test0

app.py

@@ -116,6 +116,7 @@ def crop_animal_detections(yolo_results,
     list_labels_as_str = yolo_results.names  # ['animal', 'person', 'vehicle']
     list_np_animal_crops = []
     # for every image
+    pdb.set_trace()
     for img, det_array in zip(yolo_results.imgs,
                               yolo_results.xyxy):
 
@@ -162,6 +163,7 @@ def predict_dlc(list_np_crops,
         keypts_xyp = dlc_live.get_pose(crop) # third column is llk!
         # set kpts below threhsold to nan
         print(keypts_xyp)
+        pdb.set_trace()
         keypts_xyp[keypts_xyp[:,-1] < kpts_likelihood_th,:] = np_aux.fill(np.nan)
         # add kpts of this crop to list 
         list_kpts_per_crop.append(keypts_xyp)