diff --git a/keypoint_demo.py b/keypoint_demo.py
new file mode 100644
index 0000000..3a9ea2e
--- /dev/null
+++ b/keypoint_demo.py
@@ -0,0 +1,119 @@
+# keypoint_demo.py
+import cv2
+import numpy as np
+from mmpose.apis import MMPoseInferencer
+
+def draw_keypoints(frame, keypoints, keypoint_scores, threshold=0.3):
+    """Draw COCO 17-keypoint skeleton on frame."""
+    
+    # COCO 17 skeleton connections (joint pairs)
+    SKELETON = [
+        (0, 1), (0, 2),           # nose to eyes
+        (1, 3), (2, 4),           # eyes to ears
+        (5, 6),                   # shoulders
+        (5, 7), (7, 9),           # left arm
+        (6, 8), (8, 10),          # right arm
+        (5, 11), (6, 12),         # shoulders to hips
+        (11, 12),                 # hips
+        (11, 13), (13, 15),       # left leg
+        (12, 14), (14, 16),       # right leg
+    ]
+    
+    KEYPOINT_NAMES = [
+        'nose', 'left_eye', 'right_eye', 'left_ear', 'right_ear',
+        'left_shoulder', 'right_shoulder', 'left_elbow', 'right_elbow',
+        'left_wrist', 'right_wrist', 'left_hip', 'right_hip',
+        'left_knee', 'right_knee', 'left_ankle', 'right_ankle'
+    ]
+    
+    h, w = frame.shape[:2]
+    
+    for person_kps, person_scores in zip(keypoints, keypoint_scores):
+        # Draw skeleton lines
+        for (j1, j2) in SKELETON:
+            if person_scores[j1] > threshold and person_scores[j2] > threshold:
+                pt1 = (int(person_kps[j1][0]), int(person_kps[j1][1]))
+                pt2 = (int(person_kps[j2][0]), int(person_kps[j2][1]))
+                # Clamp to frame bounds
+                if (0 <= pt1[0] < w and 0 <= pt1[1] < h and
+                    0 <= pt2[0] < w and 0 <= pt2[1] < h):
+                    cv2.line(frame, pt1, pt2, (0, 255, 0), 2)
+        
+        # Draw keypoints
+        for idx, (kp, score) in enumerate(zip(person_kps, person_scores)):
+            if score > threshold:
+                x, y = int(kp[0]), int(kp[1])
+                if 0 <= x < w and 0 <= y < h:
+                    # Color by confidence: green=high, yellow=medium
+                    color = (0, 255, 0) if score > 0.7 else (0, 200, 200)
+                    cv2.circle(frame, (x, y), 4, color, -1)
+                    cv2.circle(frame, (x, y), 5, (255, 255, 255), 1)  # white border
+    
+    return frame
+
+
+def main():
+    # Initialize inferencer with RTMPose
+    # det_model: person detector
+    # pose2d: pose estimator
+    inferencer = MMPoseInferencer(
+        pose2d='human',  # uses the built-in alias — downloads everything automatically
+        device='cuda:0'
+    )
+    
+    cap = cv2.VideoCapture(0)  # 0 = default webcam; use 1, 2, etc. for others
+    cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
+    cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
+    
+    print("Press 'q' to quit, 's' to save a frame")
+    
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
+        
+        # Run inference
+        # scope='mmpose' is important to avoid namespace issues
+        result_generator = inferencer(
+            frame,
+            show=False,           # we handle display ourselves
+            return_datasamples=False
+        )
+        results = next(result_generator)
+        
+        # Extract keypoints from results
+        predictions = results.get('predictions', [[]])[0]
+        
+        all_keypoints = []
+        all_scores = []
+        
+        for pred in predictions:
+            kps = pred.get('keypoints', [])
+            scores = pred.get('keypoint_scores', [])
+            if len(kps) > 0:
+                all_keypoints.append(np.array(kps))
+                all_scores.append(np.array(scores))
+        
+        # Draw on frame
+        if all_keypoints:
+            frame = draw_keypoints(frame, all_keypoints, all_scores)
+        
+        # Show FPS
+        cv2.putText(frame, f'Subjects: {len(all_keypoints)}', 
+                    (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), 2)
+        
+        cv2.imshow('MMPose RTMPose Keypoints', frame)
+        
+        key = cv2.waitKey(1) & 0xFF
+        if key == ord('q'):
+            break
+        elif key == ord('s'):
+            cv2.imwrite('keypoint_capture.jpg', frame)
+            print("Frame saved.")
+    
+    cap.release()
+    cv2.destroyAllWindows()
+
+
+if __name__ == '__main__':
+    main()
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