Pinned Repositories
.tmux
🇫🇷 Oh my tmux! My self-contained, pretty & versatile tmux configuration made with ❤️
996.ICU
Repo for counting stars and contributing. Press F to pay respect to glorious developers.
Adan
Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models
AdelaiDet
AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.
AGI-survey
Evaluate-Generative-Models
Evaluate FID, sFID, Precision, Recall, and Inception Score for generative models.
GenDSA
[Med - Cell Press] Large-scale Pretrained Frame Generative Model Enables Real-Time Low-Dose DSA Imaging: an AI System Development and Multicenter Validation Study
MoSt-DSA
[ECAI 2024] MoSt-DSA: Modeling Motion and Structural Interactions for Direct Multi-Frame Interpolation in DSA Images
TKH_MTH_Datasets_Release
The Tripitaka Koreana in Han (TKH) Dataset and the Multiple Tripitaka in Han (MTH) Dataset for the research of Chinese character detection and recognition in historical documents.
yoloair
🔥🔥🔥YOLOv7, YOLOv5, YOLOv4, Transformer, YOLOX, YOLOR, YOLOv3 and Improved-YOLOv5... Support to improve backbone, head, loss, IoU, NMS and other modules
ZyoungXu's Repositories
ZyoungXu/awesome-anti-gfw
突破网络审查和封锁的开源工具清单。
ZyoungXu/BBN
The official PyTorch implementation of paper BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition
ZyoungXu/berkeley-stat-157
Homepage for STAT 157 at UC Berkeley
ZyoungXu/built-onnxruntime-for-raspberrypi-linux
Built python wheel files of https://github.com/microsoft/onnxruntime for raspberry pi linux.
ZyoungXu/CRAFT-pytorch
Official implementation of Character Region Awareness for Text Detection (CRAFT)
ZyoungXu/crnn_ctc_ocr_tf
Extremely simple implement for CRNN by Tensorflow
ZyoungXu/deep-text-recognition-benchmark
Text recognition (optical character recognition) with deep learning methods.
ZyoungXu/detectron2-publaynet
Trained Detectron2 object detection models for document layout analysis based on PubLayNet dataset
ZyoungXu/DocumentLayoutAnalysis
Document Layout Analysis resources repos for development with PdfPig.
ZyoungXu/EasyOCR
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
ZyoungXu/HUST-Invictus
华中科技大学研究生课程资料
ZyoungXu/imgaug
Image augmentation for machine learning experiments.
ZyoungXu/labelme
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
ZyoungXu/lite.ai.toolkit
🛠 A lite C++ toolkit of awesome AI models with ONNXRuntime, NCNN, MNN and TNN. YOLOX, YOLOP, YOLOv5, YOLOR, NanoDet, YOLOX, SCRFD, YOLOX . MNN, NCNN, TNN, ONNXRuntime, CPU/GPU.
ZyoungXu/mega.pytorch
Memory Enhanced Global-Local Aggregation for Video Object Detection, CVPR2020
ZyoungXu/mmcv
OpenMMLab Computer Vision Foundation
ZyoungXu/mmsegmentation
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
ZyoungXu/Multimodal-action-recognition
Code on selecting an action based on multimodal inputs. Here in this case inputs are voice and text.
ZyoungXu/netron
Visualizer for neural network, deep learning, and machine learning models
ZyoungXu/onnxruntime
Fork of Microsoft's onnxruntime with patches to run faster on Jetson TX2 and Raspberry Pi
ZyoungXu/PlotNeuralNet
Latex code for making neural networks diagrams
ZyoungXu/pytorch-armv7l
PyTorch 1.7.0 and torchvision 0.8.0 builds for RaspberryPi 4 (32bit OS)
ZyoungXu/pytorch-cnn-visualizations
Pytorch implementation of convolutional neural network visualization techniques
ZyoungXu/SLATracker
Spatial-Attention Location-Aware Multi-Object Tracking
ZyoungXu/tensorflow-on-arm
TensorFlow for Arm
ZyoungXu/VisualDL
Deep Learning Visualization Toolkit（『飞桨』深度学习可视化工具 ）
ZyoungXu/wuhan-IT
『武汉互联网』持续关注武汉互联网公司，帮助大家排坑，让一线浪子顺利回家
ZyoungXu/YOLOP
You Only Look Once for Panopitic Driving Perception.（https://arxiv.org/abs/2108.11250）
ZyoungXu/YOLOP-ONNX-Video-Inference-Sample
YOLOPのPythonでのONNX推論サンプル
ZyoungXu/YOLOP-opencv-dnn
使用OpenCV部署全景驾驶感知网络YOLOP，可同时处理交通目标检测、可驾驶区域分割、车道线检测，三项视觉感知任务，包含C++和Python两种版本的程序实现。本套程序只依赖opencv库就可以运行， 从而彻底摆脱对任何深度学习框架的依赖。