zhangw864680355

Pinned Repositories

anyRTC-RTMP-OpenSource
RTMP 推流器，RTMP(HLS)秒开播放器，直播点播，跨平台（Win,IOS,Android）开源代码
Language:C++0 0 00
caffe-int8-convert-tools
This convert tools is base on TensorRT 2.0 Int8 calibration tools,which use the KL algorithm to find the suitable threshold to quantize the activions from Float32 to Int8(-128 - 127).
Language:Python0 1 00
caffe-model-zoo
caffe pretrained models and prototxt
0 1 00
cpuinfo
CPU INFOrmation library (x86/x86-64/ARM/ARM64, Linux/Windows/Android/macOS/iOS)
Language:Objective-C0 1 00
DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
0 1 00
django2.0-course
Django2.0视频教程相关代码（杨仕航）
Language:Python0 1 00
fire_detect_mobilenet_v2_ssdlite_keras
A keras version of real-time fire detection network: mobilenet_v2_ssdlite.
Language:Python16 2 39
opencv-sample
This is opencv3.4 sample for study
Language:C++1 1 01
safety_helmet_detect_retinanet_keras
safety-helmet-detect retinanet keras
Language:Python4 3 11
yolo_v3_keras
train your own data by yolo-v3
Language:Python1 2 00

zhangw864680355's Repositories

zhangw864680355/fire_detect_mobilenet_v2_ssdlite_keras
A keras version of real-time fire detection network: mobilenet_v2_ssdlite.
Language:Python16 2 39
zhangw864680355/safety_helmet_detect_retinanet_keras
safety-helmet-detect retinanet keras
Language:Python4 3 11
zhangw864680355/opencv-sample
This is opencv3.4 sample for study
Language:C++1 1 01
zhangw864680355/yolo_v3_keras
train your own data by yolo-v3
Language:Python1 2 00
zhangw864680355/anyRTC-RTMP-OpenSource
RTMP 推流器，RTMP(HLS)秒开播放器，直播点播，跨平台（Win,IOS,Android）开源代码
Language:C++0 0 00
zhangw864680355/caffe-int8-convert-tools
This convert tools is base on TensorRT 2.0 Int8 calibration tools,which use the KL algorithm to find the suitable threshold to quantize the activions from Float32 to Int8(-128 - 127).
Language:Python0 1 00
zhangw864680355/caffe-model-zoo
caffe pretrained models and prototxt
0 1 00
zhangw864680355/cpuinfo
CPU INFOrmation library (x86/x86-64/ARM/ARM64, Linux/Windows/Android/macOS/iOS)
Language:Objective-C0 1 00
zhangw864680355/DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
0 1 00
zhangw864680355/django2.0-course
Django2.0视频教程相关代码（杨仕航）
Language:Python0 1 00
zhangw864680355/DjangoBlog
🍺基于Django的博客系统
Language:Python1 0
zhangw864680355/docker_image_pusher
使用Github Action将国外的Docker镜像转存到阿里云私有仓库，供国内服务器使用，免费易用
zhangw864680355/EasyQuant
EasyQuant(EQ) is an efficient and simple post-training quantization method via effectively optimizing the scales of weights and activations.
Language:Python1 0
zhangw864680355/EverydayWechat
每日自动给女朋友发微信暖心话。
Language:Python1 0
zhangw864680355/examples-of-web-crawlers
python有趣的爬虫例子,对新手比较友好,主要爬取淘宝、天猫、微信、豆瓣、QQ等网站。
Language:Python1 0
zhangw864680355/faceai
一款入门级的人脸、视频、文字检测以及识别的项目.
Language:Python1 0
zhangw864680355/free-api
收集免费的接口服务,做一个api的搬运工
1 0
zhangw864680355/learn_python3_spider
python爬虫教程系列、从0到1学习python爬虫，包括浏览器抓包，手机APP抓包，如 fiddler、mitmproxy，各种爬虫涉及的模块的使用，如：requests、beautifulSoup、selenium、appium、scrapy等，以及IP代理，验证码识别，Mysql，MongoDB数据库的python使用，多线程多进程爬虫的使用，css 爬虫加密逆向破解，JS爬虫逆向，分布式爬虫，爬虫项目实战实例等
Language:Python1 0
zhangw864680355/nanodet
⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
Language:Python1 0
zhangw864680355/python-spider
:rainbow:Python3网络爬虫实战：VIP视频破解助手；GEETEST验证码破解；小说、动漫下载；手机APP爬取；财务报表入库；火车票抢票；抖音APP视频下载；百万英雄辅助；网易云音乐下载；B站视频和弹幕下载；京东晒单图下载
Language:Python1 0
zhangw864680355/pytorch-handbook
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
Language:Jupyter Notebook1 0
zhangw864680355/tensorrtx
Implementation of popular deep learning networks with TensorRT network definition APIs
Language:C++1 0
zhangw864680355/Yolo-Fastest
:zap: Yolo universal target detection model combined with EfficientNet-lite, the calculation amount is only 230Mflops(0.23Bflops), and the model size is 1.3MB
Language:C1 0