{"id":1419,"date":"2024-05-10T21:33:28","date_gmt":"2024-05-10T21:33:28","guid":{"rendered":"https:\/\/www.nicekj.com\/?p=1419"},"modified":"2024-05-10T21:34:11","modified_gmt":"2024-05-10T21:34:11","slug":"aigcquanxinlingyuertuxiangshibieruheshixianxiaobaiyenengqing","status":"publish","type":"post","link":"https:\/\/www.nicekj.com\/aigcquanxinlingyuertuxiangshibieruheshixianxiaobaiyenengqing.html","title":{"rendered":"\u3010AIGC\u3011\u5168\u65b0\u9886\u57df\uff01(\u4e8c)\uff1a\u56fe\u50cf\u8bc6\u522b\u5982\u4f55\u5b9e\u73b0\uff1f\u5c0f\u767d\u4e5f\u80fd\u8f7b\u677e\u5b66\u4f1a\uff01"},"content":{"rendered":"

\u524d\u8a00<\/h1>\n

\u2002\u2002\u2002\u2002\u4e0a\u7bc7\u6587\u7ae0\u6211\u4eec\u7b80\u5355\u4f53\u9a8c\u4e86\u4e00\u4e0bOpenAI\u7684\u4f7f\u7528\u548c\u8c03\u8bd5\uff0c\u4eca\u5929\u6211\u4eec\u7ee7\u7eed\u5e26\u5927\u5bb6\u6765\u8fdb\u884c\u7ec3\u4e60\u548c\u66f4\u52a0\u6df1\u5165\u7684\u4e86\u89e3\u3002\u8bdd\u4e0d\u591a\u8bf4\uff0c\u8ba9\u6211\u4eec\u5f00\u59cb\u5427\uff01<\/p>\n

\u6b63\u6587<\/h1>\n

Colaboratory<\/h2>\n

\u2002\u2002\u2002\u2002Colaboratory\uff08\u901a\u5e38\u7b80\u79f0Colab\uff09\u662f\u7531Google\u5f00\u53d1\u548c\u63d0\u4f9b\u7684\u514d\u8d39\u7684\u4e91\u7aefJupyter\u7b14\u8bb0\u672c\u73af\u5883\u3002\u9002\u7528\u4e8ePython\u7f16\u7a0b\u3001\u6570\u636e\u5206\u6790\u548c\u673a\u5668\u5b66\u4e60\uff0c\u4f7f\u7528\u6237\u80fd\u591f\u65e0\u9700\u62c5\u5fc3\u672c\u5730\u8ba1\u7b97\u8d44\u6e90\u7684\u9650\u5236\uff0c\u8f7b\u677e\u8fdb\u884c\u5404\u79cd\u8ba1\u7b97\u4efb\u52a1\u3002\u5728\u6211\u4eec\u62e5\u6709\u4e00\u4e2aGoogle\u8d26\u53f7<\/strong>\u4e4b\u540e\uff0c\u6211\u4eec\u5c06\u4f7f\u7528Colab\u6765\u8fdb\u884c\u6211\u4eec\u7684\u5b66\u4e60\u3002<\/p>\n

\u2002\u2002\u2002\u2002\u9996\u5148\u8ba9\u6211\u4eec\u8fdb\u5165\u5b98\u7f51\uff1acolab.research.google.com\/<\/a> \u3002\u968f\u540e\u8ba9\u6211\u4eec\u627e\u5230\u6587\u4ef6<\/strong>–>\u7136\u540e\u65b0\u5efa\u7b14\u8bb0\u672c<\/strong>\uff08\u5982\u4e0b\u56fe\uff09\uff1a<\/p>\n

\n

\"3.png\"<\/figure>\n<\/p>\n

\u2002\u2002\u2002\u2002\u8df3\u8f6c\u5230\u4e4b\u540e\u7684\u754c\u9762\u6211\u4eec\u5c31\u53ef\u4ee5\u5f00\u59cb\u7f16\u5199\u6211\u4eec\u7684\u4ee3\u7801\u4e86\uff0c\u70b9\u51fb\u5de6\u8fb9\u7684\u201c\u64ad\u653e\u6309\u94ae<\/strong>\u201d\u53ef\u4ee5\u8fd0\u884c\u5f53\u524d\u6846\u5185\u7684\u4ee3\u7801\uff0c\u5f53\u7136\u8fd0\u884c\u5b8c\u6bcf\u6b21\u7684\u4ee3\u7801\u540e\uff0c\u901a\u8fc7\u70b9\u51fb\u201c+\u4ee3\u7801<\/strong>\u201d\u6765\u8fdb\u884c\u65b0\u7684\u4ee3\u7801\u7f16\u5199\uff08\u5982\u4e0b\u56fe\uff09\uff1a<\/p>\n

\n

\"4.png\"<\/figure>\n<\/p>\n

\u2002\u2002\u2002\u2002\u8fd9\u6837\u4f60\u5c31\u5b66\u4f1a\u4e86\u57fa\u672c\u7684\u4f7f\u7528\u65b9\u6cd5\u5566~<\/p>\n

\u673a\u5668\u5b66\u4e60\u4efb\u52a1<\/h2>\n

\u2002\u2002\u2002\u2002\u8fd9\u6b21\u6587\u7ae0\u8ba9\u6211\u4eec\u6765\u8c03\u8bd5<\/strong>\u4e00\u53f0\u80fd\u591f\u5b8c\u6210\u6211\u4eec\u9700\u6c42\u7684\u201c\u673a\u5668<\/strong>\u201d\uff0c\u901a\u8fc7\u4e0d\u65ad\u5730\u8c03\u8bd5\u8ba9\u5b83\u8fdb\u884c\u5b66\u4e60\uff0c\u6700\u7ec8\u80fd\u591f\u5b8c\u6210\u6211\u4eec\u4ea4\u7ed9\u5b83\u7684\u4efb\u52a1\u2014\u2014\u8bc6\u522b\u56fe\u7247\u4e0a\u6211\u4eec\u60f3\u8981\u5b83\u8bc6\u522b\u51fa\u6765\u7684\u4e1c\u897f<\/code>\u3002<\/p>\n

\u2002\u2002\u2002\u2002\u9996\u5148\u8ba9\u6211\u4eec\u8fdb\u5165Colab<\/strong>\uff0c\u65b0\u5efa\u4e00\u53f0\u7b14\u8bb0\u672c\u4f9b\u6211\u4eec\u8fd9\u6b21\u5b66\u4e60\u4f7f\u7528\u3002<\/p>\n

\u2002\u2002\u2002\u2002\u968f\u540e\uff0c\u8ba9\u6211\u4eec\u5b89\u88c5\u4e00\u4e2atransformers<\/code>\u2014\u2014\u4e5f\u5c31\u662fhuggingface<\/strong>\u7684\u6838\u5fc3\u5e93\u5e76\u70b9\u51fb\u8fd0\u884c\uff1a<\/p>\n

<\/div>
python<\/span>
\u590d\u5236\u4ee3\u7801<\/div><\/div><\/div>!pip install transformers<\/span>\n<\/code><\/pre>\n
\n
\"3.png\"<\/figure>\n<\/p>\n
\u2002\u2002\u2002\u2002\u5b89\u88c5\u5b8c\u4e4b\u540e\u5148\u522b\u6025\u7740\u5f04\u5b8c\u6211\u4eec\u7684\u201c\u673a\u5668\u201d\uff0c\u5148\u8ba9\u6211\u4eec\u770b\u770b\u652f\u6301\u6d3e\u53d1\u90a3\u4e9b\u4efb\u52a1\u3002<\/p>\n
<\/div>
python<\/span>
\u590d\u5236\u4ee3\u7801<\/div><\/div><\/div># pipeline --- \u5206\u53d1\u4efb\u52a1 --- pipeline(task, model)<\/span><\/span>\n# transformers pipeline \u54ea\u4e9b\u4efb\u52a1\uff1f<\/span><\/span>\nfrom<\/span> transformers.pipelines import<\/span> SUPPORTED_TASKS<\/span>\nSUPPORTED_TASKS<\/span>\n<\/code><\/pre>\n
\n
\"4.png\"<\/figure>\n<\/p>\n
\u2002\u2002\u2002\u2002\u8fd0\u884c\u5b8c\u4e4b\u540e\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4e0b\u62c9\u4e0b\u5212\u7ebf\u770b\u89c1\u975e\u5e38\u975e\u5e38\u591a\u80fd\u591f\u652f\u6301\u7684\u4efb\u52a1\u3002\u7ee7\u7eed\u6267\u884c\u4e0b\u5217\u4ee3\u7801\u5e76\u8fd0\u884c\uff1a<\/p>\n
<\/div>
python<\/span>
\u590d\u5236\u4ee3\u7801<\/div><\/div><\/div>print<\/span>(SUPPORTED_TASKS.items()) # dick \u5b57\u5178 0(1)<\/span><\/span>\n<\/code><\/pre>\n
\n
\"5.png\"<\/figure>\n<\/p>\n
\u2002\u2002\u2002\u2002\u63a5\u4e0b\u6765\u518d\u8ba9\u6211\u4eec\u770b\u770btransformers<\/strong>\u9ed8\u8ba4\u652f\u6301\u7684nlp\u4efb\u52a1<\/strong>\uff1a<\/p>\n
<\/div>
python<\/span>
\u590d\u5236\u4ee3\u7801<\/div><\/div><\/div># es6 \u89e3\u6784<\/span><\/span>\nfor<\/span> k, v in<\/span> SUPPORTED_TASKS.items(): # \u76f8\u5f53\u4e8e\u5757\u7ea7\u4f5c\u7528\u57df<\/span><\/span>\n  print<\/span>(k) # \u67e5\u770b\u9ed8\u8ba4\u652f\u6301\u7684nlp\u4efb\u52a1<\/span><\/span>\n<\/code><\/pre>\n
\n
\"6.png\"<\/figure>\n<\/p>\n
\u2002\u2002\u2002\u2002\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u5f88\u591a\u5e38\u89c1\u9700\u8981\u7528\u5230\u7684\u529f\u80fd\uff0c\u50cf\u662fquestion-answering<\/code>\u95ee\u7b54\u529f\u80fd\uff0cAI\u5c31\u662f\u9760\u8fd9\u4e2a\u6765\u8fdb\u884c\u8bad\u7ec3\u7684\uff1b\u8fd8\u6709\u6211\u4eec\u63a5\u4e0b\u6765\u6253\u7b97\u7528\u5230\u7684image-classification<\/code>\u56fe\u50cf\u5206\u7c7b\u529f\u80fd\u5566\uff1bzero-shot-object-detection<\/code>\u5b9a\u4f4d\u548c\u8bc6\u522b\u76ee\u6807\u529f\u80fd\u5566\u7b49\u7b49\u3002\u7136\u540e\u518d\u6267\u884c\u4e0b\u9762\u7684\u4ee3\u7801\u8ba9\u6211\u4eec\u80fd\u5feb\u901f\u5b8c\u6210\u4e0a\u9762\u7684\u4efb\u52a1\uff1a<\/p>\n
<\/div>
python<\/span>
\u590d\u5236\u4ee3\u7801<\/div><\/div><\/div>from<\/span> transformers import<\/span> pipeline # \u8ba9\u6211\u4eec\u80fd\u5feb\u901f\u5b8c\u6210\u4e0a\u9762\u7684\u4efb\u52a1<\/span><\/span>\n<\/code><\/pre>\n
\u2002\u2002\u2002\u2002\u901a\u8fc7\u8fd0\u884c\u4ee3\u7801\u4e0b\u8f7d\u56fe\u7247\u8bc6\u522b\u6a21\u578b\uff1a<\/p>\n
<\/div>
python<\/span>
\u590d\u5236\u4ee3\u7801<\/div><\/div><\/div>checkpoint = \"google\/owlvit-base-patch32\"<\/span> # \u56fe\u7247\u8bc6\u522b\u6a21\u578b<\/span><\/span>\ndetector = pipeline('zero-shot-object-detection'<\/span>,model=checkpoint) # (\u9009\u62e9\u4efb\u52a1\uff0c\u4f20\u5165\u6a21\u578b)<\/span><\/span>\n# \u7136\u540e\u5c31\u4f1a\u5f00\u59cb\u4e0b\u8f7d\u56fe\u7247\u8bc6\u522b\u6a21\u578b<\/span><\/span>\n<\/code><\/pre>\n
\n
\"7.png\"<\/figure>\n<\/p>\n
\u6267\u884c\u4efb\u52a1<\/h2>\n
\u2002\u2002\u2002\u2002\u6211\u4eec\u7684\u201c\u673a\u5668<\/strong>\u201d\u8c03\u8bd5\u5230\u8fd9\u5c31\u5feb\u5b8c\u6210\u5566\uff01\u8981\u60f3\u5b83\u80fd\u591f\u8bc6\u522b\u4e1c\u897f\uff0c\u6211\u4eec\u5f97\u5148\u8ba9\u5b83\u80fd\u591f\u62ff\u5230\u56fe\u7247\uff1a<\/p>\n
<\/div>
python<\/span>
\u590d\u5236\u4ee3\u7801<\/div><\/div><\/div>import<\/span> requests # \u5f15\u5165python\u7684http\u8bf7\u6c42\u5e93<\/span><\/span>\nfrom<\/span> PIL import<\/span> Image # PIL\u662fpython\u7684\u56fe\u7247\u7684\u4e13\u4e1a\u5e93<\/span><\/span>\n<\/span>\nurl = 'https:\/\/unsplash.com\/photos\/oj0zeY2Ltk4\/download?ixid=MnwxMjA3fDB8MXxzZWFyY2h8MTR8fHBpY25pY3xlbnwwfHx8fDE2Nzc0OTE1NDk&force=true&w=640'<\/span><\/span>\n# requests.get---\u53d1\u9001\u8fdc\u7a0b\u8bf7\u6c42\uff0c\u8fd9\u4e2a\u8fc7\u7a0b\u4f1a\u82b1\u8d39\u65f6\u95f4<\/span><\/span>\n# python\u662f\u4e00\u95e8\u540c\u6b65\u8bed\u8a00\uff0c\u4f1a\u540c\u6b65\u8bf7\u6c42<\/span><\/span>\n# \u7b49\u5f85\u56fe\u7247\u4e0b\u8f7d\u5b8c\u6210\uff1b\u7136\u540e\u518dImage.open\uff1b\u6700\u540e\u6253\u5370img<\/span><\/span>\nimg = Image.open<\/span>(requests.get(url, stream=True<\/span>).raw)<\/span>\n# requsets --- \u7528\u4e8e\u7f51\u7edc\u8bf7\u6c42\uff0chttp\u8bf7\u6c42\u7684\u65b9\u6cd5\uff0cget\u8868\u793a\u660e\u6587\u8bf7\u6c42<\/span><\/span>\nimg<\/span>\n<\/code><\/pre>\n
\n
\"8.png\"<\/figure>\n<\/p>\n
\u2002\u2002\u2002\u2002\u8fd9\u6837\u6211\u4eec\u5c31\u62ff\u5230\u4e86\u4e00\u5f20\u201c\u6c99\u6ee9\u201d\u7684\u56fe\u7247\u3002\u63a5\u4e0b\u6765\u8ba9\u6211\u4eec\u5411\u6211\u4eec\u7684\u201c\u673a\u5668\u201d\u4f20\u8fbe<\/strong>\u6211\u4eec\u60f3\u8981\u8ba9\u5b83\u5b8c\u6210\u7684\u4efb\u52a1\uff0c\u4e5f\u5c31\u662f\u8bc6\u522b<\/strong>\u54ea\u4e9b\u4e1c\u897f\uff1a<\/p>\n
<\/div>
python<\/span>
\u590d\u5236\u4ee3\u7801<\/div><\/div><\/div>predictions = detector(<\/span>\n    img,<\/span>\n    # \u5019\u9009\u7684\u5bf9\u8c61<\/span><\/span>\n    candidate_labels=[\"hat\"<\/span>,\"sunglasses\"<\/span>,\"book\"<\/span>] <\/span>\n    # \u67e5\u627e\u60f3\u8981\u8bc6\u522b\u7684\u5bf9\u8c61<\/span><\/span>\n)<\/span>\npredictions<\/span>\n<\/code><\/pre>\n
\n
\"9.png\"<\/figure>\n<\/p>\n
\u2002\u2002\u2002\u2002\u6839\u636e\u8fd0\u884c\u7ed3\u679c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u8fd4\u56de\u4e86JSON\u6570\u7ec4<\/strong>\uff0c\u8fd9\u91cc\u4ee3\u8868\u7684\u610f\u601d\u5206\u522b\u662f\uff1a'score'<\/code>\uff1a\u76f8\u4f3c\u5ea6\uff1b'label'<\/code>\uff1a\u6807\u7b7e\u548c'box'<\/code>\uff1a\u8d77\u59cb\u5750\u6807\u3002<\/p>\n
\u67e5\u770b\u7ed3\u679c<\/h2>\n
\u2002\u2002\u2002\u2002\u4f46\u8fd9\u6837\u4f3c\u4e4e\u53ea\u662f\u201c\u673a\u5668\u201d\u80fd\u591f\u7406\u89e3\uff0c\u5728\u6211\u4eec\u770b\u6765\u662f\u4e0d\u591f\u76f4\u89c2\u7684\uff0c\u90a3\u8ba9\u6211\u4eec\u518d\u6765\u4e00\u70b9\u70b9\u201c\u5c0f\u9b54\u6cd5<\/strong>\u201d\uff1a<\/p>\n
<\/div>
python<\/span>
\u590d\u5236\u4ee3\u7801<\/div><\/div><\/div>from<\/span> PIL import<\/span> ImageDraw # \u5f15\u5165\u201c\u5199\u6a21\u5757\"<\/span><\/span>\ndraw = ImageDraw.Draw(img)<\/span>\n<\/span>\nfor<\/span> prediction in<\/span> predictions: # predictions\u91cc\u653e\u7740\u521a\u521a\u7684JSON\u6570\u7ec4<\/span><\/span>\n  box = prediction[\"box\"<\/span>]<\/span>\n  label = prediction[\"label\"<\/span>]<\/span>\n  score = prediction[\"score\"<\/span>]<\/span>\n  xmin, ymin, xmax, ymax = box.values() <\/span>\n  # \u89e3\u6784\u8bed\u6cd5\uff0c\u8fd9\u91cc\u662f\u628a\u4e00\u4e2a\u6570\u7ec4\u91cc\u7684\u503c\u89e3\u6784\u6210\u56db\u4e2a\u53d8\u91cf<\/span><\/span>\n  draw.rectangle((xmin, ymin, xmax, ymax),outline=\"red\"<\/span>,width=1<\/span>) <\/span>\n  # \u5728\u8bc6\u522b\u51fa\u6765\u6807\u7b7e\u7269\u54c1\u7684\u59cb\u672b\u5750\u6807\u6807\u51fa\u7ea2\u8272\u65b9\u6846\uff0c\u5bbd\u5ea6\u4e3a1<\/span><\/span>\n  draw.text((xmin, ymin), f\"{label}<\/span>:{round<\/span>(score, 2<\/span>)}<\/span>\"<\/span>, fill=\"red\"<\/span>) <\/span>\n  # \u5728\u5de6\u4e0a\u89d2\u5199\u4e0a\u6807\u7b7e\u540d\u548c\u76f8\u4f3c\u503c\uff08\u4fdd\u7559\u4e24\u4f4d\u5c0f\u6570\uff09\uff0c\u5b57\u4f53\u4e3a\u7ea2\u8272<\/span><\/span>\n<\/span>\nimg<\/span>\n<\/code><\/pre>\n
\n
\"10.png\"<\/figure>\n<\/p>\n
\u2002\u2002\u2002\u2002\u600e\u4e48\u6837\uff1f\u73b0\u5728\u662f\u4e0d\u662f\u5c31\u8db3\u591f\u76f4\u89c2\u4e86\uff0c\u6211\u4eec\u53ef\u4ee5\u76f4\u63a5\u901a\u8fc7\u8089\u773c\u770b\u89c1\u201c\u673a\u5668\u201d\u5c55\u793a\u7ed9\u6211\u4eec\u6807\u8bb0<\/strong>\u51fa\u6765\u7684\u7ed3\u679c\uff0c\u751a\u81f3\u6253\u4e0a\u4e86\u7ea2\u6846<\/strong>\u5e76\u6253\u4e0a\u4e86\u6807\u7b7e<\/strong>\uff01\u5f97\u5230\u8fd9\u6837\u7684\u7ed3\u679c\u5c31\u8bf4\u660e\u6211\u4eec\u7684\u4efb\u52a1\u5ba3\u5e03\u6210\u529f\u5566~<\/p>\n
\u7ed3\u8bed<\/h1>\n
\u2002\u2002\u2002\u2002\u4eca\u5929\u5e26\u5927\u5bb6\u4f53\u9a8c\u7684\u529f\u80fd\u76f8\u4fe1\u5927\u5bb6\u5728\u751f\u6d3b\u4e2d\u4e5f\u80fd\u611f\u53d7\u5230\u5404\u79cd\u5404\u6837\u7684\u8fd0\u7528<\/strong>\uff1a\u50cf\u662f\u76f8\u673a\u7684\u9762\u90e8\u6355\u6349\u5566\uff1b\u624b\u673a\u7684\u4eba\u8138\u8bc6\u522b\u5566\uff1b\u8f66\u5e93\u95e8\u53e3\u7684\u8f66\u724c\u8bc6\u522b\u5566\u7b49\u7b49\u7b49\u7b49\u3002AI\u5df2\u7ecf\u8d8a\u6765\u8d8a\u878d\u5165\u6211\u4eec\u7684\u751f\u6d3b\u4e86\uff0c\u5982\u679c\u559c\u6b22\u7684\u8bdd\u8fd8\u5e0c\u671b\u70b9\u70b9\u5173\u6ce8\uff0c\u4e4b\u540e\u7ee7\u7eed\u7ed9\u5927\u5bb6\u5e26\u6765\u66f4\u591a\u6709\u8da3\u7684\u6587\u7ae0\u2661\uff01<\/p>","protected":false},"excerpt":{"rendered":"
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