R-CNN Trainer

R-CNN Trainer is a professional desktop application for training, testing, and running R-CNN-based object detection models.

It is designed for users who want to prepare their own image datasets, configure training projects, manage model files, and run detections locally on their own computer.

The integrated workflow helps organize projects, images, annotations, classes, training settings, model checkpoints, and detection results in a clear and practical interface. R-CNN Trainer supports common computer vision tasks such as dataset selection, training configuration, model management, detection testing, and result export.

The app runs locally on the device and is suitable for research projects, image analysis, GIS-related workflows, technical inspection, experimental AI models, and custom object detection tasks.

R-CNN Trainer combines a modern dark interface with practical tools for training, detection, and custom backbone workflows. This makes it possible to build, adapt, and test object detection models in local projects without relying on a cloud platform.