Update app.py

app.py

@@ -126,9 +126,9 @@ def inference(image_url, image, min_score):
     # )
     # v = v.draw_instance_predictions(outputs["instances"].to("cpu"))
     # cv2_imshow(v.get_image()[:, :, ::-1])
-    print(outputs["instances"])
+    # print(outputs["instances"])
     masks = np.asarray(outputs["instances"].pred_masks.to("cpu"))
-    bbox = np.asarray(outputs["instances"].pred_boxes.to("cpu"))
+    # bbox = np.asarray(outputs["instances"].pred_boxes.to("cpu"))
     
     # Pick an item to mask
     # img=v.get_image()
@@ -137,7 +137,7 @@ def inference(image_url, image, min_score):
     measurements = {}
     
     for ind,item_mask in enumerate(masks):
-      box=bbox[ind]
+      # box=bbox[ind]
       # Get the true bounding box of the mask (not the same as the bbox prediction)
       segmentation = np.where(item_mask == True)
       x_min = int(np.min(segmentation[1]))