Feature/detection

web_programming/face_detection.py

@@ -0,0 +1,84 @@
+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
+            bbox = detection.location_data.relative_bounding_box
+            ih, iw, _ = img.shape
+            box = (
+                int(bbox.xmin * iw),
+                int(bbox.ymin * ih),
+                int(bbox.width * iw),
+                int(bbox.height * ih),
+            )
+            # Draw the bounding box
+            cv2.rectangle(img, box, (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
+    mp_face_detection = mp.solutions.face_detection
+    mp_draw = mp.solutions.drawing_utils
+    face_detection = mp_face_detection.FaceDetection(0.75)
+
+    prev_time = 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
+        img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        result = face_detection.process(img_rgb)
+
+        # Draw face detections
+        draw_face_detections(img, result.detections)
+
+        # FPS calculation
+        current_time = time.time()
+        fps = 1 / (current_time - prev_time)
+        prev_time = current_time
+
+        # 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)