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2018 云从人头技术冠军分享方案
This project forked from ywcmaike/2018--zjuai--pyramidboxdetector
2018 云从人头技术冠军分享方案
2018云从人头技术 冠军方案分享 运行环境: Ubuntu16.04 pytorch0.3.1 torchvision numpy cuda cudnn等 需要GPU 如Titan 12G等。 Test 新建weights/, model文件在这里下载 通用模型: 链接:https://pan.baidu.com/s/1hDGi02UsHplftYFpfcAvpw 提取码:9xk1 our专用模型:链接:https://pan.baidu.com/s/1PN3aBBr4Frzb9RvO4NgfNw 提取码:kkrc 1、将数据置于yuncong_test_set文件夹中, 2、直接运行test_yuncong_*.py 可以得到对应的生成文件,更多的参数设置请看文件 train 1 将数据放在当前目录下,即2018云从人头技术-...., 此目录下有Mall Part_A 等场景的原始数据,你可以相应的调整,但原来的代码文件路径可能需要相应的调整. 2 数据增强,对每个场景都有对应的数据增强,由于之前使用的是paddlepaddle版本的pyramidbox的数据格式,需要调用一下topytorch.py来生成pytorch版本的数据格式,可以自己去调整. 最后对每个场景生成训练的数据文件集如: cat UCSD.txt augfile_UCSD > final_UCSD.txt 3 然后可以进行训练, 可生成通用的模型,也可对应场景的模型, mod/parta/partb/mall/ucsd/our等. 运行相应的代码即可. 最近在赶deadline,更多训练的步骤,后续将更详细的给出. 如有疑问,请联系我 微信: 13032893650 手机: 13032893650 email: [email protected] [email protected] 更多细节请看 .docx 和 .pptx 文件 欢迎star
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