Derek (tecsai)

tecsai

Geek Repo

Location:Shanghai

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Derek's repositories

TensorRT_yolo3

use TensorRT accelerate yolo3

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AddGPS

Add GPS info to jpg image

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MobileNet-Caffe

Caffe Implementation of Google's MobileNets (v1 and v2)

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DesignPattern23-C-

23 designed pattern in C++

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996.ICU

Repo for counting stars and contributing. Press F to pay respect to glorious developers.

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libfacedetection

An open source library for face detection in images. The face detection speed can reach 1500FPS.

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caffe

Caffe: a fast open framework for deep learning.

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openpose-1

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

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nsfw_data_scrapper

Collection of scripts to aggregate image data for the purposes of training an NSFW Image Classifier

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nsfw_data_source_urls

Collection of NSFW images URLs for the purposes of training an NSFW Image Classifier

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SSD-Tensorflow

Single Shot MultiBox Detector in TensorFlow

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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15个章节,近20万字。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

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face_recognition

The world's simplest facial recognition api for Python and the command line

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EasyPusher

简单、高效、稳定的一款标准RTSP/RTP协议直播推送库,支持将H.264/G.711/G.726/AAC等音视频数据推送到RTSP流媒体服务器进行低延时直播或者视频通信,支持Windows、Linux、ARM、Android、iOS等平台,EasyPusher配套EasyDarwin流媒体服务器、EasyPlayer RTSP播放器适用于特殊行业的低延时应急指挥需求! Android迁移到了https://github.com/EasyDarwin/EasyPusher_Android , iOS迁移到了https://github.com/EasyDarwin/EasyPusher_iOS

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caffe_rtpose

Realtime C++ code for multi-person pose estimation

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rtsp

简单的RTSP播放器

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MTCNN

Repository for "Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks", implemented with Caffe, C++ interface.

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rapidonvif

ONVIF C++ lib, support ProfileS, mail to info@linkingvision.com for latest version

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OpenPose

OpenPose的简单实现版本,简洁不简单,so easy. 就一个cpp

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EasyOpenPose

OpenPose的简单实现

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MTCNN_Caffe

Simple implementation of kpzhang93's paper from Matlab to c++, and don't change models.

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