new return

main.py

@@ -20,7 +20,7 @@ import cv2
 
 print("[INFO]: Imported modules!")
 human = MMPoseInferencer("human")
-hand = MMPoseInferencer("hand")
+hand = MMPoseInferencer("hand", kpt_thr=0.15) #kpt_thr (float) – The threshold to visualize the keypoints. Defaults to 0.3
 human3d = MMPoseInferencer(pose3d="human3d")
 track_model = YOLO('yolov8n.pt')  # Load an official Detect model
 
@@ -103,21 +103,22 @@ def infer(video, check):
 
         if i == "Detect and track":
             #continue
-            out_file = show_tracking(video, vis_out_dir, inferencer)
+            [out_file] = show_tracking(video, vis_out_dir, inferencer)
 
         else:
             out_file = poses(inferencer, video, vis_out_dir)                                                                                                                                                                                                    
-
-        print(out_file)
+        
         out_files.extend(out_file)
         print(out_files)
 
-    return "track.mp4", out_files[0], out_files[1], out_files[2] # out_files[3]
+    return "track.mp4", out_files[1], out_files[2], out_files[3] # out_files[3]
 
 def run():
     #https://github.com/open-mmlab/mmpose/blob/main/docs/en/user_guides/inference.md
     check_web =  gr.CheckboxGroup(choices = ["Detect and track", "Estimate human 2d poses", "Estimate human 2d hand poses", "Estimate human 3d poses"], label="Methods", type="value", info="Select the model(s) you want")
     check_file = gr.CheckboxGroup(choices = ["Detect and track", "Estimate human 2d poses", "Estimate human 2d hand poses", "Estimate human 3d poses"], label="Methods", type="value", info="Select the model(s) you want")
+    
+    # Insert slider with kpt_thr
 
     webcam = gr.Interface(
         fn=infer,