test download

app.py

@@ -193,10 +193,10 @@ def predict_pipeline(img_input,
     ## Get DLC model and labels as strings   
     # TODO: make a dict as for megadetector
     # pdb.set_trace()
-    #path_to_DLCmodel = DLC_models[dlc_model_input_str]
-    #pose_cfg_path = os.path.join(path_to_DLCmodel,'pose_cfg.yaml')        
-    path_to_DLCmodel = DownloadModel(dlc_model_input_str, './model/')
-    pose_cfg_path = './model/pose_cfg.yaml'          
+    path_to_DLCmodel = DLC_models[dlc_model_input_str]
+    pose_cfg_path = os.path.join(path_to_DLCmodel,'pose_cfg.yaml')        
+    #path_to_DLCmodel = DownloadModel(dlc_model_input_str, './model/')
+    #pose_cfg_path = './model/pose_cfg.yaml'          
     # extract map label ids to strings
     # pose_cfg_dict['all_joints'] is a list of one-element lists,
     with open(pose_cfg_path, "r") as stream: