{"id":1556,"date":"2025-07-25T10:25:06","date_gmt":"2025-07-25T01:25:06","guid":{"rendered":"https:\/\/beeknowledge.co.jp\/?p=1556"},"modified":"2025-07-25T10:25:07","modified_gmt":"2025-07-25T01:25:07","slug":"python-x-mediapipe%e3%81%a7%e6%98%a0%e5%83%8f%e3%81%ae%e3%83%97%e3%83%a9%e3%82%a4%e3%83%90%e3%82%b7%e3%83%bc%e5%af%be%e7%ad%96%ef%bc%9a%e9%a1%94%e6%a4%9c%e5%87%ba%ef%bc%86%e3%83%a2%e3%82%b6","status":"publish","type":"post","link":"https:\/\/beeknowledge.co.jp\/?p=1556","title":{"rendered":"Python \u00d7 MediaPipe\u3067\u6620\u50cf\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u5bfe\u7b56\uff1a\u9854\u691c\u51fa\uff06\u30e2\u30b6\u30a4\u30af\u51e6\u7406\u306e\u5b9f\u8df5"},"content":{"rendered":"<div class=\"veu_autoEyeCatchBox\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"1024\" src=\"https:\/\/beeknowledge.co.jp\/wp-content\/uploads\/2025\/07\/0023.jpg\" class=\"attachment-large size-large wp-post-image\" alt=\"\" srcset=\"https:\/\/beeknowledge.co.jp\/wp-content\/uploads\/2025\/07\/0023.jpg 1024w, https:\/\/beeknowledge.co.jp\/wp-content\/uploads\/2025\/07\/0023-300x300.jpg 300w, https:\/\/beeknowledge.co.jp\/wp-content\/uploads\/2025\/07\/0023-150x150.jpg 150w, https:\/\/beeknowledge.co.jp\/wp-content\/uploads\/2025\/07\/0023-768x768.jpg 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/div>\n<!DOCTYPE html>\n<html lang=\"ja\">\n<head>\n  <meta charset=\"UTF-8\">\n  <title>Python \u00d7 MediaPipe\u3067\u6620\u50cf\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u5bfe\u7b56\uff1a\u9854\u691c\u51fa\uff06\u30e2\u30b6\u30a4\u30af\u51e6\u7406\u306e\u5b9f\u8df5<\/title>\n  <style>\n    body { font-family: \"Segoe UI\", \"Hiragino Kaku Gothic ProN\", Meiryo, sans-serif; line-height: 1.8; padding: 2em; background: #f9f9f9; color: #333; }\n    h1, h2, h3 { color: #2c3e50; }\n    pre { background: #eee; padding: 1em; overflow-x: auto; }\n    code { font-family: Consolas, monospace; }\n  <\/style>\n<\/head>\n<body>\n\n\n\n<p>\u8fd1\u5e74\u3001\u500b\u4eba\u60c5\u5831\u3084\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u306e\u4fdd\u8b77\u304c\u5f37\u304f\u6c42\u3081\u3089\u308c\u308b\u3088\u3046\u306b\u306a\u308a\u307e\u3057\u305f\u3002\u3068\u308a\u308f\u3051\u9632\u72af\u30ab\u30e1\u30e9\u3084\u30c9\u30ed\u30fc\u30f3\u3001\u696d\u52d9\u8a18\u9332\u7528\u306e\u6620\u50cf\u30c7\u30fc\u30bf\u306b\u304a\u3044\u3066\u300c\u4eba\u306e\u9854\u300d\u304c\u305d\u306e\u307e\u307e\u6620\u308a\u8fbc\u3080\u3053\u3068\u306f\u3001\u500b\u4eba\u8b58\u5225\u306b\u3064\u306a\u304c\u308b\u30ea\u30b9\u30af\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n<p>\u3053\u306e\u30da\u30fc\u30b8\u3067\u306f\u3001Google \u306e <strong>MediaPipe<\/strong> \u3092\u4f7f\u3063\u3066\u300c\u52d5\u753b\u5185\u306e\u9854\u3092\u81ea\u52d5\u7684\u306b\u691c\u51fa\u3057\u3001\u30e2\u30b6\u30a4\u30af\u51e6\u7406\u3092\u304b\u3051\u308b\u300dPython\u30b9\u30af\u30ea\u30d7\u30c8\u306e\u4ed5\u7d44\u307f\u3092\u3001\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u5b66\u7fd2\u8005\u5411\u3051\u306b\u4e01\u5be7\u306b\u89e3\u8aac\u3057\u307e\u3059\u3002<\/p>\n\n<hr>\n\n<h2>1. \u3053\u306e\u30b9\u30af\u30ea\u30d7\u30c8\u306e\u76ee\u7684<\/h2>\n\n<p>\u672c\u30b9\u30af\u30ea\u30d7\u30c8\u306e\u76ee\u7684\u306f\u3001\u52d5\u753b\u30d5\u30a1\u30a4\u30eb\u306b\u542b\u307e\u308c\u308b\u4eba\u7269\u306e\u9854\u3092\u81ea\u52d5\u7684\u306b\u691c\u51fa\u3057\u3001<strong>\u30e2\u30b6\u30a4\u30af\u52a0\u5de5<\/strong>\u3092\u65bd\u3059\u3053\u3068\u3067\u500b\u4eba\u306e\u7279\u5b9a\u3092\u9632\u3050\u3053\u3068\u306b\u3042\u308a\u307e\u3059\u3002<\/p>\n\n<ul>\n  <li>\u5165\u529b\uff1a\u6620\u50cf\u30d5\u30a1\u30a4\u30eb\uff08mp4, avi, mov, mkv\uff09<\/li>\n  <li>\u51e6\u7406\uff1aMediaPipe\u3067\u9854\u691c\u51fa \u2192 \u691c\u51fa\u7bc4\u56f2\u3092\u30e2\u30b6\u30a4\u30af\u5316<\/li>\n  <li>\u51fa\u529b\uff1a\u9854\u306b\u30e2\u30b6\u30a4\u30af\u304c\u304b\u304b\u3063\u305f\u518d\u751f\u53ef\u80fd\u306a\u52d5\u753b<\/li>\n<\/ul>\n\n<p>\u3053\u306e\u51e6\u7406\u306f\u3001\u6620\u50cf\u306e\u7b2c\u4e09\u8005\u63d0\u4f9b\u30fb\u5171\u6709\u30fb\u516c\u958b\u3092\u884c\u3046\u969b\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u5bfe\u7b56\u3068\u3057\u3066\u975e\u5e38\u306b\u6709\u52b9\u3067\u3059\u3002<\/p>\n\n<hr>\n\n<h2>2. \u4f7f\u7528\u30e9\u30a4\u30d6\u30e9\u30ea<\/h2>\n\n<p>Python\u3068\u4ee5\u4e0b\u306e\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/p>\n\n<ul>\n  <li><code>opencv-python<\/code>\uff1a\u6620\u50cf\u306e\u8aad\u307f\u66f8\u304d\u30fb\u753b\u50cf\u51e6\u7406<\/li>\n  <li><code>mediapipe<\/code>\uff1a\u9854\u691c\u51fa\uff08AI\u30e2\u30c7\u30eb\u5185\u8535\uff09<\/li>\n  <li><code>os<\/code>\uff1a\u30d5\u30a9\u30eb\u30c0\u64cd\u4f5c<\/li>\n<\/ul>\n\n<pre><code>pip install opencv-python mediapipe<\/code><\/pre>\n\n<hr>\n\n<h2>3. \u30bd\u30fc\u30b9\u30b3\u30fc\u30c9\u69cb\u6210<\/h2>\n\n<p>\u672c\u30b9\u30af\u30ea\u30d7\u30c8\u306e\u5168\u4f53\u69cb\u9020\u306f\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u306a\u3063\u3066\u3044\u307e\u3059\u3002<\/p>\n\n<pre><code>\u251c\u2500 input_videos\/        \u2190 \u5165\u529b\u52d5\u753b\u30d5\u30a9\u30eb\u30c0\n\u251c\u2500 output_videos\/       \u2190 \u51e6\u7406\u6e08\u307f\u52d5\u753b\u306e\u51fa\u529b\u5148\n\u251c\u2500 script.py            \u2190 \u672c\u4f53\u30b9\u30af\u30ea\u30d7\u30c8\n<\/code><\/pre>\n\n<hr>\n\n<h2>4. \u30d7\u30ed\u30b0\u30e9\u30e0\u89e3\u8aac\uff08\u91cd\u8981\u95a2\u6570\uff09<\/h2>\n\n<h3>4.1 \u9854\u691c\u51fa\u95a2\u6570 detect_faces_mp<\/h3>\n\n<p>MediaPipe\u3092\u7528\u3044\u3066\u30011\u679a\u306e\u30d5\u30ec\u30fc\u30e0\u5185\u304b\u3089\u9854\u306e\u4f4d\u7f6e\u3092\u691c\u51fa\u3059\u308b\u95a2\u6570\u3067\u3059\u3002<\/p>\n\n<pre><code>def detect_faces_mp(frame):\n    h, w = frame.shape[:2]\n    rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\n    results = face_detector.process(rgb)\n<\/code><\/pre>\n\n<p>MediaPipe\u3067\u306f\u9854\u306e\u4f4d\u7f6e\u3092\u300c\u76f8\u5bfe\u5ea7\u6a19\uff080.0\uff5e1.0\uff09\u300d\u3067\u8fd4\u3059\u305f\u3081\u3001\u30d4\u30af\u30bb\u30eb\u5358\u4f4d\u306b\u5909\u63db\u3057\u307e\u3059\u3002<\/p>\n\n<pre><code>\n    x1 = int(bbox.xmin * w)\n    y1 = int(bbox.ymin * h)\n    bw = int(bbox.width * w)\n    bh = int(bbox.height * h)\n<\/code><\/pre>\n\n<p>\u307e\u305f\u3001\u9854\u691c\u51fa\u304c\u30d5\u30ec\u30fc\u30e0\u5916\u306b\u306f\u307f\u51fa\u3055\u306a\u3044\u3088\u3046\u30af\u30ea\u30c3\u30d7\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n<hr>\n\n<h3>4.2 \u30e2\u30b6\u30a4\u30af\u51e6\u7406 apply_mosaic<\/h3>\n\n<p>\u691c\u51fa\u3055\u308c\u305f\u9854\u306e\u9818\u57df\u306b\u300c\u30d4\u30af\u30bb\u30eb\u7e2e\u5c0f \u2192 \u62e1\u5927\u300d\u306b\u3088\u308b\u30e2\u30b6\u30a4\u30af\u3092\u304b\u3051\u307e\u3059\u3002<\/p>\n\n<pre><code>def apply_mosaic(face_roi, mosaic_rate=0.02):\n    small = cv2.resize(face_roi, (small_w, small_h), interpolation=cv2.INTER_NEAREST)\n    return cv2.resize(small, (w, h), interpolation=cv2.INTER_NEAREST)\n<\/code><\/pre>\n\n<p><strong>mosaic_rate<\/strong> \u3092\u5c0f\u3055\u304f\u3059\u308b\u307b\u3069\u3001\u30e2\u30b6\u30a4\u30af\u304c\u7c97\u304f\u306a\u308a\u307e\u3059\uff08\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u5f37\u5ea6UP\uff09\u3002<\/p>\n\n<hr>\n\n<h3>4.3 \u30e1\u30a4\u30f3\u51e6\u7406 loop\uff08process_video\uff09<\/h3>\n\n<p>\u52d5\u753b\u30d5\u30a1\u30a4\u30eb\u30921\u30d5\u30ec\u30fc\u30e0\u305a\u3064\u8aad\u307f\u8fbc\u307f\u3001\u9854\u691c\u51fa\u2192\u30e2\u30b6\u30a4\u30af\u2192\u66f8\u304d\u51fa\u3057\u3092\u7e70\u308a\u8fd4\u3057\u307e\u3059\u3002<\/p>\n\n<pre><code>\nwhile True:\n    ret, frame = cap.read()\n    if not ret:\n        break\n    faces = detect_faces_mp(frame)\n    for (x, y, w, h) in faces:\n        roi = frame[y:y+h, x:x+w]\n        frame[y:y+h, x:x+w] = apply_mosaic(roi)\n    out.write(frame)\n<\/code><\/pre>\n\n<p>\u51e6\u7406\u9032\u6357\u304c\u308f\u304b\u308b\u3088\u3046\u306b\u300150\u30d5\u30ec\u30fc\u30e0\u3054\u3068\u306b\u30ed\u30b0\u8868\u793a\u3082\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n<hr>\n\n<h3>4.4 \u30d5\u30a9\u30eb\u30c0\u4e00\u62ec\u51e6\u7406\uff08main\uff09<\/h3>\n\n<p><code>input_videos<\/code>\u30d5\u30a9\u30eb\u30c0\u5185\u306e\u52d5\u753b\u30d5\u30a1\u30a4\u30eb\u3092\u4e00\u62ec\u3067\u51e6\u7406\u3057\u3066\u3001\u51fa\u529b\u3092<code>output_videos<\/code>\u30d5\u30a9\u30eb\u30c0\u306b\u4fdd\u5b58\u3057\u307e\u3059\u3002<\/p>\n\n<pre><code>\nfor fname in os.listdir(input_folder):\n    if ext.lower() in {\\\".mp4\\\", \\\".avi\\\", \\\".mov\\\", \\\".mkv\\\"}:\n        process_video(in_path, out_path)\n<\/code><\/pre>\n\n<hr>\n\n<h2>5. \u30e2\u30c7\u30eb\u9078\u629e\u3068\u691c\u51fa\u6027\u80fd\u306e\u8abf\u6574<\/h2>\n\n<p><code>model_selection<\/code> \u306b\u306f\u4ee5\u4e0b\u306e2\u7a2e\u985e\u304c\u3042\u308a\u307e\u3059\uff1a<\/p>\n\n<ul>\n  <li><code>0<\/code>: \u9ad8\u7cbe\u5ea6\uff08\u30de\u30b9\u30af\u9854\u306b\u3082\u3084\u3084\u5f37\u3044\uff09<\/li>\n  <li><code>1<\/code>: \u9ad8\u901f\uff08\u51e6\u7406\u304c\u8efd\u3044\u304c\u7cbe\u5ea6\u306f\u3084\u3084\u843d\u3061\u308b\uff09<\/li>\n<\/ul>\n\n<p>\u73fe\u5b9f\u7684\u306a\u904b\u7528\u3067\u306f <code>model_selection=1<\/code> \u3092\u30d9\u30fc\u30b9\u306b\u3057\u3064\u3064\u3001\u7cbe\u5ea6\u304c\u5fc5\u8981\u306a\u74b0\u5883\u3067\u306f <code>0<\/code> \u306b\u5207\u308a\u66ff\u3048\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n<p>\u307e\u305f\u3001\u5c0f\u3055\u306a\u9854\u304c\u691c\u51fa\u3055\u308c\u306a\u3044\u3068\u304d\u306f\u3001\u30d5\u30ec\u30fc\u30e0\u3092\u62e1\u5927\u3057\u3066\u691c\u51fa\u3059\u308b\u300c\u30de\u30eb\u30c1\u30b9\u30b1\u30fc\u30eb\u691c\u51fa\u300d\u306a\u3069\u306e\u30c6\u30af\u30cb\u30c3\u30af\u3082\u6709\u52b9\u3067\u3059\uff08\u51e6\u7406\u6642\u9593\u306f\u5897\u3048\u307e\u3059\uff09\u3002<\/p>\n\n<hr>\n\n<h2>6. \u5fdc\u7528\u3068\u4eca\u5f8c\u306e\u5c55\u671b<\/h2>\n\n<p>\u3053\u306e\u30b9\u30af\u30ea\u30d7\u30c8\u306f\u57fa\u672c\u7684\u306a\u30e2\u30b6\u30a4\u30af\u51e6\u7406\u3092\u884c\u3044\u307e\u3059\u304c\u3001\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u5fdc\u7528\u304c\u53ef\u80fd\u3067\u3059\uff1a<\/p>\n\n<ul>\n  <li>\u97f3\u58f0\u4ed8\u304d\u52d5\u753b\u306e\u51e6\u7406\uff08\u97f3\u58f0\u306f\u305d\u306e\u307e\u307e\uff09<\/li>\n  <li>\u30c8\u30e9\u30c3\u30ad\u30f3\u30b0\u3067\u691c\u51fa\u6f0f\u308c\u88dc\u5b8c\uff08\u8ffd\u8de1\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u4f75\u7528\uff09<\/li>\n  <li>\u9759\u6b62\u753b\u3078\u306e\u5fdc\u7528\uff08\u30b5\u30e0\u30cd\u30a4\u30eb\u81ea\u52d5\u30e2\u30b6\u30a4\u30af\uff09<\/li>\n  <li>\u30de\u30b9\u30af\u9854\u306b\u3082\u5f37\u3044\u9854\u691c\u51fa\uff08RetinaFace, MTCNN\u306a\u3069\u3078\u306e\u5207\u308a\u66ff\u3048\uff09<\/li>\n<\/ul>\n\n<p>\u502b\u7406\u7684\u306a\u89b3\u70b9\u3067\u3082\u3001\u300cAI\u3092\u4f7f\u3063\u3066\u4f55\u3092\u5b88\u308b\u304b\u300d\u3068\u3044\u3046\u8996\u70b9\u306f\u975e\u5e38\u306b\u91cd\u8981\u3067\u3059\u3002\u5b89\u6613\u306b\u9854\u3092\u6b8b\u3059\u306e\u3067\u306f\u306a\u304f\u3001<strong>\u610f\u8b58\u7684\u306b\u4fdd\u8b77\u3059\u308b\u6587\u5316<\/strong>\u306e\u4e00\u7aef\u3068\u3057\u3066\u3001\u3053\u3046\u3057\u305f\u6280\u8853\u3092\u6d3b\u7528\u3057\u3066\u3044\u304d\u307e\u3057\u3087\u3046\u3002<\/p>\n\n<hr>\n\n<h2>7. \u304a\u308f\u308a\u306b<\/h2>\n\n<p>\u672c\u8a18\u4e8b\u3067\u306f Python \u3068 MediaPipe 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