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adadet

AdaDet: A Development Toolkit for Object Detection based on ModelScope

adaseq

AdaSeq: An All-in-One Library for Developing State-of-the-Art Sequence Understanding Models

awesome-hand-pose-estimation

Awesome work on hand pose estimation/tracking

caffe_data_augmentation

This is a data_layer.cpp, in which I implement some data augmentation (such as morror, shrink, translate, brightness changing).

caffe_visualization

to visualize the blob(feature maps) or params(w and b) of a caffemodel

damo-streamnet

egocentric_rock-scissors-paper_game

An egocentric view Rock-Scissors-Paper game built by Qt + caffe.

label_tool_simplified_version

This repository is a simplified version of label_tool repository.

labeling_tool

A tool to collect bbox and label

longshortnet

LongShortNet for Streaming Perception task.

lst

official implementation for Language Supervised Training for Skeleton-based Action Recognition

markdown-emoji

Markdown语法支持添加 emoji表情，输入不同的符号码（两个冒号包围的字符）可以显示出不同的表情

mine_utils

Some useful and reusable scripts.

mmclassification

OpenMMLab Image Classification Toolbox and Benchmark

mmcv

OpenMMLab Computer Vision Foundation

mmdetection

OpenMMLab Detection Toolbox and Benchmark

mtcnn-tensorflow

Reproduce MTCNN using Tensorflow

nts-net

This is a PyTorch implementation of the ECCV2018 paper "Learning to Navigate for Fine-grained Classification" (Ze Yang, Tiange Luo, Dong Wang, Zhiqiang Hu, Jun Gao, Liwei Wang).

query_cameraid

A project in windows to query the camera ID when there are several camera connected to the PC.

r-c3d.pytorch

R-C3D pytorch implementation

record_dataset_gui

A GUI application for collecting human motion dataset

robustphotometricstereo

Robust Photometric Stereo

temporal-transformer-module

The tensorflow implementation of Temporal Transformer Module (TTM).

tensorflow-mtcnn

人脸检测MTCNN算法，采用tensorflow框架编写，从理解到训练，中文注释完全，含测试和训练，支持摄像头

tianchi_cervical_cancer_top4

TIANCHI 天池 “数字人体”视觉挑战赛——宫颈癌风险智能诊断 算法赛道 LLLLC队代码 4/2359

tutorial-for-laboratory-newcomers

A tutorial for the laboratory newcomers.