YOLO (You Only Look...
An open-source neural network framework written in C and CUDA. It is known for its speed and efficiency in training and running deep learning models, particularly for object detection.
- Experienced
- Free
- English
- Overview
- Reviews
- Alternatives

Use Cases
- Object Detection
- Image Classification

Ideal For
- Analyst
- Developer

Features
- Real-time object detection
- Support for multiple GPUs
- Pre-trained models available
- Custom training capabilities
- Easy to use with CMake

Popular Searches
- How to train a custom model?
- What are the requirements for running Darknet?
- How to use pre-trained models?
- Can Darknet run on Windows?
- What is the performance of Darknet?
Reviews
Rate this tool
Alternatives
- AirtopFreemiumAirtop Node SDK for seamless integration with Airtop services.- Dev Tools
 
 APIDNA$49/moAPIDNA is a platform that provides tools for API development, testing, and management, enabling developers to streamline their workflows and enhance productivity. APIDNA$49/moAPIDNA is a platform that provides tools for API development, testing, and management, enabling developers to streamline their workflows and enhance productivity.- Dev Tools
 
- AutoGenFreemiumAutoGen is a tool designed to automate the generation of code and documentation, enhancing productivity for developers.- Dev Tools
 
2 stars
0.0 / 5
Rating based on recent reviews
- 5 stars0
- 4 stars0
- 3 stars0
- 2 stars0
- 1 star0
FAQ
- What is YOLO (You Only Look... and what is it used for?YOLO (You Only Look Once) is a real-time object detection system that can detect multiple objects in images and videos. It is used for tasks such as surveillance, autonomous driving, and any application requiring fast and accurate object detection.
- Suitable for whom?[{"name":"Analyst","key":"analyst"},{"name":"Developer","key":"developer"}]
- How do I pay for YOLO (You Only Look...?Free
- Is there a free version or demo access?Yes
- What features are available?Real-time object detection, Support for multiple GPUs, Pre-trained models available, Custom training capabilities, Easy to use with CMake





