{"id":246,"date":"2023-08-21T23:49:39","date_gmt":"2023-08-21T15:49:39","guid":{"rendered":"https:\/\/eidolon168.com\/?p=246"},"modified":"2023-08-22T23:51:56","modified_gmt":"2023-08-22T15:51:56","slug":"%e5%b5%8c%e5%85%a5%e5%bc%8f%e9%96%8b%e7%99%bc%e7%89%88%e6%b7%b1%e5%ba%a6%e5%ad%b8%e7%bf%92%e6%a8%a1%e5%9e%8b%e5%84%aa%e5%8c%96%e6%96%b9%e5%90%91-tensorflow-lite","status":"publish","type":"post","link":"https:\/\/web.eidolon.ddns.net\/?p=246","title":{"rendered":"\u5d4c\u5165\u5f0f\u958b\u767c\u7248\u6df1\u5ea6\u5b78\u7fd2\u6a21\u578b\u512a\u5316\u65b9\u5411- Tensorflow Lite"},"content":{"rendered":"\n<p>#rpi4, #tensorflow, #tensorflow-lite<\/p>\n\n\n\n<p>\u8ddd\u96e2\u4e0a\u6b21\u66f4\u65b0\u53c8\u9694\u4e86\u597d\u4e00\u9663\u5b50\u3002\u6700\u8fd1\u5de5\u4f5c\u53c8\u56de\u5230\u4ee5\u5f80\u7684\u8001\u672c\u884c- \u4eba\u5de5\u667a\u6167\u3001\u6df1\u5ea6\u5b78\u7fd2\u6a21\u578b\u512a\u5316\u8207\u90e8\u7f72\u4efb\u52d9\u3002\u4e4b\u524d\u6311\u6230\u904eRaspiberry Pi 3B, ASUS Tinkerboard \u8207 Nvidia Jetson Nano\uff0c\u4e0d\u5f97\u4e0d\u8aaa\uff0c\u9019\u5e7e\u5e74\u96a8\u8457\u61c9\u7528\u8d8a\u4f86\u8d8a\u591a\uff0c\u6574\u500b\u751f\u614b\u4e5f\u8d8a\u4f86\u8d8a\u5b8c\u6574\u3002\u4e4b\u524d\u6700\u5e38\u78b0\u5230\u7684 CPU \u7248\u672c\u5dee\u7570(arm v7l, aarch64)\u5e36\u4f86\u7684\u5957\u4ef6\u76f8\u5bb9\u6027\u554f\u984c\u7372\u5f97\u5927\u5e45\u5ea6\u7684\u89e3\u6c7a\uff0c\u5e38\u7528\u71b1\u9580\u5957\u4ef6\u7684\u5b89\u88dd\u554f\u984c\u8d8a\u4f86\u8d8a\u5c11\uff0c\u9700\u8981\u805a\u7126\u7684\u53cd\u800c\u662f\u6a21\u578b\u7684\u904b\u7b97\u6548\u80fd\u3002<\/p>\n\n\n\n<p>\u9019\u7bc7\u6587\u7ae0\u4e0d\u7d30\u8ac7\u50b3\u7d71\u7684\u7a0b\u5f0f\u908f\u8f2f\u7b49\u50b3\u7d71\u512a\u5316\u65b9\u5411\uff0c\u4e3b\u8981\u662f\u8457\u91cd\u5728\u65e2\u6709\u7684\u7a0b\u5f0f\u78bc\u5c08\u6848\u4e2d\uff0c\u6539\u5584\u6a21\u578b\u7684\u63a8\u8ad6\u6548\u7387\u3002\u9996\u5148\u62cb\u51fa\u5169\u500b\u5f88\u5bb9\u6613\u6df7\u6dc6\u7684\u540d\u8a5e- ONNX (Open Neural Network Exchange) \u8207 Tensorflow Lite\u3002\u70ba\u4ec0\u9ebc\u8aaa\u9019\u5169\u500b\u5f88\u5bb9\u6613\u6df7\u6dc6\uff0c\u4e3b\u8981\u662f\u81ea\u5df1\u7684\u63a5\u89f8\u6b77\u7a0b\u7d93\u9a57\uff0c\u9019\u5169\u500b\u7b97\u662f\u5dee\u4e0d\u591a\u6642\u671f\u62cb\u51fa\u4f86\u7684\u5169\u500b\u5c08\u6848\uff0c\u524d\u8005\u662f\u958b\u653e\u5f0f\u795e\u7d93\u7db2\u8def\u4ea4\u63db\u67b6\u69cb\u6587\u4ef6\uff0c\u4e3b\u8981\u6709\u9451\u65bc\u6df1\u5ea6\u5b78\u7fd2\u6846\u67b6\u773e\u591a\uff0c\u4f8b\u5982: Tensorflow, Caffe, Pytorch, Keras &#8230; \u7b49\uff0c\u5404\u6709\u5404\u7684\u64c1\u6234\u8005\u3002\u56e0\u6b64\uff0c\u5982\u679c\u6a21\u578b\u8207\u6a21\u578b\u60f3\u8981\u754c\u63a5\u7684\u8a71\uff0c\u5c31\u9700\u8981\u900f\u904e\u9019\u500b\u5c08\u6848\u4f86\u8655\u7406\u3002\u7c21\u800c\u8a00\u4e4b\uff0c\u6211\u5011\u53ef\u4ee5\u628a\u4ed6\u8a8d\u70ba\u5c31\u662f\u4e00\u500b\u8f49\u63db\u5de5\u5177\uff0c\u628a\u4e0d\u64c5\u9577\u7684\u6a21\u578b\u6b0a\u91cd\u8f49\u63db\u6210\u81ea\u5df1\u64c5\u9577\u7684\u67b6\u69cb\u9032\u884c\u4e8c\u6b21\u958b\u767c\u3002\u5f8c\u8005\u5c31\u662f\u4eca\u5929\u7684\u4e3b\u984c- Tensorflow Lite \uff0c\u4ed6\u662f\u4e00\u500b\u884c\u52d5\u88dd\u7f6e\u7a0b\u5f0f\u5eab\uff0c\u7528\u65bc\u5728\u884c\u52d5\u88dd\u7f6e\u3001\u5fae\u63a7\u5236\u5668\u548c\u5176\u4ed6\u908a\u7de3\u88dd\u7f6e\u4e0a\u90e8\u7f72\u6a21\u578b\u3002\u56e0\u6b64\u5c0d\u65bc\u9019\u985e\u578b\u904b\u7b97\u6548\u80fd\u6709\u9650\u7684\u6a5f\u7a2e\uff0c\u6216\u8005\u6211\u6703\u8aaa\u662f\u4e0d\u5177\u5099GPU\u52a0\u901f\u6216\u8005TPU\u6548\u7387\u6709\u9650\u7684\u884c\u52d5\u88dd\u7f6e\u7684\u6a21\u578b\u512a\u5316\u89e3\u6c7a\u65b9\u6848\u3002<\/p>\n\n\n\n<p>\u76f4\u63a5\u4e0a\u500b\u4f8b\u5b50\uff0c\u5047\u8a2d\u6211\u6709\u4e00\u500b Tensorflow Keras \u8a13\u7df4\u51fa\u4f86\u7684\u6a21\u578b\u6a94\u6848\u3002\u6211\u4f7f\u7528 h5 \u6a94\u6848\u683c\u5f0f\u7d00\u9304\u6b0a\u91cd\u3001JSON \u6a94\u6848\u683c\u5f0f\u7d00\u9304\u6a21\u578b\u7684\u7d30\u90e8\u67b6\u69cb\u3002\u5982\u679c\u4eca\u5929\u6211\u5e0c\u671b\u900f\u904e Tensorflow Lite \u4f86\u505a\uff0c\u6211\u9700\u8981\u5982\u4f55\u8f49\u63db\u3002\u4e0b\u9762\u6211\u5011\u76f4\u63a5\u4e0a\u7a0b\u5f0f\u78bc:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import tensorflow as tf\nfrom tensorflow.keras.models import model_from_json\n\n# Load the architecture of the model from JSON file\njson_file = open('model.json', 'r')\nloaded_model_json = json_file.read()\njson_file.close()\nloaded_model = model_from_json(loaded_model_json)\n\n# Load weights into the new model\nloaded_model.load_weights(\"model.h5\")\n\n# \u4f7f\u7528 TFLiteConverter \u8f49\u63db\u6a21\u578b\nconverter = tf.lite.TFLiteConverter.from_keras_model(loaded_model)\nconverter.optimizations = &#91;tf.lite.Optimize.DEFAULT]\ntflite_model = converter.convert()\n\n# \u4fdd\u5b58 TFLite \u6a21\u578b\nwith open('model.tflite', 'wb') as f:\n    f.write(tflite_model)\n<\/code><\/pre>\n\n\n\n<p>\u6574\u500b\u7a0b\u5f0f\u78bc\u67b6\u69cb\u975e\u5e38\u6e05\u695a\uff0c\u4e3b\u8981\u5206\u62103\u500b\u968e\u6bb5<\/p>\n\n\n\n<ol class=\"wp-block-list\"><li>\u8b80\u5165\u6a21\u578b\u67b6\u69cb\u8207\u6b0a\u91cd<\/li><li>\u4f7f\u7528 TFLiteConverter \u8f49\u63db\u6a21\u578b<\/li><li>\u4fdd\u5b58\u8f49\u63db\u5f8c\u7684 TFLite \u6a21\u578b<\/li><\/ol>\n\n\n\n<p>\u5982\u679c\u6709\u7559\u610f\u5230\u7684\u8a71\uff0c\u53ef\u4ee5\u770b\u5230\u6709\u7279\u5225\u7684\u4e00\u884c\u4ee3\u78bc<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>converter.optimizations = &#91;tf.lite.Optimize.DEFAULT]<\/code><\/pre>\n\n\n\n<p>\u57fa\u672c\u4e0a\u4ed6\u662f\u600e\u9ebc\u505a\u5230\u512a\u5316\u7684\u5462? \u5176\u5be6\u4e5f\u4e0d\u96e3\u7406\u89e3\uff0c\u5c31\u662f\u964d\u4f4e\u7cbe\u5ea6\u3002\u5927\u6982\u5305\u542b\u4ee5\u4e0b\u5e7e\u500b\u7b56\u7565\u4f86\u9054\u5230\u6a21\u578b\u512a\u5316\u7684\u76ee\u7684:<\/p>\n\n\n\n<ol class=\"wp-block-list\"><li><strong>\u91cf\u5316\uff08Quantization\uff09<\/strong>\uff1a\u5c07\u6a21\u578b\u53c3\u6578\u5f9e<strong>\u6d6e\u9ede\u6578\u8f49\u63db\u70ba\u6574\u6578<\/strong>\uff0c\u5f9e\u800c\u6e1b\u5c0f\u6a21\u578b\u5927\u5c0f\u4e26\u52a0\u901f\u63a8\u7406\u904e\u7a0b\u3002<\/li><li><strong>\u53bb\u9664\u4e0d\u5fc5\u8981\u7684\u64cd\u4f5c\uff08Removing Redundant Operations\uff09<\/strong>\uff1a\u53bb\u9664\u6a21\u578b\u4e2d\u5c0d\u65bc\u63a8\u7406\u7121\u95dc\u7dca\u8981\u7684\u64cd\u4f5c\uff0c\u5f9e\u800c\u6e1b\u5c0f\u6a21\u578b\u8907\u96dc\u5ea6\u3002<\/li><li><strong>\u5408\u4f75\u64cd\u4f5c\uff08Merging Operations\uff09<\/strong>\uff1a\u5c07\u591a\u500b\u64cd\u4f5c\u5408\u4f75\u70ba\u4e00\u500b\u64cd\u4f5c\uff0c\u5f9e\u800c\u6e1b\u5c0f\u8a08\u7b97\u91cf\u3002<\/li><li><strong>\u6e1b\u5c11\u7cbe\u5ea6\uff08Reducing Precision\uff09<\/strong>\uff1a\u6e1b\u5c0f\u64cd\u4f5c\u7684\u6578\u503c\u7cbe\u5ea6\uff0c\u5f9e\u800c\u5728\u4e00\u5b9a\u7a0b\u5ea6\u4e0a\u964d\u4f4e\u6a21\u578b\u7684\u8a08\u7b97\u8ca0\u64d4\u3002<\/li><li><strong>Fused \u5e38\u898b\u64cd\u4f5c\uff08Fused Common Operations\uff09<\/strong>\uff1a\u5c07\u4e00\u4e9b\u5e38\u898b\u7684\u64cd\u4f5c\u5408\u4f75\u70ba\u4e00\u500b\u64cd\u4f5c\uff0c\u63d0\u9ad8\u63a8\u7406\u901f\u5ea6\u3002<\/li><\/ol>\n\n\n\n<p>\u7c21\u55ae\u8aaa\u660e\u529f\u80fd\u8207\u6e2c\u8a66\u74b0\u5883\u8207\u689d\u4ef6<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>\u529f\u80fd: \u9019\u500b\u6a21\u578b\u662f\u8b80\u5165\u4e00\u5f35\u4eba\u81c9\u5224\u5225\u4ed6\u7684\u60c5\u7dd2\uff0c\u4e00\u5171\u67096\u7a2e\u60c5\u7dd2\u6307\u6a19- 0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral\uff1b<\/li><li>\u4e3b\u6a5f: Raspiberry Pi 4 (RAM: 4GB, emmc: 32GB)<\/li><li>\u4f5c\u696d\u7cfb\u7d71: Raspberry Pi OS 64bits<\/li><li>\u6df1\u5ea6\u5b78\u7fd2\u904b\u884c\u6846\u67b6: Tensorflow 2.4.0 <\/li><\/ul>\n\n\n\n<p>\u6700\u5f8c\u4f86\u5f35\u8868\u683c\uff0c\u6bd4\u8f03\u4e00\u4e0b\u512a\u5316\u524d\u5f8c\u5dee\u7570<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-stripes\"><table><tbody><tr><td><\/td><td>\u65e2\u6709\u6a21\u578b<\/td><td>\u4f7f\u7528\u512a\u5316\u7b56\u7565<\/td><td>\u4e0d\u4f7f\u7528\u512a\u5316\u7b56\u7565<\/td><\/tr><tr><td>FPS<\/td><td>3.0 <\/td><td>6.2<\/td><td>6.5<\/td><\/tr><\/tbody><\/table><figcaption>H5 to TensorFlow Lite \u6a21\u578b\u512a\u5316\u524d\u5f8c\u5dee\u7570<\/figcaption><\/figure>\n\n\n\n<p>\u679c\u7136\u6548\u80fd\u6539\u5584\u5c07\u8fd11\u500d\u4ee5\u4e0a\uff0c\u9084\u63d0\u5347\u6a21\u578b\u5728\u4f7f\u7528\u4e0a\u7684\u4fbf\u5229\uff0c\u4e0d\u9700\u8981\u5206\u5225\u532f\u51652\u500b\u6a21\u578b\u6a94\u6848\uff0c\u800c\u662f\u76f4\u63a5\u8b80\u5165 tflite \u5c31\u53ef\u4ee5\u9032\u884c\u63a8\u7b97\uff0c\u5176\u4ed6\u7684\u4ee3\u78bc\u4e5f\u4e0d\u5927\u9700\u8981\u7279\u5225\u8abf\u6574\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>#rpi4, #tensorflow, #tensorflow-lite \u8ddd\u96e2\u4e0a\u6b21\u66f4\u65b0\u53c8\u9694\u4e86\u597d\u4e00\u9663\u5b50\u3002\u6700\u8fd1\u5de5\u4f5c &#8230; <a title=\"\u5d4c\u5165\u5f0f\u958b\u767c\u7248\u6df1\u5ea6\u5b78\u7fd2\u6a21\u578b\u512a\u5316\u65b9\u5411- Tensorflow Lite\" class=\"read-more\" href=\"https:\/\/web.eidolon.ddns.net\/?p=246\" aria-label=\"Read more about \u5d4c\u5165\u5f0f\u958b\u767c\u7248\u6df1\u5ea6\u5b78\u7fd2\u6a21\u578b\u512a\u5316\u65b9\u5411- Tensorflow Lite\">\u95b1\u8b80\u5168\u6587<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[39],"tags":[96,94,92,93,90,91,95],"class_list":["post-246","post","type-post","status-publish","format-standard","hentry","category-python","tag-facial-expression","tag-model-optimization","tag-raspiberry","tag-rpi4","tag-tensorflow","tag-tensorflow-lite","tag-tflite"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u5d4c\u5165\u5f0f\u958b\u767c\u7248\u6df1\u5ea6\u5b78\u7fd2\u6a21\u578b\u512a\u5316\u65b9\u5411- Tensorflow Lite - Eidolon&#039;s \u7cfb\u7d71\u6574\u5408\u7814\u767c\u5de5\u7a0b\u5e2b\u7684\u6210\u9577\u624b\u672d<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, 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