TWJ's repositories
confusion-matrices
confusion_matrices
face_dataset
收集人脸相关数据集
AircraftCarrier_Dataset
This repository is to download the AircraftCarrier Dataset
awesome-semantic-segmentation
:metal: awesome-semantic-segmentation
BestYOLO
🌟Change the world, it will become a better place. | 以科研和竞赛为导向的最好的YOLO实践框架!
caffe-sl
caffe for Similarity Learning
caffe_toolkit
Caffe toolkit, including installing Caffe, creating various networks.
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
DroneVehicle
Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning
Face-Detector-1MB-with-landmark
1M人脸检测模型(含关键点)
MMdnn
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch and CoreML.
ONNX-yolov5
deploy yolov5 in c++
OpenCV3-Intro-Book-Src
:blue_book:《OpenCV3编程入门》书本配套源码 |《Introduction to OpenCV3 Programming》Book Source Code
PaddleDetection
Object detection and instance segmentation toolkit based on PaddlePaddle.
rgb-footprint-extract
A Semantic Segmentation Network for Urban-Scale Building Footprint Extraction Using RGB Satellite Imagery
semcity_eval
Evaluation Scripts for Semcity
ShiftCNN
A script to convert floating-point CNN models into generalized low-precision ShiftCNN representation
Slim-CNN
A Light-Weight CNN for Face Attribute Prediction
tensorflow-cnn-web
Web capabilities for tensorflow image classification
TNN
TNN：由腾讯优图实验室打造，移动端高性能、轻量级推理框架，同时拥有跨平台、高性能、模型压缩、代码裁剪等众多突出优势。TNN框架在原有Rapidnet、ncnn框架的基础上进一步加强了移动端设备的支持以及性能优化，同时也借鉴了业界主流开源框架高性能和良好拓展性的优点。目前TNN已经在手Q、微视、P图等应用中落地，欢迎大家参与协同共建，促进TNN推理框架进一步完善。
tutorial
ubuntu16.10+cuda8.0+cudnn8.0+opencv3.2+caffe+tensorflow
web-caffe
web demo of caffe
web-vision
Interactive web application for image classification
yolov5_rotation
rotated bbox detection. inspired by https://github.com/hukaixuan19970627/YOLOv5_DOTA_OBB, thanks hukaixuan19970627.