added face_detection.py to web_programming

Author: aneebp

web_programming/face_detection.py

@@ -0,0 +1,76 @@
+import cv2
+import mediapipe as mp
+import time
+
+def resize_image(img, max_width=1000, max_height=800):
+    """Resizes the image while maintaining aspect ratio."""
+    height, width, _ = img.shape
+    scale = min(max_width / width, max_height / height)
+    return cv2.resize(img, None, fx=scale, fy=scale)
+
+def draw_face_detections(img, detections):
+    """Draws bounding boxes around detected faces."""
+    if detections:
+        for detection in detections:
+            # Extract bounding box information
+            bboxC = detection.location_data.relative_bounding_box
+            ih, iw, _ = img.shape
+            bbox = (
+                int(bboxC.xmin * iw), int(bboxC.ymin * ih),
+                int(bboxC.width * iw), int(bboxC.height * ih)
+            )
+            # Draw the bounding box
+            cv2.rectangle(img, bbox, (17, 219, 13), 2)
+
+def main(video_path):
+    # Initialize video capture
+    cap = cv2.VideoCapture(video_path)
+    if not cap.isOpened():
+        print("Error: Unable to open video file")
+        return
+
+    # Mediapipe Face Detection setup
+    mpFaceDetection = mp.solutions.face_detection
+    mpDraw = mp.solutions.drawing_utils
+    faceDetection = mpFaceDetection.FaceDetection(0.75)
+
+    pTime = 0  # Previous time for FPS calculation
+
+    while True:
+        success, img = cap.read()
+        if not success:
+            print("Error: Can't read the video frame.")
+            break
+
+        # Resize image for better performance
+        img = resize_image(img)
+
+        # Convert image to RGB for face detection
+        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        result = faceDetection.process(imgRGB)
+
+        # Draw face detections
+        draw_face_detections(img, result.detections)
+
+        # FPS calculation
+        cTime = time.time()
+        fps = 1 / (cTime - pTime)
+        pTime = cTime
+
+        # Display FPS on the video
+        cv2.putText(img, f"FPS: {int(fps)}", (20, 70), cv2.FONT_HERSHEY_PLAIN, 3, (0, 255, 0), 2)
+
+        # Show the output image
+        cv2.imshow("Face Detection", img)
+
+        # Break the loop on 'q' key press
+        if cv2.waitKey(10) & 0xFF == ord('q'):
+            break
+
+    # Release video capture and destroy all windows
+    cap.release()
+    cv2.destroyAllWindows()
+
+if __name__ == "__main__":
+    video_path = 'path/to/your/video.mp4'  # Update with the actual video path
+    main(video_path)