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68 lines
2.5 KiB
68 lines
2.5 KiB
import cv2
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import mediapipe as mp
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# Tasks APIの正しいインポートパス
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from mediapipe.tasks import python
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from mediapipe.tasks.python import vision
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# 1. クラスのセットアップ (正しいパスから取得)
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BaseOptions = python.BaseOptions
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FaceDetector = vision.FaceDetector
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FaceDetectorOptions = vision.FaceDetectorOptions
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VisionRunningMode = vision.RunningMode
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# 2. 顔検出器の設定
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options = FaceDetectorOptions(
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base_options=BaseOptions(model_asset_path='blaze_face_short_range.tflite'),
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running_mode=VisionRunningMode.VIDEO
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)
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# Webカメラのキャプチャを開始 (デフォルトカメラは0)
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cap = cv2.VideoCapture(0)
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# FaceDetectorのインスタンスを生成
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with FaceDetector.create_from_options(options) as detector:
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while cap.isOpened():
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success, frame = cap.read()
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if not success:
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print("Webカメラからの映像を取得できませんでした。")
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break
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# OpenCVのBGR画像をRGBに変換
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rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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# タイムスタンプ（ミリ秒）を取得
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frame_timestamp_ms = int(cap.get(cv2.CAP_PROP_POS_MSEC))
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# 3. MediaPipe用のImageオブジェクトを作成
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mp_image = mp.Image(image_format=mp.ImageFormat.SRGB, data=rgb_frame)
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# 4. 検出の実行
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detection_result = detector.detect_for_video(mp_image, frame_timestamp_ms)
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# 5. 検出結果の描画
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if detection_result.detections:
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for detection in detection_result.detections:
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bbox = detection.bounding_box
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# 座標はピクセル単位で取得
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start_point = (bbox.origin_x, bbox.origin_y)
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end_point = (bbox.origin_x + bbox.width, bbox.origin_y + bbox.height)
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# 顔を囲む枠を描画 (緑色, 太さ2)
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cv2.rectangle(frame, start_point, end_point, (0, 255, 0), 2)
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# スコア（信頼度）の描画
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if detection.categories:
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score = detection.categories[0].score
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cv2.putText(frame, f"Face: {score:.2f}", (bbox.origin_x, bbox.origin_y - 10),
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cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
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# 結果を画面に表示
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cv2.imshow('MediaPipe Tasks Face Detection', frame)
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# 'q' キーを押すとループを抜ける
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break
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cap.release()
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cv2.destroyAllWindows() |