{"id":103,"date":"2024-10-21T14:35:28","date_gmt":"2024-10-21T06:35:28","guid":{"rendered":"https:\/\/eve2333.top\/?p=103"},"modified":"2024-10-21T14:51:28","modified_gmt":"2024-10-21T06:51:28","slug":"yolov5%e5%ae%9e%e6%88%98%e5%85%a8%e9%83%a8%e6%b5%81%e7%a8%8b","status":"publish","type":"post","link":"https:\/\/eve2333.top\/?p=103","title":{"rendered":"YOLOV5\u5b9e\u6218\u5168\u90e8\u6d41\u7a0b"},"content":{"rendered":"

\u672c\u79d1\u751f\u9636\u6bb5\u9664\u4e86\u5728\u4e2d\u7b49\u4ee5\u4e0a\u7684985\u548c\u67d0\u4e9b\u7279\u5b9a\u7684CS\u5f3a\u9879\u9662\u6821\uff0c\u65e0\u610f\u613f\u7814\u7a76\u751f\u5b66\u4e60\u7684\u672c\u79d1\u751f\u662f\u4e0d\u5efa\u8bae\u5b66\u4e60\u4eba\u5de5\u667a\u80fd\u8fd9\u4e00\u4e13\u4e1a\u7684\uff0c\u4fdd\u7814\u5b66\u751f\u4e5f\u8bb8\u53ef\u4ee5\u5728\u5b9e\u9a8c\u5ba4\u6253\u5de5\u63a8\u8350\u4fe1\u5b66\u4e60\u63a5\u89e6\u5230\u6b64\u7c7b\u4e8b\u4ef6\uff0c\u6b64\u9879blog\u4e3b\u8981\u662f\u5bf9yolov5\u7684\u5b9e\u8df5\u6027\u9879\u76ee\uff0cyolov5\u4f5c\u4e3a\u6700\u5177\u6709\u4ee3\u8868\u6027\u7684yolo\u7248\u672c\uff0c\u5373\u4fbf\u662f2024\u5e74\u4e0a\u534a\u5e74\u6e05\u534e\u7684yolov10\uff0c\u4e5f\u96be\u63a9\u4ed6\u7684\u72ec\u7279\u5149\u8f89\uff0c\u5728\u6b64\u4e0d\u5bf9yolov1\u5230yolov5\u7684\u7248\u672c\u8fed\u4ee3\u548c\u7b97\u6cd5\u66f4\u66ff\u8fdb\u884c\u8be6\u7ec6\u7684\u89e3\u8bf4\u548c\u9610\u8ff0\uff0c\u53ea\u8fdb\u884c\u5b9e\u9645\u9879\u76ee\u6f14\u7ec3<\/p>\n

\u2022 \u00a0Miniconda
\n\u2022\u00a0 \u4e0b\u8f7d\u5730\u5740\uff1aIndex of \/anaconda\/miniconda\/ | \u6e05\u534e\u5927\u5b66\u5f00\u6e90\u8f6f\u4ef6\u955c\u50cf\u7ad9 | Tsinghua Open Source Mirror<\/a><\/span>
\n\u2022 \u00a0pypi\u56fd\u5185\u6e90\uff1a
\n\u2022\u00a0 \u00a0 \u00a0 \u00a0pypi | \u955c\u50cf\u7ad9\u4f7f\u7528\u5e2e\u52a9 | \u6e05\u534e\u5927\u5b66\u5f00\u6e90\u8f6f\u4ef6\u955c\u50cf\u7ad9 | Tsinghua Open Source Mirror<\/a><\/span>
\n\u2022 \u00a0Pytorch
\n\u2022\u5b98\u65b9\u7f51\u7ad9\uff1aPyTorch<\/a><\/span>
\n\u2022 \u00a0YoloV5
\n\u2022 Github\u5730\u5740\uff1aultralytics\/yolov5: YOLOv5 \ud83d\ude80 in PyTorch > ONNX > CoreML > TFLite (github.com)<\/a><\/span><\/p>\n

\u5176\u5b9e\u4e0d\u4e00\u5b9a\u8981miniconda\uff0canaconda\u5c31ok\uff0c\u56e0\u4e3a\u662f\u66f4\u5168\u7684\u5de5\u5177\u5e93\uff0c\u6211\u5728opencv\u5c31\u4e0b\u4e86anaconda\uff0c\u4e0d\u518d\u6362\u6210\u8f7b\u91cf\u7ea7\u7684anaconda\uff0cminiconda\u9009\u62e9py38 22.11.1-1\u8fd9\u4e2a\u7a33\u5b9a\u7248\u672c<\/p>\n

\u5982\u679cC\u76d8\u6709\u7a7a\u95f4\uff0c\u6700\u597d\u5b89\u88c5\u5728C\u76d8\uff0c\u4e14\u5b89\u88c5\u76ee\u5f55\u4e2d\u4e0d\u8981\u6709\u4e2d\u6587---->\u52fe\u9009\u5c06\u5176\u6dfb\u52a0\u5230PATH\u00a0 ------>\u5728conda\u7684cmd\u4e2dconda create -n yolov8 python=3.8Ps:\u7248\u672c\u8fc7\u9ad8\u4f1a\u6709\u4e9b\u5305\u88c5\u4e0d\u4e0a<\/p>\n

pytorch\u7684\u5b89\u88c5<\/h3>\n

 <\/p>\n

\u5982\u679c\u6ca1\u6709Nvidia\u663e\u5361\uff0c\u9009\u62e9cpu\u7248\u672c\u5373\u53ef<\/p>\n

\u5bf9\u4e8eNvidia\u663e\u5361\uff0c\u5728windows\u641c\u7d22\u2018\u82f1\u4f1f\u8fbe\u63a7\u5236\u9762\u677f\u2019\uff0c\u70b9\u51fb\u5de6\u4e0b\u89d2\u7684\u7cfb\u7edf\u4fe1\u606f\u663e\u793a\u5982\u4e0b<\/p>\n

\"\"<\/p>\n

 <\/p>\n

\u8868\u660eCUDA 12.2 146<\/p>\n

\u6839\u636e\u4f60\u7684\u663e\u5361\uff0c\u9009\u62e9\u8f83\u65b0\u7248\u672c\uff0c\u8fd9\u91cc\u5982\u679c\u5927\u5bb6\u6709\u62a5\u9519\u7684\u8bdd\u53ef\u4ee5\u770b\u770b\u662f\u4e0d\u662f\u5f00\u4e86\u4ee3\u7406\uff08\u68af\u5b50\uff09\uff0c\u5f00\u4e86\u4ee3\u7406\u8bb0\u5f97\u628a\u4ee3\u7406\u5173\u4e86\uff0c\u8f7b\u91cf\u7ea7\u7684\u8bad\u7ec3\u4e0d\u7528\u4e0b\u8f7dCUDA\uff0c\u800c\u4e14\u4f60\u7684\u663e\u5361\u4e5f\u57fa\u672c\u4e0a\u4e0d\u600e\u4e48\u6837<\/p>\n

\u6309\u7167\u5982\u4e0b\u64cd\u4f5c\uff0c\u82e5\u548c\u4e0b\u56fe\u4e00\u6837\u5373\u53ef\u8868\u660eok<\/p>\n

https:\/\/i-blog.csdnimg.cn\/direct\/debbcce075aa45309bcc040d59ea575d.png<\/a><\/p>\n

yolov5\u5728github<\/h3>\n

\u6253\u5f00\u53f3\u4fa7\u7684release\u9875\u9762\u4e0b\u8f7d\u540e\u6253\u5f00requirement.txt<\/p>\n

\u4fee\u6539numpy==1.20.3\uff0cPillow==8.3.0\uff0c\u628atorch\u548ctorchvision\u4e24\u884c\u6ce8\u91ca\u6389\u5373\u53ef<\/p>\n

\u5728yolov5\u7684\u6587\u4ef6\u5939\u6253\u5f00cmd\uff0c\u8f93\u5165conda activate yolov5\uff0c\u7136\u540epip install -r requirements.txt<\/p>\n

python detect.py,\u4f1a\u663e\u793a\u4e00\u4e9b\u57fa\u672c\u4fe1\u606f\uff0c\u5b89\u88c5yolov5s.pt\uff0c\u6839\u636e\u63d0\u793a<\/p>\n

\u6a21\u578b\u68c0\u6d4b<\/h1>\n

weights\uff1a\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u6587\u4ef6<\/h3>\n

https:\/\/i-blog.csdnimg.cn\/direct\/75310ea48f594cff9354667cd1d76dce.png<\/a><\/p>\n

\u901a\u8fc7cmd\u8f93\u5165python detect.py --weights yolov5s.pt<\/p>\n

\u5176\u4ed6\u7684\u6587\u4ef6\u53ef\u4ee5\u63d0\u524d\u4e0b\u597d\u653e\u5728yolo\u6587\u4ef6\u5939\u4e2d\uff0c<\/p>\n

source\uff1a\u68c0\u6d4b\u7684\u76ee\u6807\uff0c\u56fe\u7247\uff0c\u6587\u4ef6\u5939\uff0c\u5c4f\u5e55\uff0c\u6444\u50cf\u5934\u7b49<\/h3>\n
\n
python detect.py --weights yolov5s.pt --source<\/span> data\/images\/bus.jpg<\/code><\/pre>\n
<\/span><\/p>\n<\/div>\n
\u5c31\u51fa\u6765\u4e86\u00a0 \u00a0 \u00a0 \u00a0 \u00a0\u63a5\u4e0b\u6765\u5bf9\u5c4f\u5e55\u5b9e\u65f6\u76d1\u6d4b<\/p>\n
\n
python detect.py --weights yolov5s.pt --source<\/span> screen<\/code><\/pre>\n
<\/span><\/p>\n<\/div>\n
conf-thres\u5224\u65ad\u7f6e\u4fe1\u5ea6\u9608\u503c<\/h3>\n
iou-thres\u76f8\u53cd\u7684<\/h3>\n
https:\/\/i-blog.csdnimg.cn\/direct\/8cc07f18749d4d9abeef2ff1c0d3f623.png<\/a><\/p>\n
\"\"<\/span>\u200b<\/span>\u7f16\u8f91<\/span><\/span>\u5404\u79cd\u5404\u6837\u7684\u53c2\u6570<\/p>\n
jupyter\u5b9e\u73b0\u4e00\u4e2a\u754c\u9762<\/h2>\n
\u65b0\u5efa\u4e00\u4e2ahub_detect.ipynb<\/p>\n
\n
import torch\r\n\r\n# Model  <\/span>\r\nmodel = torch.hub.load(\".\/\"<\/span>, \"yolov5s\"<\/span>, source<\/span>=\"local\"<\/span>)\r\n\r\n#Images<\/span>\r\nimg = \".\/data\/images\/zidane.jpg\"<\/span>\r\n\r\n# Inference<\/span>\r\nresults = model(img)\r\n\r\n# Results<\/span>\r\nresults.show()<\/code><\/pre>\n
<\/span><\/p>\n<\/div>\n
\u6784\u5efa\u81ea\u5b9a\u4e49\u6570\u636e\u96c6<\/h1>\n
\u89c6\u9891\u52a8\u6001\u8bc6\u522b<\/h3>\n
https:\/\/i-blog.csdnimg.cn\/direct\/0dcedb29700342ecbcf00f7fcb156f04.png<\/a><\/p>\n
https:\/\/i-blog.csdnimg.cn\/direct\/eb7e76240a4942ddb09c6b08974c2981.png<\/a><\/p>\n
\u6211\u4eec\u5728\u6587\u4ef6\u5939\u8fd9\u79cd\u521b\u5efadatasets\uff0c\u91cc\u9762\u4e00\u4e2a\u89c6\u9891\uff0c\u4e00\u4e2aipynb\u6587\u4ef6\u5bf9\u89c6\u9891\u8fdb\u884copencv\u62bd\u5e27\uff0c\u628a\u62bd\u51fa\u7684\u56fe\u7247\u653e\u5728images\u6587\u4ef6\u5939<\/p>\n
\u7ec8\u7aef\u8f93\u5165labelimg\uff0c\u70b9\u51fbopendir\uff0c\u9009\u62e9images\uff0cchanges save dir\u4e2d\uff0c\u9009\u62e9\u540c\u7ea7\u7684labels\u6587\u4ef6\u5939<\/p>\n
\u628apascal-C\u70b9\u4e00\u4e0b\u53d8\u6210yolo\uff0csave\u4fdd\u5b58\uff0c\u6253\u5f00\u4e0a\u9762view\uff0c\u6253\u5f00autosave\u81ea\u52a8\u4fdd\u5b58<\/p>\n
\u53f3\u952ecreate box\uff0c\u53d1\u73b0\u95ea\u9000\u4e0d\u505c\uff0c\u901a\u8fc7\u6b64\u65b9\u6cd5\u662f\u5426\u89e3\u51b3\uff1f\u95ea\u9000\u662f\u56e0\u4e3a\u7248\u672c3.8<\/strong>\u548c3.11\u4e0d\u5339\u914d \u9700\u8981\u91cd\u65b0\u4e0b\u8f7dUnable to draw annotations on Windows \u00b7 Issue #811 \u00b7 HumanSignal\/labelImg (github.com)<\/a><\/span><\/p>\n
\u6362\u7528labelme\uff0c\u76f8\u540c\u7684pip install labelme\uff0c\u540c\u6837\u7684\u65b9\u6cd5\uff0c\u6807\u6ce8daitu\u548cmingren<\/p>\n
labelimg\u6807\u6ce8\u540e\u662fJSON\u6587\u4ef6\uff0c\u548cyolo\u7684txt\u4e0d\u540c<\/p>\n
jsonTOtxt\u672a\u6d4b\u8bd5<\/p>\n
\n
import<\/span> json\r\nimport<\/span> os\r\nimport<\/span> glob\r\nimport<\/span> os.path as<\/span> osp\r\n\r\n\r\ndef<\/span> labelme2yolov2Seg<\/span>(jsonfilePath=\"\"<\/span>, resultDirPath=\"\"<\/span>, classList=[\"YiBiao\"<\/span>, \"ZhiZhen\"<\/span>]<\/span>):\r\n    \"\"\"\r\n    \u6b64\u51fd\u6570\u7528\u6765\u5c06labelme\u8f6f\u4ef6\u6807\u6ce8\u597d\u7684\u6570\u636e\u96c6\u8f6c\u6362\u4e3ayolov5_7.0sege\u4e2d\u4f7f\u7528\u7684\u6570\u636e\u96c6\r\n    :param jsonfilePath: labelme\u6807\u6ce8\u597d\u7684*.json\u6587\u4ef6\u6240\u5728\u6587\u4ef6\u5939\r\n    :param resultDirPath: \u8f6c\u6362\u597d\u540e\u7684*.txt\u4fdd\u5b58\u6587\u4ef6\u5939\r\n    :param classList: \u6570\u636e\u96c6\u4e2d\u7684\u7c7b\u522b\u6807\u7b7e\r\n    :return:\r\n    \"\"\"<\/span>\r\n    # 0.\u521b\u5efa\u4fdd\u5b58\u8f6c\u6362\u7ed3\u679c\u7684\u6587\u4ef6\u5939<\/span>\r\n    if<\/span>(not<\/span> os.path.exists(resultDirPath)):\r\n        os.mkdir(resultDirPath)\r\n\r\n    # 1.\u83b7\u53d6\u76ee\u5f55\u4e0b\u6240\u6709\u7684labelme\u6807\u6ce8\u597d\u7684Json\u6587\u4ef6\uff0c\u5b58\u5165\u5217\u8868\u4e2d<\/span>\r\n    jsonfileList = glob.glob(osp.join(jsonfilePath, \"*.json\"<\/span>))\r\n    print<\/span>(jsonfileList)  # \u6253\u5370\u6587\u4ef6\u5939\u4e0b\u7684\u6587\u4ef6\u540d\u79f0<\/span>\r\n\r\n    # 2.\u904d\u5386json\u6587\u4ef6\uff0c\u8fdb\u884c\u8f6c\u6362<\/span>\r\n    for<\/span> jsonfile in<\/span> jsonfileList:\r\n        # 3. \u6253\u5f00json\u6587\u4ef6<\/span>\r\n        with<\/span> open<\/span>(jsonfile, \"r\"<\/span>) as<\/span> f:\r\n            file_in = json.load(f)\r\n\r\n            # 4. \u8bfb\u53d6\u6587\u4ef6\u4e2d\u8bb0\u5f55\u7684\u6240\u6709\u6807\u6ce8\u76ee\u6807<\/span>\r\n            shapes = file_in[\"shapes\"<\/span>]\r\n\r\n            # 5. \u4f7f\u7528\u56fe\u50cf\u540d\u79f0\u521b\u5efa\u4e00\u4e2atxt\u6587\u4ef6\uff0c\u7528\u6765\u4fdd\u5b58\u6570\u636e<\/span>\r\n            with<\/span> open<\/span>(resultDirPath + \"\\\\\"<\/span> + jsonfile.split(\"\\\\\"<\/span>)[-1<\/span>].replace(\".json\"<\/span>, \".txt\"<\/span>), \"w\"<\/span>) as<\/span> file_handle:\r\n                # 6. \u904d\u5386shapes\u4e2d\u7684\u6bcf\u4e2a\u76ee\u6807\u7684\u8f6e\u5ed3<\/span>\r\n                for<\/span> shape in<\/span> shapes:\r\n                    # 7.\u6839\u636ejson\u4e2d\u76ee\u6807\u7684\u7c7b\u522b\u6807\u7b7e\uff0c\u4ececlassList\u4e2d\u5bfb\u627e\u7c7b\u522b\u7684ID\uff0c\u7136\u540e\u5199\u5165txt\u6587\u4ef6\u4e2d<\/span>\r\n                    file_handle.writelines(str<\/span>(classList.index(shape[\"label\"<\/span>])) + \" \"<\/span>)\r\n\r\n                    # 8. \u904d\u5386shape\u8f6e\u5ed3\u4e2d\u7684\u6bcf\u4e2a\u70b9\uff0c\u6bcf\u4e2a\u70b9\u8981\u8fdb\u884c\u56fe\u50cf\u5c3a\u5bf8\u7684\u7f29\u653e\uff0c\u5373x\/width, y\/height<\/span>\r\n                    for<\/span> point in<\/span> shape[\"points\"<\/span>]:\r\n                        x = point[0<\/span>]\/file_in[\"imageWidth\"<\/span>]  # mask\u8f6e\u5ed3\u4e2d\u4e00\u70b9\u7684X\u5750\u6807<\/span>\r\n                        y = point[1<\/span>]\/file_in[\"imageHeight\"<\/span>]  # mask\u8f6e\u5ed3\u4e2d\u4e00\u70b9\u7684Y\u5750\u6807<\/span>\r\n                        file_handle.writelines(str<\/span>(x) + \" \"<\/span> + str<\/span>(y) + \" \"<\/span>)  # \u5199\u5165mask\u8f6e\u5ed3\u70b9<\/span>\r\n\r\n                    # 9.\u6bcf\u4e2a\u7269\u4f53\u4e00\u884c\u6570\u636e\uff0c\u4e00\u4e2a\u7269\u4f53\u904d\u5386\u5b8c\u6210\u540e\u9700\u8981\u6362\u884c<\/span>\r\n                    file_handle.writelines(\"\\n\"<\/span>)\r\n            # 10.\u6240\u6709\u7269\u4f53\u90fd\u904d\u5386\u5b8c\uff0c\u9700\u8981\u5173\u95ed\u6587\u4ef6<\/span>\r\n            file_handle.close()\r\n        # 10.\u6240\u6709\u7269\u4f53\u90fd\u904d\u5386\u5b8c\uff0c\u9700\u8981\u5173\u95ed\u6587\u4ef6<\/span>\r\n        f.close()\r\n\r\nif<\/span> __name__ == \"__main__\"<\/span>:\r\n    jsonfilePath = \"E:\\\\yolo\\\\yolov5-master\\\\datasets\\\\labelme\\\\json\"<\/span>  # \u8981\u8f6c\u6362\u7684json\u6587\u4ef6\u6240\u5728\u76ee\u5f55<\/span>\r\n    resultDirPath = \"E:\\\\yolo\\\\yolov5-master\\\\datasets\\\\labelme\\\\txt\"<\/span>  # \u8981\u751f\u6210\u7684txt\u6587\u4ef6\u5939<\/span>\r\n    labelme2yolov2Seg(jsonfilePath=jsonfilePath, resultDirPath=resultDirPath, classList=[\"YiBiao\"<\/span>, \"ZhiZhen\"<\/span>])<\/code><\/pre>\n
<\/span><\/p>\n<\/div>\n
\u6df1\u5ea6\u5b66\u4e60\uff0810\uff09\u4e4bRoboflow \u4f7f\u7528\u8be6\u89e3\uff1a\u6570\u636e\u96c6\u6807\u6ce8\u3001\u8bad\u7ec3 \u53ca \u4e0b\u8f7d-CSDN\u535a\u5ba2<\/a><\/span><\/p>\n
yolov5\u6a21\u578b\u8bad\u7ec3<\/h1>\n
\u00b7images:\u5b58\u653e\u56fe\u7247<\/strong>
\n\u00b7train\uff1a\u8bad\u7ec3\u96c6\u56fe\u7247
\n\u00b7val\uff1a\u9a8c\u8bc1\u96c6\u56fe\u7247
\n\u00b7labels:\u5b58\u653e\u6807\u7b7e<\/strong>
\n\u00b7train\uff1a\u8bad\u7ec3\u96c6\u6807\u7b7e\u6587\u4ef6\uff0c\u8981\u4e0e\u8bad\u7ec3\u96c6\u56fe\u7247\u540d\u79f0\u4e00\u4e00\u5bf9\u5e94
\n\u00b7val\uff1a\u9a8c\u8bc1\u96c6\u6807\u7b7e\u6587\u4ef6\uff0c\u8981\u4e0e\u9a8c\u8bc1\u96c6\u56fe\u7247\u540d\u79f0\u4e00\u4e00\u5bf9\u5e94<\/p>\n
data\u6587\u4ef6\u5939\u91cc\u9762\uff0c\u628acoco128.yaml\u590d\u5236\u4e00\u4efd\u5728\u6e90\u5730\u5740\uff0c\u6539\u540dbvn.yaml<\/p>\n
11\u884c\u540e\u9762\u6240\u6709\u4fee\u6539\u5982\u4e0b<\/p>\n
\n
path: .\/datasets  # dataset root dir<\/span>\r\ntrain: images\/train  # train images (relative to 'path') 128 images<\/span>\r\nval: images\/val  # val images (relative to 'path') 128 images<\/span>\r\ntest:  # test images (optional)<\/span>\r\n\r\n# Classes<\/span>\r\nnames:\r\n  0<\/span>: daitu\r\n  1<\/span>: mingren\r\n  \r\n\r\n<\/code><\/pre>\n
<\/span><\/p>\n<\/div>\n
train.py\u7b2c439\u884c\uff0c<\/p>\n
\n
parser.add_argument('--data'<\/span>, type<\/span>=str<\/span>, default=ROOT \/ 'data\/bvn.yaml'<\/span>, help<\/span>='dataset.yaml path'<\/span>)<\/code><\/pre>\n
<\/span><\/p>\n<\/div>\n
\u8fd0\u884ctrain.py<\/p>\n
\u62a5\u9519\u4e86\uff0c\u622a\u56fe\u5982\u4e0b<\/p>\n
https:\/\/i-blog.csdnimg.cn\/direct\/2e6fdc11a1c34e789c6fb777279aba33.png<\/a><\/p>\n
\u54a8\u8be2\u4e86chatgpt\uff0c\u53ea\u8981\u6dfb\u52a0\u4ee3\u7801\u5373\u53ef<\/p>\n
https:\/\/i-blog.csdnimg.cn\/direct\/4e32bda049de4cd099c18b822849b033.png<\/a>
\n\u5728train.py\u6dfb\u52a0\u4ee5\u4e0b\u4ee3\u7801\u5373\u53ef<\/p>\n
\n
import<\/span> os\r\nos.environ['KMP_DUPLICATE_LIB_OK'<\/span>] = 'TRUE'<\/span>\r\n#####\u4e0a\u9762\u662f\u4e34\u65f6<\/span><\/code><\/pre>\n
<\/span><\/p>\n<\/div>\n
\u5e38\u89c1\u95ee\u9898<\/h3>\n
Arial.ttf\u5b57\u4f53\u6587\u4ef6\u65e0\u6cd5\u4e0b\u8f7d
\n\u00b7\u624b\u52a8\u4e0b\u8f7d\uff0c\u653e\u5230\u5bf9\u5e94\u7684\u4f4d\u7f6e\uff0cwindows\u4e0b\u7684\u76ee\u5f55\u662f\uff1a~\/AppData\/Roaming\/Ultralytics
\n\u00b7\u9875\u9762\u6587\u4ef6\u592a\u5c0f\uff0c\u65e0\u6cd5\u5b8c\u6210\u64cd\u4f5c
\n\u00b7\u8c03\u6574\u8bad\u7ec3\u53c2\u6570\u4e2d\u7684workers\uff0c\u8bbe\u7f6e\u4e3a1
\n\u00b7\u4fee\u6539\u865a\u62df\u5185\u5b58\uff0c\u5c06\u73af\u5883\u5b89\u88c5\u4f4d\u7f6e\u6240\u5728\u7684\u76d8\uff0c\u8bbe\u7f6e\u4e00\u4e2a\u8f83\u5927\u7684\u53c2\u6570.'Upsample' object has no attribute 'recompute scale_factor'
\n\u00b7pytorch\u7248\u672c\u8fc7\u9ad8\u5bfc\u81f4\uff0c\u53ef\u4ee5\u9009\u62e9\u964d\u7248\u672c\uff0c1.8.2\u76ee\u524d\u662f\u4e0d\u4f1a\u62a5\u9519\u7684\u7248\u672c
\n\u00b7\u5982\u4e0d\u60f3\u964d\u4f4e\u7248\u672c\uff0c\u53ef\u4ee5\u4fee\u6539pytorch\u6e90\u7801\uff0c\u6253\u5f00\u62a5\u9519\u7684unsampling.py\uff0c\u5220\u9664recompute_scale_factor\u8fd9\u4e2a\u53c2\u6570<\/p>\n
\u8bad\u7ec3\u6210\u529f\uff01\uff08\u6307\u8fd4\u56de\u503c\u4e3a0\uff09<\/strong><\/p>\n
\u5728weights\u4e2d\u6709best\u548cbad.pt\u5bf9\u5e94\u6700\u597d\u548c\u6700\u574f\u6a21\u578b\u3002\u6709\u4e00\u4e2a\u5f88\u957f\u7684\u6587\u4ef6\uff0c\u662f\u4e00\u4e2a\u65e5\u5fd7<\/p>\n
\u5728pycharm\u7ec8\u7aef\u8f93\u5165<\/p>\n
\n
tensorboard --logdir runs<\/code><\/pre>\n
<\/span><\/p>\n<\/div>\n
\u5373\u53ef\u8df3\u8f6c\u52306006\u7684\u7aef\u53e3<\/p>\n
https:\/\/i-blog.csdnimg.cn\/direct\/3a6c92149fc34bfebef8ad13e627958a.png<\/a><\/p>\n
https:\/\/i-blog.csdnimg.cn\/direct\/b2a0a1c05eca42e286ccf4efc6de3a17.png<\/a><\/p>\n
labels.png\u6587\u4ef6\u4e5f\u6709\u4e00\u4e9b\u6570\u636eresults.csv\uff0cresult.png\u662f\u6574\u5408\u7684\u4e00\u4e9b\u6570\u636e<\/p>\n
\n
cmd\u4e2d  python detect.py --weights runs\/train\/exp3\/weights\/best.pt --source<\/span> datasets\/BVN.MP4 --view-img<\/code><\/pre>\n
<\/span><\/p>\n<\/div>\n
\u5176\u5b9e\u6548\u679c\u8fd8\u5c06\u5c31\uff0c\u4f46\u662f\u7ed3\u679c\u544a\u8bc9\u6211\u8981\u6807\u6ce8\u6e05\u6670\u4e00\u4e9b\uff0c\u5426\u5219\u5bb9\u6613\u91cd\u5408\u7ed3\u679c\uff0c5555<\/p>\n
Pyside6\u5b9e\u73b0GUI\u754c\u9762<\/h1>\n
\u7ec8\u7aef\u8f93\u5165<\/p>\n
\n
pip install pyside6\r\n\u7136\u540e\r\nwhere<\/span> python<\/code><\/pre>\n
<\/span><\/p>\n<\/div>\n
https:\/\/i-blog.csdnimg.cn\/direct\/4f438da08d2d451ca3ee62d6a1a912f1.png<\/a><\/p>\n
D:\\anaconda\\Lib\\site-packages\\PySide6<\/p>\n
main windows\u540e\u70b9\u51fb\u521b\u5efa\uff0c\u6258\u4e24\u4e2alabel\uff0c\u8c03\u597d\u5408\u9002\u7684\u5927\u5c0f\u4f4d\u7f6e\uff0cpush button\u83b7\u5f97\u6309\u94ae<\/p>\n
\u53f3\u4fa7alignment\u6362\u6210\u6c34\u5e73\u4e2d\u5fc3\u5bf9\u9f50\uff0c\u52fe\u9009scaledconpents<\/p>\n
\u6539\u6539\u4fbf\u4e8e\u8bb0\u4f4f\u7684\u6587\u4ef6\u540d\u4fdd\u5b58<\/p>\n
\u628a\u4ed6\u53f3\u952ecompile QT UI uic\u7f16\u8bd1\u51fa\u6765\u5f97\u5230py\u6587\u4ef6<\/p>\n
\u6dfb\u52a0base_ui.py\uff0c\u628aui_main_window.py\u6dfb\u52a0\u8ba1\u5165\uff0c\u5185\u5bb9\u5982\u4e0b<\/p>\n
\n
import<\/span> cv2\r\nimport<\/span> sys\r\nimport<\/span> torch\r\nfrom<\/span> PySide6.QtWidgets import<\/span> QMainWindow, QApplication, QFileDialog\r\nfrom<\/span> PySide6.QtGui import<\/span> QPixmap, QImage\r\nfrom<\/span> PySide6.QtCore import<\/span> QTimer\r\n\r\nfrom<\/span> ui_main_window import<\/span> Ui_MainWindow\r\n\r\n\r\ndef<\/span> convert2QImage<\/span>(img<\/span>):\r\n    height, width, channel = img.shape\r\n    return<\/span> QImage(img, width, height, width * channel, QImage.Format_RGB888)\r\n\r\n\r\nclass<\/span> MainWindow<\/span>(QMainWindow, Ui_MainWindow):\r\n    def<\/span> __init__<\/span>(self<\/span>):\r\n        super<\/span>(MainWindow, self).__init__()\r\n        self.setupUi(self)\r\n        self.model = torch.hub.load(\".\/\"<\/span>, \"custom\"<\/span>, path=\"runs\/train\/exp3\/weights\/best.pt\"<\/span>, source=\"local\"<\/span>)\r\n        self.timer = QTimer()\r\n        self.timer.setInterval(1<\/span>)\r\n        self.video = None<\/span>\r\n        self.bind_slots()\r\n\r\n    def<\/span> image_pred<\/span>(self, file_path<\/span>):\r\n        results = self.model(file_path)\r\n        image = results.render()[0<\/span>]\r\n        return<\/span> convert2QImage(image)\r\n\r\n    def<\/span> open_image<\/span>(self<\/span>):\r\n        print<\/span>(\"\u70b9\u51fb\u4e86\u68c0\u6d4b\u56fe\u7247\uff01\"<\/span>)\r\n        self.timer.stop()\r\n        file_path = QFileDialog.getOpenFileName(self, dir<\/span>=\".\/datasets\/images\/train\"<\/span>, filter<\/span>=\"*.jpg;*.png;*.jpeg\"<\/span>)\r\n        if<\/span> file_path[0<\/span>]:\r\n            file_path = file_path[0<\/span>]\r\n            qimage = self.image_pred(file_path)\r\n            self.input<\/span>.setPixmap(QPixmap(file_path))\r\n            self.output.setPixmap(QPixmap.fromImage(qimage))\r\n\r\n    def<\/span> video_pred<\/span>(self<\/span>):\r\n        ret, frame = self.video.read()\r\n        if<\/span> not<\/span> ret:\r\n            self.timer.stop()\r\n        else<\/span>:\r\n            frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\r\n            self.input<\/span>.setPixmap(QPixmap.fromImage(convert2QImage(frame)))\r\n            results = self.model(frame)\r\n            image = results.render()[0<\/span>]\r\n            self.output.setPixmap(QPixmap.fromImage(convert2QImage(image)))\r\n\r\n    def<\/span> open_video<\/span>(self<\/span>):\r\n        print<\/span>(\"\u70b9\u51fb\u4e86\u68c0\u6d4b\u89c6\u9891\uff01\"<\/span>)\r\n        file_path = QFileDialog.getOpenFileName(self, dir<\/span>=\".\/datasets\"<\/span>, filter<\/span>=\"*.mp4\"<\/span>)\r\n        if<\/span> file_path[0<\/span>]:\r\n            file_path = file_path[0<\/span>]\r\n            self.video = cv2.VideoCapture(file_path)\r\n            self.timer.start()\r\n\r\n    def<\/span> bind_slots<\/span>(self<\/span>):\r\n        self.det_image.clicked.connect(self.open_image)\r\n        self.det_video.clicked.connect(self.open_video)\r\n        self.timer.timeout.connect(self.video_pred)\r\n\r\n\r\nif<\/span> __name__ == \"__main__\"<\/span>:\r\n    app = QApplication(sys.argv)\r\n\r\n    window = MainWindow()\r\n    window.show()\r\n\r\n    app.exec<\/span>()<\/code><\/pre>\n
<\/span><\/p>\n<\/div>\n
\u5176\u5b9e\u662f\u4e00\u4e2apyqt\uff0c\u6709cppqt\u57fa\u7840\u7684\u5e94\u8be5\u53ef\u4ee5\u4e0d\u77e5\u9053\u4e3a\u4ec0\u4e48\u53ea\u80fd\u770b \uff1f<\/p>\n
\u539f\u6765\u662f\u7f3a\u4e00\u4e2a\u6587\u4ef6<\/p>\n
Gradio\u642d\u5efa\u6f14\u793aWeb GUI<\/h1>\n
\u00b7Gradio\u662f\u4e00\u4e2a\u5f00\u6e90\u7684Python\u5e93\uff0c\u7528\u4e8e\u6784\u5efa\u673a\u5668\u5b66\u4e60\u6f14\u793a\u548cWeb\u5e94\u7528
\n\u00b7\u5185\u7f6e\u4e30\u5bcc\u7684\u7ec4\u4ef6\uff0c\u5e76\u4e14\u5b9e\u73b0\u4e86\u524d\u540e\u7aef\u7684\u4ea4\u4e92\u903b\u8f91\uff0c\u65e0\u9700\u989d\u5916\u7f16\u5199\u4ee3\u7801<\/p>\n
\n
pip install gradio<\/code><\/pre>\n
<\/span><\/p>\n<\/div>\n
\u4e66\u5199gradio_demo.py<\/p>\n
\n
import<\/span> torch\r\nimport<\/span> gradio as<\/span> gr\r\n\r\nmodel = torch.hub.load(\".\/\"<\/span>, \"custom\"<\/span>, path=\"runs\/train\/exp3\/weights\/best.pt\"<\/span>, source=\"local\"<\/span>)\r\n\r\ntitle = \"\u57fa\u4e8eGradio\u7684YOLOv5\u6f14\u793a\u9879\u76ee\"<\/span>\r\n\r\ndesc = \"\u8fd9\u662f\u4e00\u4e2a\u57fa\u4e8eGradio\u7684YOLOv5\u6f14\u793a\u9879\u76ee\uff0c\u975e\u5e38\u7b80\u6d01\uff0c\u975e\u5e38\u65b9\u4fbf\uff01\"<\/span>\r\n\r\nbase_conf, base_iou = 0.25<\/span>, 0.45<\/span>\r\n\r\ndef<\/span> det_image<\/span>(img, conf_thres, iou_thres<\/span>):\r\n    model.conf = conf_thres\r\n    model.iou = iou_thres\r\n    return<\/span> model(img).render()[0<\/span>]\r\n\r\ngr.Interface(inputs=[\"image\"<\/span>, gr.Slider(minimum=0<\/span>, maximum=1<\/span>, value=base_conf), gr.Slider(minimum=0<\/span>, maximum=1<\/span>, value=base_iou)],\r\n             outputs=[\"image\"<\/span>],\r\n             fn=det_image,\r\n             title=title,\r\n             description=desc,\r\n             live=True<\/span>,\r\n             examples=[[\".\/datasets\/images\/train\/30.jpg\"<\/span>, base_conf, base_iou], [\".\/datasets\/images\/train\/60.jpg\"<\/span>, 0.3<\/span>, base_iou]]).launch(share=True<\/span>)\r\n\r\n<\/code><\/pre>\n
<\/span><\/p>\n<\/div>\n
\u76f4\u63a5\u586b\u5199image\u505a\u4e86\u4e00\u4e2a\u6620\u5c04\uff0c\u672c\u8d28\u4e0a\u8c03\u4e86gr.Image()\u7ec4\u4ef6<\/p>\n
\u8fd0\u884c\u540e\u53ef\u80fd\u4f1a\u6709\u70b9\u5361\uff0c\u6700\u540eexamples\u662flist<\/p>\n
\u5728launch\u8bbe\u5b9a\u8fd9\u91cc\uff0c\u6362\u6210true\uff0c\u90a3\u4e48\u5c31\u4f1a\u628a\u670d\u52a1\u653e\u5728\u516c\u7f51\u4e0a<\/p>\n
\u200b<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
\u672c\u79d1\u751f\u9636\u6bb5\u9664\u4e86\u5728\u4e2d\u7b49\u4ee5\u4e0a\u7684985\u548c\u67d0\u4e9b\u7279\u5b9a\u7684CS\u5f3a\u9879\u9662\u6821\uff0c\u65e0\u610f\u613f\u7814\u7a76\u751f\u5b66\u4e60\u7684\u672c\u79d1\u751f\u662f\u4e0d\u5efa\u8bae\u5b66\u4e60\u4eba\u5de5\u667a\u80fd\u8fd9\u4e00\u4e13\u4e1a\u7684\uff0c\u4fdd\u7814\u5b66\u751f\u4e5f\u8bb8\u53ef\u4ee5 …<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"emotion":"","emotion_color":"","title_style":"","license":"","footnotes":""},"categories":[3],"tags":[6,5],"class_list":["post-103","post","type-post","status-publish","format-standard","hentry","category-3","tag-cv","tag-yolo"],"_links":{"self":[{"href":"https:\/\/eve2333.top\/index.php?rest_route=\/wp\/v2\/posts\/103","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/eve2333.top\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/eve2333.top\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/eve2333.top\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/eve2333.top\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=103"}],"version-history":[{"count":0,"href":"https:\/\/eve2333.top\/index.php?rest_route=\/wp\/v2\/posts\/103\/revisions"}],"wp:attachment":[{"href":"https:\/\/eve2333.top\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=103"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/eve2333.top\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=103"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/eve2333.top\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=103"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
https:\/\/i-blog.csdnimg.cn\/direct\/4972605010c24fdea414d1d9eafa438d.png<\/a><\/p>\n
Sign in to Roboflow<\/a><\/span>\u00a0\u6211\u4eec\u9009\u62e9\u5728\u7ebf\u5e73\u53f0roboflow\u6765\u76f4\u63a5\u6807\u8bb0\uff0c\u751f\u6210txt\uff0c\u65b9\u6cd5\u5982\u4e0b<\/p>\n
\u56fe\u7247\u8fdb\u884c\u8bc6\u522b<\/h3>\n
\u6559\u7a0b\uff1a\u8d85\u8be6\u7ec6\u4ece\u96f6\u5f00\u59cbyolov5\u6a21\u578b\u8bad\u7ec3_yolo\u8bad\u7ec3-CSDN\u535a\u5ba2d<\/a><\/span><\/p>\n
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