Emily's repositories

autoLabeling

自动标注工具

Stargazers:0Issues:0Issues:0

PyTorch-YOLOv3

Minimal PyTorch implementation of YOLOv3

License:GPL-3.0Stargazers:0Issues:0Issues:0

nsfw-resnet

🔥🔥NSFW implement in pytorch(色情图&性感图识别,本程序经过了线上大数据集测试,性能优异效果良好)🔥🔥

Stargazers:0Issues:0Issues:0

nsfw_data_scraper

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

License:MITStargazers:0Issues:0Issues:0

2018--ZJUAI--PyramidBoxDetector

2018 云从人头技术冠军分享方案

Stargazers:0Issues:0Issues:0

FALdetector

Code for the paper: Detecting Photoshopped Faces by Scripting Photoshop

License:Apache-2.0Stargazers:0Issues:0Issues:0

head-detection-using-yolo

Detection of head using YOLO

License:MITStargazers:0Issues:0Issues:0

Safety-Helmet-Wearing-Dataset

Safety helmet wearing detect dataset, with pretrained model

License:MITStargazers:0Issues:0Issues:0

ffhq-dataset

Flickr-Faces-HQ Dataset (FFHQ)

License:NOASSERTIONStargazers:0Issues:0Issues:0

person_search_demo

利用YOLOv3结合行人重识别模型,实现行人的检测识别,查找特定行人

Stargazers:0Issues:0Issues:0
License:Apache-2.0Stargazers:0Issues:0Issues:0
Stargazers:0Issues:0Issues:0

mmaction

An open-source toolbox for action understanding based on PyTorch

License:Apache-2.0Stargazers:0Issues:0Issues:0

faceswap

Deepfakes Software For All

License:GPL-3.0Stargazers:0Issues:0Issues:0

garbage_classify

最严垃圾分类政策自7月1日颁布,如何进行垃圾分类已经成为居民生活的灵魂拷问。但是,没关系!AI在垃圾分类的应用可以成为居民的得力助手。本次垃圾分类挑战杯,目的在于构建基于深度学习技术的图像分类模型,实现垃圾图片类别的精准识别,大赛参考深圳垃圾分类标准,按可回收物、厨余垃圾、有害垃圾和其他垃圾四项分类。

Stargazers:0Issues:0Issues:0

Real-Time-Action-Recognition

A project for action recognition on C3D

Stargazers:0Issues:0Issues:0

vehicle-ReID-baseline

vehicle re-identification baseline for veri and vehicleID dataset

Stargazers:0Issues:0Issues:0

Multimodal-short-video-dataset-and-baseline-classification-model

500,000 multimodal short video data and baseline models. 50万条多模态短视频数据集和基线模型。

Language:Jupyter NotebookStargazers:0Issues:0Issues:0
Stargazers:0Issues:0Issues:0

FBP

FBP项目全称FootBallPrediction,历经9个月完成的足球比赛预测项目。项目结合大数据+机器学习,不断摸索开发了一款软件。软件根据各大博彩公司赔率多维度预测足球比赛结果(包含胜和不胜)。机器学习用的是自己建立的“三木板模型”算法,已在国家期刊发表论文并被万方数据库收录,详见_ML_文件。目前准确率可达80%。该项目在自己创建的微信群里已经吸引了很多人,附件为群讨论截图,并且每天均有部分人根据预测结果参考投注竞彩,参考的人都获得了相应的收益。 现在想通过认识更多的有识之士,一起探索如何将项目做大做强,找到合伙人,实现共赢。希望感兴趣的同仁联系本人,微信号acredjb。公众号AI金胆(或AI-FBP),每天都有程序预测的足球比赛。程序优势请看Advantages和README文件。程序3.0版本:(第三轮目前13中12) 8月10日:13让负(正确) 8月11日:27让负(正确) 8月12日:11让负(正确) 8月13日:6胜(不正确) 8月14日:25让负(正确) 8月15日:无预测 8月16日:1胜(正确) 8月17日:6让负(正确) 8月18日:16胜(正确) 8月19日:34让负(正确) ... 1.0版本(第一轮为11中9) 2.0版本(第二轮13中11).

Language:PythonStargazers:0Issues:0Issues:0

Vehicle-Re-identification-on-VeRi-dataset

Modification of cosine_metric_learning from https://github.com/nwojke/cosine_metric_learning/issues

Stargazers:0Issues:0Issues:0

action-detection

temporal action detection with SSN

License:BSD-3-ClauseStargazers:0Issues:0Issues:0

R2Plus1D-C3D

A PyTorch implementation of R2Plus1D and C3D based on CVPR 2017 paper "A Closer Look at Spatiotemporal Convolutions for Action Recognition" and CVPR 2014 paper "Learning Spatiotemporal Features with 3D Convolutional Networks"

Stargazers:1Issues:0Issues:0

ActivityNet

This repository is intended to host tools and demos for ActivityNet

License:MITStargazers:0Issues:0Issues:0

FCHD-Fully-Convolutional-Head-Detector

Code for FCHD - A fast and accurate head detector

License:NOASSERTIONStargazers:0Issues:0Issues:0

RepNet-MDNet-VehicleReID

Implementing RepNet(a two-stream multitask learning network) to do vehicle Re-identification, vehicle search(or vehicle match) with PyTorch 可用于车辆细粒度识别,车辆再识别,车辆匹配,车辆检索,RepNet/MDNet的一种PyTorch实现

Stargazers:0Issues:0Issues:0

Fall-detection

a very simple Fall-detection(摔倒/跌倒检测)using yolo2

Stargazers:0Issues:0Issues:0

pytorch-video-recognition

PyTorch implemented C3D, R3D, R2Plus1D models for video activity recognition.

License:MITStargazers:0Issues:0Issues:0

Dehazing

Dehazing Project

Stargazers:2Issues:0Issues:0

multimodal-deep-learning-for-disaster-response

Damage Identification in Social Media Posts using Multimodal Deep Learning: code and dataset

Language:PythonStargazers:0Issues:0Issues:0