motokimura/yolo_v1_pytorch
PyTorch implementation of YOLO-v1 including training
This project helps computer vision practitioners and researchers quickly train an object detection model using the YOLO-v1 architecture. You provide a dataset of images, and it outputs a model capable of identifying and localizing specific objects within new images. It's designed for those who need to build systems that automatically recognize objects in visual data.
166 stars. No commits in the last 6 months.
Use this if you need a straightforward PyTorch implementation to train a YOLO-v1 model for object detection tasks.
Not ideal if you are looking for the latest object detection architectures or a tool that doesn't require familiarity with machine learning training processes.
Stars
166
Forks
41
Language
Shell
License
MIT
Category
Last pushed
Nov 21, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/motokimura/yolo_v1_pytorch"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
ultralytics/yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
ultralytics/yolov3
YOLOv3 in PyTorch > ONNX > CoreML > TFLite
mindspore-lab/mindyolo
A toolbox of yolo models and algorithms based on MindSpore
ultralytics/assets
Ultralytics assets
stephanecharette/DarkHelp
C++ wrapper library for Darknet