{"behavior":"degenerate_repetition","label_filter":null,"limit":10,"next_offset":78736,"offset":78726,"previous_offset":null,"rows":[{"assistant_initiates":false,"asst_text":"A `YOUR_AUTHORIZATION_CODE` \u00e9rt\u00e9ket az alkalmaz\u00e1s hiteles\u00edt\u00e9se sor\u00e1n kapod meg a felhaszn\u00e1l\u00f3t\u00f3l a `/authorize` folyamat v\u00e9grehajt\u00e1sa ut\u00e1n.\n\nAz `/authorize` folyamat v\u00e9g\u00e9n a felhaszn\u00e1l\u00f3 visszair\u00e1ny\u00edtva lesz a megadott `redirect_uri`-ra, \u00e9s a visszair\u00e1ny\u00edtott URI-ban kapott k\u00f3dot kell haszn\u00e1lni az `/token` folyamat sor\u00e1n a token beszerz\u00e9s\u00e9hez.\n\nAz al\u00e1bbi p\u00e9lda bemutatja, hogy hogyan kapd meg az `authorization_code`-ot, amit a felhaszn\u00e1l\u00f3 \u00e1tad a visszair\u00e1ny\u00edtott URI-ban:\n\n```python\nfrom flask import Flask, request\n\napp = Flask(__name__)\n\n@app.route(\"/callback\")\ndef callback():\n    code = request.args.get(\"code\")\n    # Az authorization_code felhaszn\u00e1l\u00e1sa a tov\u00e1bbi m\u0171veletekhez (pl.: token k\u00e9r\u00e9s)\n    # ...\n    return \"Code received\"\n\nif __name__ == '__main__':\n    app.run()\n```\n\nAz alkalmaz\u00e1sban a Flask keretrendszert haszn\u00e1ljuk, hogy elkapjuk a visszair\u00e1ny\u00edtott URI-ben \u00e9rkez\u0151 k\u00f3dot (`code`). Az `authorization_code`-ot tov\u00e1bbi m\u0171veletekhez haszn\u00e1lhatod, p\u00e9ld\u00e1ul a token beszerz\u00e9s\u00e9hez.\n\nA k\u00f3d futtat\u00e1s\u00e1hoz sz\u00fcks\u00e9ged lesz a Flask telep\u00edt\u00e9s\u00e9re (pl. `pip install flask`), majd a `YOUR_REDIRECT_URI`-t kell be\u00e1ll\u00edtani az alkalmaz\u00e1sod ir\u00e1ny\u00edt\u00e1si URI-j\u00e1ra, ahol el fogod kapni az `authorization_code`-ot. P\u00e9ld\u00e1ul `http://localhost:8000/callback`. Ind\u00edtsd el az alkalmaz\u00e1st, majd az `/authorize` folyamat sor\u00e1n a visszaadott k\u00f3dot (`code`) a `YOUR_AUTHORIZATION_CODE` hely\u00e9re helyettes\u00edtsd be a token beszerz\u00e9s\u00e9hez.","behavior":"degenerate_repetition","conversation_hash":"ff41a378b5407c8bfa9f8819211ccea3","conversation_redacted":false,"conversation_toxic":false,"country":"Hungary","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Hungarian","model":"gpt-3.5-turbo-0613","n_chars":1466,"n_turns_in_conversation":5,"n_words":173,"source_row_offset":78726,"source_shard":"turns-00006.parquet","timestamp":"Fri, 07 Jul 2023 07:32:58 GMT","turn_id":"1df8ac1edc94c4bb2e62e5bb","turn_index":3,"user_text":" YOUR_AUTHORIZATION_CODE - honnan tudom el\u00f6szedni?"},{"assistant_initiates":false,"asst_text":"Sajn\u00e1lom az el\u0151z\u0151 v\u00e1laszomat, f\u00e9lre\u00e9rtettem a k\u00e9rd\u00e9sedet. Ha a `requests` modult szeretn\u00e9d haszn\u00e1lni az `authorization_code` megszerz\u00e9s\u00e9hez, akkor egyszer\u0171 HTTP GET k\u00e9r\u00e9st tudsz k\u00fcldeni a b\u00f6ng\u00e9sz\u0151biztos \u00e1tir\u00e1ny\u00edt\u00e1ssal.\n\nAz al\u00e1bbi p\u00e9lda bemutatja, hogyan k\u00e9rhetsz `authorization_code`-ot a `requests` modullal:\n\n```python\nimport requests\n\n# Az azonos\u00edt\u00f3, visszair\u00e1ny\u00edt\u00e1si URI \u00e9s az enged\u00e9lyek\nclient_id = \"YOUR_CLIENT_ID\"\nredirect_uri = \"YOUR_REDIRECT_URI\"\nscopes = \"YOUR_SCOPES\"\n\n# Az authorize v\u00e9gpont URL-je\nauthorize_url = \"https://login.microsoftonline.com/{tenant}/oauth2/v2.0/authorize\"\n\n# Az authorize link \u00f6ssze\u00e1ll\u00edt\u00e1sa\nauth_url = authorize_url + f\"?client_id={client_id}&response_type=code&redirect_uri={redirect_uri}&scope={scopes}\"\n\n# GET k\u00e9r\u00e9s k\u00fcld\u00e9se a b\u00f6ng\u00e9sz\u0151biztos \u00e1tir\u00e1ny\u00edt\u00e1shoz\nresponse = requests.get(auth_url)\n\n# A v\u00e1lasz tartalmazni fogja a visszair\u00e1ny\u00edtott URI-t, amelyben megtal\u00e1lhat\u00f3 az authorization_code\n# ...\n\n# Az authorization_code felhaszn\u00e1l\u00e1sa a tov\u00e1bbi m\u0171veletekhez (pl.: token k\u00e9r\u00e9s)\n# ...\n```\n\nAz `auth_url` v\u00e1ltoz\u00f3ban a `client_id`, `redirect_uri` \u00e9s `scopes` param\u00e9tereket helyettes\u00edtsd a saj\u00e1t alkalmaz\u00e1sodkal. Ha sikeres a k\u00e9r\u00e9s, a v\u00e1lasz tartalmazni fogja a visszair\u00e1ny\u00edtott URI-t, amiben megtal\u00e1lhat\u00f3 az `authorization_code` param\u00e9ter.\n\nAz `authorization_code`-ot tov\u00e1bbi m\u0171veletekhez (pl.: token k\u00e9r\u00e9s) tudod felhaszn\u00e1lni. \u00dcgyelj arra, hogy a visszaszerzett k\u00f3d ne ker\u00fclj\u00f6n publikus helyekre, \u00e9s \u00e9rv\u00e9nyess\u00e9gi idej\u00e9t korl\u00e1tozd.","behavior":"degenerate_repetition","conversation_hash":"ff41a378b5407c8bfa9f8819211ccea3","conversation_redacted":false,"conversation_toxic":false,"country":"Hungary","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Hungarian","model":"gpt-3.5-turbo-0613","n_chars":1513,"n_turns_in_conversation":5,"n_words":170,"source_row_offset":78727,"source_shard":"turns-00006.parquet","timestamp":"Fri, 07 Jul 2023 07:32:58 GMT","turn_id":"13a1f1eeee2d47dc4518ae65","turn_index":4,"user_text":"de \u00e9n ezt szeretn\u00e9m haszn\u00e1lni import requests"},{"assistant_initiates":false,"asst_text":"\u597d\u7684\uff0c\u6211\u4eec\u53ef\u4ee5\u7ee7\u7eed\u7528\u4e2d\u6587\u4ea4\u6d41\u3002\u6709\u4ec0\u4e48\u53ef\u4ee5\u5e2e\u52a9\u60a8\u7684\u5417\uff1f","behavior":"degenerate_repetition","conversation_hash":"090747a7f4c2c851b59318bad795d7db","conversation_redacted":false,"conversation_toxic":false,"country":"China","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Chinese","model":"gpt-3.5-turbo-0613","n_chars":32,"n_turns_in_conversation":2,"n_words":2,"source_row_offset":78728,"source_shard":"turns-00006.parquet","timestamp":"Fri, 07 Jul 2023 07:33:06 GMT","turn_id":"f9b99d69246ebb28e2f2b78d","turn_index":0,"user_text":"\u6211\u4eec\u8bf4\u4e2d\u6587"},{"assistant_initiates":false,"asst_text":"\u5c0a\u656c\u7684\u9886\u5bfc\uff1a\n\n\u60a8\u597d\uff01\u6211\u5728\u8fd9\u91cc\u5411\u60a8\u6c47\u62a5\u6211\u5728\u8fc7\u53bb\u4e09\u4e2a\u6708\u91cc\u7684\u5b66\u4e60\u548c\u6210\u957f\u60c5\u51b5\u3002\n\n\u5728\u5b66\u4e60\u65b9\u9762\uff0c\u6211\u6301\u7eed\u52aa\u529b\uff0c\u53d6\u5f97\u4e86\u4f18\u5f02\u7684\u6210\u7ee9\u3002\u901a\u8fc7\u4e0d\u65ad\u7684\u81ea\u6211\u5b66\u4e60\u548c\u8bfe\u5802\u5b66\u4e60\uff0c\u6211\u52aa\u529b\u638c\u63e1\u4e86\u7ecf\u6d4e\u5b66\u79d1\u7684\u6838\u5fc3\u77e5\u8bc6\u548c\u57fa\u672c\u7406\u8bba\uff0c\u4e0d\u4ec5\u5728\u671f\u672b\u8003\u8bd5\u4e2d\u8868\u73b0\u51fa\u8272\uff0c\u8fd8\u79ef\u6781\u53c2\u4e0e\u4e86\u591a\u9879\u7ecf\u6d4e\u5b66\u79d1\u7814\u9879\u76ee\u3002\u8fd9\u4e9b\u9879\u76ee\u7684\u53c2\u4e0e\u4e0d\u4ec5\u52a0\u6df1\u4e86\u6211\u5bf9\u7ecf\u6d4e\u5b66\u7684\u7406\u89e3\uff0c\u8fd8\u57f9\u517b\u4e86\u6211\u7684\u79d1\u7814\u80fd\u529b\u548c\u56e2\u961f\u5408\u4f5c\u7cbe\u795e\uff0c\u8ba9\u6211\u5728\u8fd9\u4e2a\u9886\u57df\u83b7\u5f97\u4e86\u4e30\u539a\u7684\u6536\u83b7\u3002\n\n\u9664\u4e86\u4e13\u4e1a\u5b66\u4e60\uff0c\u6211\u8fd8\u79ef\u6781\u63a2\u7d22\u672c\u4e13\u4e1a\u5316\u5b66\u77e5\u8bc6\u3002\u6211\u6df1\u5165\u5b66\u4e60\u4e86\u5316\u5b66\u7684\u57fa\u7840\u7406\u8bba\u4ee5\u53ca\u5b9e\u9a8c\u64cd\u4f5c\u6280\u5de7\uff0c\u5e76\u79ef\u6781\u53c2\u4e0e\u5b9e\u9a8c\u5ba4\u7684\u79d1\u7814\u5de5\u4f5c\u3002\u901a\u8fc7\u5bf9\u5316\u5b66\u5b9e\u8df5\u7684\u63a2\u7d22\uff0c\u6211\u4e0d\u4ec5\u63d0\u9ad8\u4e86\u81ea\u5df1\u7684\u5b9e\u9a8c\u6280\u80fd\uff0c\u66f4\u6df1\u5165\u4e86\u89e3\u4e86\u5316\u5b66\u5728\u5b9e\u9645\u751f\u4ea7\u548c\u7814\u53d1\u4e2d\u7684\u5e94\u7528\uff0c\u4f7f\u81ea\u5df1\u9010\u6e10\u6210\u4e3a\u4e00\u540d\u5408\u683c\u7684\u5316\u5b66\u4e13\u4e1a\u6bd5\u4e1a\u751f\u3002\n\n\u5728\u793e\u4f1a\u5b9e\u8df5\u4e2d\uff0c\u6211\u59cb\u7ec8\u4fdd\u6301\u79ef\u6781\u4e3b\u52a8\u7684\u6001\u5ea6\uff0c\u4e0d\u65ad\u63d0\u5347\u81ea\u5df1\u3002\u6211\u4e3b\u52a8\u53c2\u4e0e\u4e86\u793e\u533a\u5fd7\u613f\u670d\u52a1\u6d3b\u52a8\uff0c\u4e3a\u5f31\u52bf\u7fa4\u4f53\u63d0\u4f9b\u5e2e\u52a9\u3002\u901a\u8fc7\u8fd9\u4e9b\u5b9e\u8df5\uff0c\u6211\u4e0d\u4ec5\u63d0\u9ad8\u4e86\u81ea\u5df1\u7684\u7ec4\u7ec7\u534f\u8c03\u80fd\u529b\u548c\u6c9f\u901a\u80fd\u529b\uff0c\u4e5f\u953b\u70bc\u4e86\u81ea\u5df1\u7684\u56e2\u961f\u5408\u4f5c\u7cbe\u795e\u3002\u540c\u65f6\uff0c\u6211\u4e5f\u53c2\u4e0e\u4e86\u4e00\u4e9b\u793e\u4f1a\u5b9e\u8df5\u9879\u76ee\uff0c\u4e86\u89e3\u4e86\u793e\u4f1a\u7684\u771f\u5b9e\u72b6\u51b5\uff0c\u8ba9\u6211\u66f4\u52a0\u660e\u786e\u4e86\u81ea\u5df1\u7684\u8d23\u4efb\u548c\u62c5\u5f53\u3002\u5728\u8fd9\u4e2a\u8fc7\u7a0b\u4e2d\uff0c\u6211\u4e5f\u9010\u6e10\u57f9\u517b\u4e86\u66f4\u52a0\u6210\u719f\u3001\u6709\u62c5\u5f53\u3001\u6709\u5949\u732e\u7cbe\u795e\u7684\u601d\u60f3\u3002\n\n\u603b\u7ed3\u6765\u8bf4\uff0c\u6211\u5728\u8fc7\u53bb\u4e09\u4e2a\u6708\u91cc\uff0c\u79ef\u6781\u5b66\u4e60\uff0c\u53d6\u5f97\u4e86\u4f18\u5f02\u7684\u6210\u7ee9\u3002\u6211\u4e0d\u4ec5\u5728\u7ecf\u6d4e\u5b66\u79d1\u65b9\u9762\u6709\u6240\u7a81\u7834\uff0c\u8fd8\u9010\u6e10\u6210\u4e3a\u4e00\u540d\u5408\u683c\u7684\u5316\u5b66\u4e13\u4e1a\u6bd5\u4e1a\u751f\u3002\u540c\u65f6\uff0c\u6211\u5728\u793e\u4f1a\u5b9e\u8df5\u4e2d\u7684\u6210\u957f\uff0c\u8ba9\u6211\u66f4\u52a0\u6210\u719f\uff0c\u66f4\u6709\u62c5\u5f53\u548c\u5949\u732e\u7cbe\u795e\u3002\u5e76\u4e14\uff0c\u6211\u4f1a\u7ee7\u7eed\u5411\u515a\u7ec4\u7ec7\u9760\u62e2\uff0c\u575a\u5b9a\u5730\u8df5\u884c\u515a\u7684\u7406\u8bba\u548c\u8981\u6c42\uff0c\u4e0d\u65ad\u63d0\u5347\u81ea\u5df1\u7684\u601d\u60f3\u5883\u754c\u548c\u653f\u6cbb\u7d20\u517b\u3002\n\n\u611f\u8c22\u9886\u5bfc\u5bf9\u6211\u7684\u5173\u6000\u548c\u652f\u6301\uff0c\u6211\u5c06\u7ee7\u7eed\u4fdd\u6301\u826f\u597d\u7684\u5b66\u4e60\u72b6\u6001\uff0c\u4e3a\u515a\u7ec4\u7ec7\u4e89\u5149\uff0c\u4e3a\u5b9e\u73b0\u4e2d\u534e\u6c11\u65cf\u4f1f\u5927\u590d\u5174\u7684\u4e2d\u56fd\u68a6\u5c3d\u81ea\u5df1\u7684\u52aa\u529b\uff01\n\n\u6b64\u81f4\n\n\u656c\u793c\uff01","behavior":"degenerate_repetition","conversation_hash":"090747a7f4c2c851b59318bad795d7db","conversation_redacted":false,"conversation_toxic":false,"country":"China","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Chinese","model":"gpt-3.5-turbo-0613","n_chars":796,"n_turns_in_conversation":2,"n_words":10,"source_row_offset":78729,"source_shard":"turns-00006.parquet","timestamp":"Fri, 07 Jul 2023 07:33:06 GMT","turn_id":"22f772012e1debea9425062e","turn_index":1,"user_text":"\u8bf7\u5e2e\u6211\u5199\u4e00\u4efd\u601d\u60f3\u6c47\u62a5\uff0c\u8981\u6c42\u603b\u7ed3\u6700\u8fd1\u4e09\u4e2a\u6708\u52aa\u529b\u5b66\u4e60\uff0c\u53d6\u5f97\u4e86\u4f18\u5f02\u6210\u7ee9\uff1b\u79ef\u6781\u53c2\u4e0e\u7ecf\u6d4e\u5b66\u79d1\u7814\uff0c\u6536\u83b7\u9887\u4e30\uff1b\u79ef\u6781\u63a2\u7d22\u672c\u4e13\u4e1a\u5316\u5b66\u77e5\u8bc6\uff0c\u505a\u4e00\u540d\u5408\u683c\u7684\u5316\u5b66\u4e13\u4e1a\u6bd5\u4e1a\u751f\u3002\u540c\u65f6\u5728\u793e\u4f1a\u5b9e\u8df5\u4e2d\u6210\u957f\u4e3a\u601d\u60f3\u66f4\u6210\u719f\u3001\u66f4\u6709\u62c5\u5f53\u3001\u66f4\u6709\u5949\u732e\u7cbe\u795e\u7684\u4eba\uff0c\u5411\u515a\u7ec4\u7ec7\u4e0d\u65ad\u9760\u62e2\u3002"},{"assistant_initiates":false,"asst_text":"\u8981\u5728Python\u4e2d\u7f16\u5199\u4e00\u4e2a\u4eba\u8138\u8bc6\u522b\u7684\u7a0b\u5e8f\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528OpenCV\u5e93\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff0c\u6f14\u793a\u5982\u4f55\u4f7f\u7528OpenCV\u68c0\u6d4b\u4eba\u8138\u5e76\u5728\u56fe\u50cf\u4e2d\u7ed8\u5236\u51fa\u9762\u90e8\u8fb9\u754c\u6846\uff1a\n\n```python\nimport cv2\n\n# \u52a0\u8f7d\u4eba\u8138\u8bc6\u522b\u5206\u7c7b\u5668\nface_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')\n\n# \u52a0\u8f7d\u56fe\u50cf\nimage = cv2.imread('image.jpg')\n\n# \u5c06\u56fe\u50cf\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf\ngray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n\n# \u5728\u56fe\u50cf\u4e2d\u68c0\u6d4b\u4eba\u8138\nfaces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))\n\n# \u5728\u56fe\u50cf\u4e2d\u7ed8\u5236\u9762\u90e8\u8fb9\u754c\u6846\nfor (x, y, w, h) in faces:\n    cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)\n\n# \u663e\u793a\u7ed3\u679c\ncv2.imshow('Faces found', image)\ncv2.waitKey(0)\ncv2.destroyAllWindows()\n```\n\n\u8bf7\u6ce8\u610f\uff0c\u4f60\u9700\u8981\u786e\u4fdd\u5b89\u88c5\u4e86OpenCV\u5e93\u5e76\u5c06\u5206\u7c7b\u5668\u6587\u4ef6\uff08`haarcascade_frontalface_default.xml`\uff09\u653e\u5728\u4e0e\u4ee3\u7801\u6587\u4ef6\u76f8\u540c\u7684\u76ee\u5f55\u4e2d\u3002\u4f60\u53ef\u4ee5\u4eceOpenCV\u5b98\u65b9GitHub\u5b58\u50a8\u5e93\u627e\u5230\u5206\u7c7b\u5668\u6587\u4ef6\uff1ahttps://github.com/opencv/opencv/tree/master/data/haarcascades","behavior":"degenerate_repetition","conversation_hash":"bb4e8ea641538ae316479203beb3c054","conversation_redacted":false,"conversation_toxic":false,"country":"China","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Chinese","model":"gpt-3.5-turbo-0613","n_chars":780,"n_turns_in_conversation":4,"n_words":57,"source_row_offset":78730,"source_shard":"turns-00006.parquet","timestamp":"Fri, 07 Jul 2023 07:33:23 GMT","turn_id":"a065c8e63eb3587aa1fc6c71","turn_index":0,"user_text":"\u4e0d\u7528dlib\u5199\u4e00\u4e2a\u8bc6\u522b\u4eba\u8138\u9762\u90e8\u7684\u7a0b\u5e8fpython"},{"assistant_initiates":false,"asst_text":"\u5982\u679c\u4f60\u4e0d\u60f3\u4f7f\u7528OpenCV\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528`picamera`\u5e93\u548c`face_recognition`\u5e93\u6765\u5b9e\u73b0\u6444\u50cf\u5934\u4eba\u8138\u8bc6\u522b\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u6f14\u793a\u5982\u4f55\u4f7f\u7528\u6811\u8393\u6d3e\uff08PiCamera\uff09\u548cFace Recognition\u5e93\u6765\u5b9e\u73b0\u4eba\u8138\u8bc6\u522b\uff1a\n\n```python\nimport picamera\nimport numpy as np\nimport face_recognition\n\n# \u52a0\u8f7d\u5df2\u77e5\u7684\u4eba\u8138\u56fe\u50cf\u548c\u540d\u79f0\nknown_face_names = [\"person1\", \"person2\"] #\u5c06\u5176\u66ff\u6362\u4e3a\u4f60\u8981\u8bc6\u522b\u7684\u4eba\u7684\u540d\u79f0\nknown_face_encodings = []\nfor name in known_face_names:\n    image = face_recognition.load_image_file(name + \".jpg\")\n    face_encoding = face_recognition.face_encodings(image)[0]\n    known_face_encodings.append(face_encoding)\n\n# \u521d\u59cb\u5316\u6444\u50cf\u5934\ncamera = picamera.PiCamera()\ncamera.resolution = (640, 480)\n\n# \u76d1\u6d4b\u6444\u50cf\u5934\u4e2d\u7684\u4eba\u8138\nwhile True:\n    # \u62cd\u6444\u56fe\u50cf\n    image = np.empty((480, 640, 3), dtype=np.uint8)\n    camera.capture(image, 'rgb')\n\n    # \u5728\u56fe\u50cf\u4e2d\u68c0\u6d4b\u4eba\u8138\n    face_locations = face_recognition.face_locations(image)\n    face_encodings = face_recognition.face_encodings(image, face_locations)\n\n    # \u5728\u56fe\u50cf\u4e2d\u6807\u8bb0\u5df2\u77e5\u7684\u4eba\u8138\n    for face_encoding in face_encodings:\n        matches = face_recognition.compare_faces(known_face_encodings, face_encoding)\n        if True in matches:\n            first_match_index = matches.index(True)\n            name = known_face_names[first_match_index]\n            print(\"\u8bc6\u522b\u5230\u7684\u4eba\u7269\uff1a\", name)\n\n    # \u663e\u793a\u7ed3\u679c\n    cv2.imshow('Video', image)\n\n    # \u6309\u4e0bq\u9000\u51fa\n    if cv2.waitKey(1) & 0xFF == ord('q'):\n        break\n\n# \u6e05\u7406\ncamera.release()\ncv2.destroyAllWindows()\n```\n\n\u8bf7\u6ce8\u610f\uff0c\u4f60\u9700\u8981\u786e\u4fdd\u5728\u4f60\u7684\u6811\u8393\u6d3e\u4e0a\u5b89\u88c5\u4e86`picamera`\u548c`face_recognition`\u5e93\u3002\u4f60\u8fd8\u9700\u8981\u4e3a\u6bcf\u4e2a\u5df2\u77e5\u7684\u4eba\u8138\u521b\u5efa\u4e00\u4e2a\u56fe\u50cf\u6587\u4ef6\uff08\u4f8b\u5982\uff1a\"person1.jpg\"\uff09\u4ee5\u53ca\u5176\u5bf9\u5e94\u7684\u540d\u79f0\uff0c\u5e76\u5c06\u5176\u653e\u5728\u548c\u4ee3\u7801\u6587\u4ef6\u76f8\u540c\u7684\u76ee\u5f55\u4e2d\u3002\u8fd9\u4e2a\u793a\u4f8b\u4ee3\u7801\u5c06\u5728\u8bc6\u522b\u5230\u5df2\u77e5\u4eba\u8138\u65f6\u6253\u5370\u51fa\u5176\u540d\u79f0\u3002\u4f60\u53ef\u4ee5\u6839\u636e\u9700\u8981\u8fdb\u884c\u4fee\u6539\u3002","behavior":"degenerate_repetition","conversation_hash":"bb4e8ea641538ae316479203beb3c054","conversation_redacted":false,"conversation_toxic":false,"country":"China","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Chinese","model":"gpt-3.5-turbo-0613","n_chars":1497,"n_turns_in_conversation":4,"n_words":108,"source_row_offset":78731,"source_shard":"turns-00006.parquet","timestamp":"Fri, 07 Jul 2023 07:33:23 GMT","turn_id":"e6b299623fadc957ada5ef1d","turn_index":1,"user_text":"\u4e0d\u7528dlib\u5199\u4e00\u4e2a\u7528\u6444\u50cf\u5934\u8bc6\u522b\u4eba\u8138\u9762\u90e8\u7684\u7a0b\u5e8fpython\u4e0d\u8981\u7528opeencv"},{"assistant_initiates":false,"asst_text":"\u5982\u679c\u4f60\u4e0d\u5e0c\u671b\u4f7f\u7528dlib\u548cOpenCV\u5e93\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528`picamera`\u5e93\u548c`face_recognition`\u5e93\u6765\u5b9e\u73b0\u6444\u50cf\u5934\u5b9e\u65f6\u4eba\u8138\u8bc6\u522b\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u6f14\u793a\u5982\u4f55\u4f7f\u7528\u6811\u8393\u6d3e\uff08PiCamera\uff09\u548cFace Recognition\u5e93\u6765\u5b9e\u73b0\u5b9e\u65f6\u4eba\u8138\u8bc6\u522b\uff1a\n\n```python\nimport picamera\nimport numpy as np\nimport face_recognition\n\n# \u52a0\u8f7d\u5df2\u77e5\u7684\u4eba\u8138\u56fe\u50cf\u548c\u540d\u79f0\nknown_face_names = [\"person1\", \"person2\"] # \u5c06\u5176\u66ff\u6362\u4e3a\u4f60\u8981\u8bc6\u522b\u7684\u4eba\u7684\u540d\u79f0\nknown_face_encodings = []\nfor name in known_face_names:\n    image = face_recognition.load_image_file(name + \".jpg\")\n    face_encoding = face_recognition.face_encodings(image)[0]\n    known_face_encodings.append(face_encoding)\n\n# \u521d\u59cb\u5316\u6444\u50cf\u5934\ncamera = picamera.PiCamera()\ncamera.resolution = (640, 480)\n\n# \u76d1\u6d4b\u6444\u50cf\u5934\u4e2d\u7684\u4eba\u8138\nwhile True:\n    # \u62cd\u6444\u56fe\u50cf\n    image = np.empty((480, 640, 3), dtype=np.uint8)\n    camera.capture(image, 'rgb')\n\n    # \u5728\u56fe\u50cf\u4e2d\u68c0\u6d4b\u4eba\u8138\n    face_locations = face_recognition.face_locations(image)\n    face_encodings = face_recognition.face_encodings(image, face_locations)\n\n    # \u5728\u56fe\u50cf\u4e2d\u6807\u8bb0\u5df2\u77e5\u7684\u4eba\u8138\n    for face_encoding in face_encodings:\n        matches = face_recognition.compare_faces(known_face_encodings, face_encoding)\n        if True in matches:\n            first_match_index = matches.index(True)\n            name = known_face_names[first_match_index]\n            print(\"\u8bc6\u522b\u5230\u7684\u4eba\u7269\uff1a\", name)\n\n    # \u663e\u793a\u7ed3\u679c\n    cv2.imshow('Video', image)\n\n    # \u6309\u4e0bq\u9000\u51fa\n    if cv2.waitKey(1) & 0xFF == ord('q'):\n        break\n\n# \u6e05\u7406\ncamera.release()\ncv2.destroyAllWindows()\n```\n\n\u8bf7\u6ce8\u610f\uff0c\u4f60\u9700\u8981\u786e\u4fdd\u5728\u4f60\u7684\u6811\u8393\u6d3e\u4e0a\u5b89\u88c5\u4e86`picamera`\u548c`face_recognition`\u5e93\u3002\u4f60\u8fd8\u9700\u8981\u4e3a\u6bcf\u4e2a\u5df2\u77e5\u7684\u4eba\u8138\u521b\u5efa\u4e00\u4e2a\u56fe\u50cf\u6587\u4ef6\uff08\u4f8b\u5982\uff1a\"person1.jpg\"\uff09\u4ee5\u53ca\u5176\u5bf9\u5e94\u7684\u540d\u79f0\uff0c\u5e76\u5c06\u5176\u653e\u5728\u548c\u4ee3\u7801\u6587\u4ef6\u76f8\u540c\u7684\u76ee\u5f55\u4e2d\u3002\u8fd9\u4e2a\u793a\u4f8b\u4ee3\u7801\u5c06\u5728\u8bc6\u522b\u5230\u5df2\u77e5\u4eba\u8138\u65f6\u6253\u5370\u51fa\u5176\u540d\u79f0\u3002\u4f60\u53ef\u4ee5\u6839\u636e\u9700\u8981\u8fdb\u884c\u4fee\u6539\u3002","behavior":"degenerate_repetition","conversation_hash":"bb4e8ea641538ae316479203beb3c054","conversation_redacted":false,"conversation_toxic":false,"country":"China","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Chinese","model":"gpt-3.5-turbo-0613","n_chars":1510,"n_turns_in_conversation":4,"n_words":109,"source_row_offset":78732,"source_shard":"turns-00006.parquet","timestamp":"Fri, 07 Jul 2023 07:33:23 GMT","turn_id":"328513dbb821c703f4db7dbd","turn_index":2,"user_text":"\u4e0d\u7528dlib\u5199\u4e00\u4e2a\u7528\u6444\u50cf\u5934\u5b9e\u65f6\u8bc6\u522b\u4eba\u8138\u9762\u90e8\u7684\u7a0b\u5e8fpython\u4e0d\u8981\u7528opencv"},{"assistant_initiates":false,"asst_text":"\u5982\u679c\u4f60\u53ea\u60f3\u4f7f\u7528OpenCV\u6765\u5b9e\u73b0\u6444\u50cf\u5934\u4eba\u8138\u8bc6\u522b\uff0c\u4f60\u53ef\u4ee5\u53c2\u8003\u4e0b\u9762\u7684\u793a\u4f8b\u4ee3\u7801\uff1a\n\n```python\nimport cv2\n\n# \u52a0\u8f7d\u4eba\u8138\u8bc6\u522b\u5206\u7c7b\u5668\nface_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')\n\n# \u521d\u59cb\u5316\u6444\u50cf\u5934\ncap = cv2.VideoCapture(0)\n\nwhile True:\n    # \u8bfb\u53d6\u6444\u50cf\u5934\u56fe\u50cf\n    ret, frame = cap.read()\n    \n    # \u5c06\u56fe\u50cf\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf\n    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n\n    # \u5728\u56fe\u50cf\u4e2d\u68c0\u6d4b\u4eba\u8138\n    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))\n\n    # \u5728\u56fe\u50cf\u4e2d\u7ed8\u5236\u9762\u90e8\u8fb9\u754c\u6846\n    for (x, y, w, h) in faces:\n        cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)\n\n    # \u663e\u793a\u7ed3\u679c\n    cv2.imshow('Face Detection', frame)\n    \n    # \u6309\u4e0bq\u9000\u51fa\n    if cv2.waitKey(1) & 0xFF == ord('q'):\n        break\n\n# \u91ca\u653e\u6444\u50cf\u5934\u8d44\u6e90\ncap.release()\n\n# \u5173\u95ed\u7a97\u53e3\ncv2.destroyAllWindows()\n```\n\n\u8bf7\u786e\u4fdd\u4f60\u5df2\u7ecf\u5c06\u5206\u7c7b\u5668\u6587\u4ef6\uff08`haarcascade_frontalface_default.xml`\uff09\u653e\u5728\u4e0e\u4ee3\u7801\u6587\u4ef6\u76f8\u540c\u7684\u76ee\u5f55\u4e2d\u3002\u6b64\u793a\u4f8b\u4ee3\u7801\u5c06\u6253\u5f00\u6444\u50cf\u5934\u5e76\u5b9e\u65f6\u68c0\u6d4b\u4eba\u8138\uff0c\u5c06\u68c0\u6d4b\u5230\u7684\u4eba\u8138\u7528\u7eff\u8272\u8fb9\u6846\u6807\u8bb0\u3002\u6309\u4e0bq\u952e\u53ef\u9000\u51fa\u7a0b\u5e8f\u3002\n\n\u8bf7\u6ce8\u610f\uff0c\u8fd9\u53ea\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff0c\u53ef\u80fd\u65e0\u6cd5\u8bc6\u522b\u6240\u6709\u7684\u4eba\u8138\u3002\u5982\u679c\u9700\u8981\u66f4\u51c6\u786e\u548c\u7a33\u5b9a\u7684\u4eba\u8138\u8bc6\u522b\uff0c\u5efa\u8bae\u4f7f\u7528dlib\u6216\u5176\u4ed6\u6df1\u5ea6\u5b66\u4e60\u5e93\u8fdb\u884c\u5904\u7406\u3002","behavior":"degenerate_repetition","conversation_hash":"bb4e8ea641538ae316479203beb3c054","conversation_redacted":false,"conversation_toxic":false,"country":"China","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Chinese","model":"gpt-3.5-turbo-0613","n_chars":943,"n_turns_in_conversation":4,"n_words":79,"source_row_offset":78733,"source_shard":"turns-00006.parquet","timestamp":"Fri, 07 Jul 2023 07:33:23 GMT","turn_id":"3b192a7b1c6bfb7058f9e5c4","turn_index":3,"user_text":"\u4e0d\u7528dlib\u5199\u4e00\u4e2a\u7528\u6444\u50cf\u5934\u8bc6\u522b\u4eba\u8138\u9762\u90e8\u7684\u7a0b\u5e8fpython\u53ea\u7528opeencv"},{"assistant_initiates":false,"asst_text":"As Treaca does not exist and there is no official schedule, the following schedule is a fictional representation for entertainment purposes only:\n\n9:50 AM - 10:15 AM: \"SpongeBob SquarePants\" \u2013 Episode: \"The Legend of Boo-Kini Bottom\"\n10:15 AM - 10:40 AM: \"Monsters vs Aliens\" \u2013 Episode: \"Halloween Special\"\n10:40 AM - 11:05 AM: \"The Loud House\" \u2013 Episode: \"Tricked!\"\n11:05 AM - 11:30 AM: \"Rugrats\" \u2013 Episode: \"Spooky\" \n11:30 AM - 11:55 AM: \"Danny Phantom\" \u2013 Episode: \"Fright Night\"\n11:55 AM - 12:20 PM: \"Bunsen is a Beast\" \u2013 Episode: \"Beast Halloween Ever\"\n12:20 PM - 12:45 PM: \"Hey Arnold!\" \u2013 Episode: \"Arnold's Halloween\"\n12:45 PM - 1:10 PM: \"Rocket Power\" \u2013 Episode: \"It Came from Planet Nightosphere\"\n1:10 PM - 1:35 PM: \"CatDog\" \u2013 Episode: \"Nightmare\"\n1:35 PM - 2:00 PM: \"The Fairly OddParents\" \u2013 Episode: \"Scary Godparents\"\n2:00 PM - 2:25 PM: \"Jimmy Neutron: Boy Genius\" \u2013 Episode: \"Nightmare in Retroville\"\n2:25 PM - 2:50 PM: \"Avatar: The Last Airbender\" \u2013 Episode: \"The Puppetmaster\"\n2:50 PM - 3:15 PM: \"The Penguins of Madagascar\" \u2013 Episode: \"Haunted Habitat\"\n3:15 PM - 3:40 PM: \"Teenage Mutant Ninja Turtles\" \u2013 Episode: \"The Curse of Savanti Romero\"\n3:40 PM - 4:05 PM: \"Harvey Beaks\" \u2013 Episode: \"The Finger\"\n4:05 PM - 4:30 PM: \"Back at the Barnyard\" \u2013 Episode: \"A Barn Day's Night\"\n4:30 PM - 4:55 PM: \"The Wild Thornberrys\" \u2013 Episode: \"Blood Sisters\"\n4:55 PM - 5:20 PM: \"The Adventures of Jimmy Neutron: Boy Genius\" \u2013 Episode: \"Nightmare in Retroville\" (Encore)\n5:20 PM - 5:45 PM: \"Rugrats\" \u2013 Episode: \"Curse of the Werewuff\"\n5:45 PM - 6:10 PM: \"The Loud House\" \u2013 Episode: \"Haunting Pranks\"\n6:10 PM - 6:35 PM: \"The Fairly OddParents\" \u2013 Episode: \"Scary Godparents\" (Encore)\n6:35 PM - 7:00 PM: \"SpongeBob SquarePants\" \u2013 Episode: \"Scaredy Pants\"\n7:00 PM - 7:25 PM: \"Hey Arnold!\" \u2013 Episode: \"Ghost Bride\"\n7:25 PM - 7:50 PM: \"Rocket Power\" \u2013 Episode: \"Reggie's Wild Ride\"\n7:50 PM - 8:15 PM: \"The Angry Beavers\" \u2013 Episode: \"The Day the Earth Got Really Screwed Up\"\n8:15 PM - 8:40 PM: \"The Ren & Stimpy Show\" \u2013 Episode: \"Haunted House\"\n8:40 PM - 9:05 PM: \"Doug\" \u2013 Episode: \"Doug's Halloween Adventure\"\n9:05 PM - 9:30 PM: \"The Legend of Boo-Kini Bottom\" (Encore)\n9:30 PM - 9:55 PM: \"Tricked!\" (Encore)\n9:55 PM onwards: Halloween-themed Nickelodeon movies and specials.\n\nPlease note that this schedule is entirely fictional and created for entertainment purposes only.","behavior":"degenerate_repetition","conversation_hash":"12327a7269c74e8187c85e10f8c1697e","conversation_redacted":false,"conversation_toxic":false,"country":"United Kingdom","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-3.5-turbo-0613","n_chars":2803,"n_turns_in_conversation":1,"n_words":479,"source_row_offset":78734,"source_shard":"turns-00006.parquet","timestamp":"Fri, 07 Jul 2023 07:33:23 GMT","turn_id":"70dcce248344aa63e74280da","turn_index":0,"user_text":"On October 31st 2017, Nickelodeon Treaca aired a Halloween marathon, this premiered the SpongeBob episode \"The Legend of Boo-Kini Bottom\" and The Loud House episode \"Tricked!\" in Treaca, and also making the Monsters vs Aliens show briefly returning to the channel for the first time since April 2015, plus more, what was the schedule, you can make it up as Treaca doesn\u2019t exist, schedule slots are 25 minutes and it started at 9:50 AM"},{"assistant_initiates":false,"asst_text":"The list provided contains topics related to first aid and medical care. Some of these topics include the types of medical care, basics of asepsis and antiseptics, rules of personal safety when providing first aid, sources of infection and prevention of infections associated with providing first aid, rules and procedure for surveying casualties, assessing impaired consciousness, breathing, and blood circulation, pulse characteristics and examination techniques, cardiopulmonary resuscitation, asphyxia and assistance in case of ingestion of foreign bodies, different types of injuries (wounds, fractures, head injuries, chest injuries, abdominal injuries, etc.), specific first aid for different types of injuries, burns and heatstroke, acute poisoning and first aid, and bites and first aid for bites of poisonous insects or animals.","behavior":"degenerate_repetition","conversation_hash":"5680c795a3b818cbc30738adfd819847","conversation_redacted":false,"conversation_toxic":false,"country":"Belarus","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-3.5-turbo-0613","n_chars":4089,"n_turns_in_conversation":3,"n_words":585,"source_row_offset":78735,"source_shard":"turns-00006.parquet","timestamp":"Fri, 07 Jul 2023 07:33:33 GMT","turn_id":"3b6fcb20e03404e0ccf1734c","turn_index":0,"user_text":"1. Types of medical care. The concept of first aid. 2. Basics of asepsis and antiseptics. Rules of personal safety when providing first aid to casualties.\n\n3. Sources of infection, ways and factors of transmission. Prevention of infections associated with providing of first aid.\n\n4. Rules and procedure for survey of the casualty. 5. The main criteria for assessing impaired consciousness, breathing, blood\n\ncirculation. 6. Pulse characteristics, technique of examination on the radial and carotid arteries. 7. Types and frequency of breathing, counting the number of respiratory\n\nmovements.\n\n8. Terminal states. Signs of clinical and biological death.\n\n9. Cardiopulmonary resuscitation. Indications and contraindications for resuscitation. 10. Mistakes and complications during cardiopulmonary resuscitation. Indications\n\nfor termination of cardiopulmonary resuscitation. 11. Asphyxia, types, main signs. Assistance in case of ingestion of foreign bodies into the respiratory tract.\n\n12. Strangulation, obturation, compression asphyxia. First aid. 13. Drowning. First aid in case of drowning. 14. Wounds, general characteristics, types of wounds. First aid.\n\n15. Bleeding, types. The main signs of acute blood loss.\n\n16. Methods of stopping bleeding. Ways to temporarily stop external bleeding. 17. Internal bleeding, main symptoms, first aid. First aid for bleeding from the\n\nnose, ear. 18. Dislocations of the upper and lower extremities, signs, first aid.\n\n19. Bone fractures, signs, first aid.\n\n20. Features of transport immobilization in fractures of various parts of the body. Transportation of patients and injured with fractures.\n\n21. Head injuries, general characteristics, types. Signs of traumatic brain injury. 22. First aid for head injuries. Transportation of casualties.\n\n23. Specificity of first aid for eye, nose, car injuries. 24. Chest injuries, general characteristics, types. The main signs of chest injury.\n\n25. The concept of pneumothorax. First aid for chest injuries. Transportation of casualties.\n\n26. Abdominal injuries, general characteristics, types. The main signs of\n\nabdominal injuries.\n\n27. First aid for abdominal injuries. Features of applying bandages with an open\n\nabdominal injury, injury with a foreign body. Transportation of casualties. 28. Long-term compression syndrome (crush syndrome), concept, main signs, first aid, features of transport immobilization.\n\n29. Traumatic shock, causes, signs, first aid. Measures to prevent the development of traumatic shock.\n\n30. Burns, general characteristics, types. Rules for determining the area of the burn. 31. First aid for thermal, chemical burns, upper respiratory tract burns.\n\n32. Cold injury, general characteristics, main signs, stages of severity. 33. First aid in case of cold injury.\n\n34. Electrical injury: local and general manifestations, first aid, safety measures. 35. Lightning strike, general and local signs, first aid.\n\n36. Heat and sunstroke, general and local signs, first aid.\n\n37 Acute poisoning, types, signs.\n\n38. First aid in case of ingestion of poisons through the respiratory tract, digestive\n\n39. Bites of poisonous insects, snakes, first aid. 40. Rabies. First aid for bites of animals suspected of rabies.\n\ntract, skin.\n\nT\n\nT\n\n1/3"}],"shard":{"index":6,"name":"turns-00006.parquet","rows":100083}}