Update app.py

app.py

@@ -1,38 +1,77 @@
-import cv2
-import streamlit as st
-from cvzone.PoseModule import PoseDetector
-
-st.title("Real-Time Pose Detection")
+#!/usr/bin/env python
 
-detector = PoseDetector()
+from __future__ import annotations
+import cv2
+import gradio as gr
+import mediapipe as mp
+import numpy as np
 
-run = st.checkbox('Run Webcam')
+mp_drawing = mp.solutions.drawing_utils
+mp_drawing_styles = mp.solutions.drawing_styles
+mp_pose = mp.solutions.pose
 
-if run:
-    cap = cv2.VideoCapture(0)
-    stframe = st.empty()
+TITLE = "Real-Time Pose Detection"
+DESCRIPTION = "Pose detection using webcam input."
 
-    while True:
+def run_webcam(
+    model_complexity: int,
+    enable_segmentation: bool,
+    min_detection_confidence: float,
+    background_color: str,
+) -> np.ndarray:
+    cap = cv2.VideoCapture(0)  # Open the webcam
+    with mp_pose.Pose(
+        static_image_mode=False,
+        model_complexity=model_complexity,
+        enable_segmentation=enable_segmentation,
+        min_detection_confidence=min_detection_confidence,
+    ) as pose:
         ret, frame = cap.read()
         if not ret:
-            st.error("Failed to capture video")
-            break
+            return None  # Return None if the webcam fails to capture
+        
+        frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        results = pose.process(frame_rgb)
+        
+        res = frame_rgb.copy()
+        if enable_segmentation and results.segmentation_mask is not None:
+            if background_color == "white":
+                bg_color = (255, 255, 255)
+            elif background_color == "black":
+                bg_color = (0, 0, 0)
+            elif background_color == "green":
+                bg_color = (0, 255, 0)
+            else:
+                raise ValueError("Unsupported background color")
+            
+            res[results.segmentation_mask <= 0.1] = bg_color
 
-        frame = cv2.flip(frame, 1)
-        frame = detector.findPose(frame)
-        lmList, bboxInfo = detector.findPosition(frame, draw=False)
+        mp_drawing.draw_landmarks(
+            res,
+            results.pose_landmarks,
+            mp_pose.POSE_CONNECTIONS,
+            landmark_drawing_spec=mp_drawing_styles.get_default_pose_landmarks_style(),
+        )
 
-        if lmList:
-            RBack_angle, frame = detector.findAngle(lmList[11][0:2],
-                                                   lmList[23][0:2],
-                                                   lmList[25][0:2],
-                                                   img=frame,
-                                                   color=(0, 0, 255),
-                                                   scale=1)
+        cap.release()
+        return cv2.cvtColor(res, cv2.COLOR_RGB2BGR)  # Convert back to BGR for display
 
-        stframe.image(frame, channels='BGR')
+model_complexities = list(range(3))
+background_colors = ["white", "black", "green"]
 
-        if st.button('Stop'):
-            break
+demo = gr.Interface(
+    fn=run_webcam,
+    inputs=[
+        gr.Radio(label="Model Complexity", choices=model_complexities, type="index", value=model_complexities[1]),
+        gr.Checkbox(label="Enable Segmentation", value=True),
+        gr.Slider(label="Minimum Detection Confidence", minimum=0, maximum=1, step=0.05, value=0.5),
+        gr.Radio(label="Background Color", choices=background_colors, type="value", value=background_colors[0]),
+    ],
+    outputs=gr.Image(label="Output"),
+    title=TITLE,
+    description=DESCRIPTION,
+    live=True  # Enable live updates for webcam
+)
 
-    cap.release()
+if __name__ == "__main__":
+    demo.launch()