This is the Windows app named YOLOv4 whose latest release can be downloaded as PyTorch_YOLOv4weightssourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
YOLOv4
DESCRIPTION:
PyTorch_YOLOv4 is a PyTorch implementation of YOLOv4 based on the earlier ultralytics YOLOv3 codebase. It provides a practical way to train, test, and run YOLOv4-style object detection models without relying only on the original Darknet implementation. The repository supports common detection workflows such as dataset preparation, model training, evaluation, inference, and weight conversion. It is useful for developers who prefer the PyTorch ecosystem for experimentation, debugging, and integration with other machine learning tooling. The project also connects to the broader YOLOv4 family, including CSP-based architecture ideas and real-time detection improvements. It is best suited for researchers and engineers who want YOLOv4 behavior in a Python-first deep learning environment.
Features
- PyTorch YOLOv4 implementation
- Training and testing scripts
- Object detection inference
- Weight conversion support
- COCO-style detection workflow
- Darknet-to-PyTorch experimentation
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/yolov4.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.