candidate boxes and run MedSAM per box
-                cand_bboxes = _find_topk_foreground_bboxes(pil_img, max_regions=12, min_area=200)
                 for bbox in cand_bboxes:
                     m = _medsam.segment_with_box(bbox)
                     if m is None or not isinstance(m.get('mask'), np.ndarray):

                     masks_for_overlay.append({"mask": seg_u8})
             else:
                 # Fallback: derive candidate boxes and run MedSAM per box
+                cand_bboxes = _find_topk_foreground_bboxes(pil_img, max_regions=8, min_area=200)
                 for bbox in cand_bboxes:
                     m = _medsam.segment_with_box(bbox)
                     if m is None or not isinstance(m.get('mask'), np.ndarray):