ajout

analyse_video.py

@@ -27,3 +27,60 @@ def detecter_visage_principal(detections, frame_w, frame_h):
         "height": int(bbox.height * frame_h),
         "score": round(best.score[0], 3)
     }
+
+
+def analyser_video(chemin_video, dossier_sortie="output"):
+    os.makedirs(dossier_sortie, exist_ok=True)
+
+    cap, fps = charger_video(chemin_video)
+    frame_w = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    frame_h = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+
+    detector = mp.solutions.face_detection.FaceDetection(min_detection_confidence=0.5)
+
+    frames_data = []
+    frame_idx = 0
+
+    print("Analyse en cours...")
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
+
+        timestamp = round(frame_idx / fps, 4)
+        frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        results = detector.process(frame_rgb)
+
+        bbox = detecter_visage_principal(
+            results.detections if results.detections else [],
+            frame_w, frame_h
+        )
+
+        frames_data.append({
+            "frame": frame_idx,
+            "timestamp": timestamp,
+            "face_detected": bbox is not None,
+            "bbox": bbox
+        })
+
+        frame_idx += 1
+        if frame_idx % 100 == 0:
+            print(f"  {frame_idx} frames traitées...")
+
+    cap.release()
+    detector.close()
+
+    nb_detected = sum(1 for f in frames_data if f["face_detected"])
+    print(f"Terminé : {frame_idx} frames, visage détecté sur {nb_detected} ({100 * nb_detected // frame_idx}%)")
+
+    output_path = os.path.join(dossier_sortie, "detection_visage.json")
+    with open(output_path, "w") as f:
+        json.dump({"fps": fps, "frames": frames_data}, f, indent=2)
+
+    print(f"Résultats sauvegardés : {output_path}")
+    return frames_data, fps
+
+
+if __name__ == "__main__":
+    chemin = sys.argv[1] if len(sys.argv) > 1 else "test.mp4"
+    analyser_video(chemin)