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Yolo_Label. GUI for marking bounded boxes of objects in images for training neural network YOLO
702PyTorch-Deformable-Convolution-v2. Don't feel pain to use Deformable Convolution
342PyTorch-Darknet53. PyTorch implementation of Darknet53
118SKNet-PyTorch. Nearly Perfect & Easily Understandable PyTorch Implementation of SKNet
100RTSP-Client-FFMPEG-OpenCV-ON-QT. RTSP Client Program using FFmpeg and OpenCV on Qt
64Custom-CNN-based-Image-Classification-in-PyTorch. Python
46onepose. Human pose estimation within one line
44EDAR. PyTorch implementation of Deep Convolution Networks based on EDSR for Compression(Jpeg) Artifacts Reduction
37Modern-Cpp-NMS. A Modern C++ Implementation of NMS
27ZAM. ZAM: Zero parameter Attention Module
27YOLOX-Backbone. yolox_backbone is a deep-learning library and a collection of YOLOX Backbone models.
25onnxruntime-cuda-cpp-example. Examples for inference models with ONNXRuntime and CUDA
25Setup-for-Imagenet. Imagenet(for image classification, 2012) 데이터 셋 다운로드 및 정리 방법 정리
24Num-Workers-Search. num_workers Search Algorithm for Fast PyTorch DataLoader
23FFmpeg-Debug-VSCode-Windows. The guide to debug FFmpeg on Windows with VSCode
20pytorch-backbone-benchmark. Benchmarks for popular neural network models supported by timm
18Explainable-YOLOv8. Visualize the low-level outputs of YOLOv8 to analyze and understand the areas where our model focuses. Specifically, illustrate which anchor points are activated to predict bounding boxes.
15YOLOv3Tiny. PyTorch Implementation of YOLOv3Tiny
13TX2-JetPack-Installation-Guide-Kr. 한글로 작성된 TX2 JetPack 설치 가이드입니다.
12image-knocker. Knock your images before you get stressed.
11Learning-Rate-WarmUp.
11qsort. Much faster than SORT(Simple Online and Realtime Tracking), a little worse than SORT
10Elastic-Distortion. Implementation of elastic distortion algorithm in C++ (Using OpenCV)
10BatchedFFmpeg. Process multiple videos with one line of ffmpeg command.
9PicoDet-Backbone. PyTorch Implementation of Backbone of PicoDet
8CSPDarknet53. Pytorch Implementation of CSPDarknet53
8imgdiet. A Python package for minimizing file size of images with negligible quality loss
8Torch-Warmup. The easiest way to use learning rate warmup method on PyTorch
7plotbbox. A package to plot pretty bounding boxes for object detection task
7Practical-FFmpeg-Examples. Practical FFmpeg examples for beginners
6rotten-korean-romanizer. Python library for romanizing Korean text. Converts '안녕하세요' to 'annyeonghaseyo' and more.
4yolov8-tensorrt-inference-docker-image. Simply run your YOLOv8 faster by using TensorRT on a docker container
4Github-Actions-Tutorial.
4developer0hye.github.io. JavaScript
4commitcleaner. Clean your all commit history in one line
3docker-cleanup. A lightweight CLI tool to clean all Docker resources – including containers, images, volumes, networks, and build caches – with a single command.
3COCO128. Small subsets of the COCO2017 dataset for CI/CD testing, debugging, and faster experiment
32019_Kwangwoon_Univ_CE_DS_Project_1. 2019년도 광운대학교 컴퓨터정보공학부 데이터 구조 설계 및 실습 1차 프로젝트 스켈레톤 코드
3Windows10-Nvidia-Docker-WSL. Nvidia Docker on WSL(Windows10) Guide
3PyTorch-ImageNet. PyTorch based Imagenet Training Code
3PyTorch-DLA. Pytorch Implementation of Deep Layer Aggregation Networks
2Algo-0hye. 백준 온라인 저지 뿌셔뿌셔
2My-FFMPEG-Scripts. Python
2yolov5. YOLOv5 in PyTorch > ONNX > CoreML > TFLite
2Genetic-Piecewise-Linear-Approximation. Coursework Project: GPLA(Genetic Piecewise Linear Approximation)
2Papers-Yonghye-reads. 읽은 논문들 정리
2Torch-BatchNorm-From-Scratch.
2ViT. Python
2googletest-hello-world. CMake
2ultralytics. YOLOv8 🚀 in PyTorch > ONNX > CoreML > TFLite
2korean-sentence-embedding-example. 한국어 문장 임베딩 모델들의 성능을 비교하고 시각화하는 프로젝트입니다. 본 프로젝트는 Claude Opus 4로 구현되었습니다.
2ColabxPytorch-Image-Classfier. ColabXPytorch-Image-Classfier
1Color-Space-3D-Visualization. Visualize the Color Space in 3D using Plotly on Google Colab.
1Imagination. An Open Source Deep Learning Framework for Image Processing
1actions-cpp-hello-world. CMake
1pre-commit-tutorial. Python
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