This is the Windows app named Faster-Rcnn whose latest release can be downloaded as v3.1-step,cosXueXiLuXiaJiang,DuoGPUXunLian,ChongLeiMuBiaoShuLiangJiSuanDengsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
Faster-Rcnn
DESCRIPTION:
Faster-Rcnn is a PyTorch implementation of the Faster R-CNN two-stage object detection model. It is designed for training and evaluating detectors on VOC-format datasets, including VOC07+12 and custom datasets arranged with VOC-style annotations and images. The repository includes scripts for training, prediction, evaluation, annotation generation, and model summary inspection. It supports backbone options through pretrained VGG and ResNet weights, making it useful for comparing feature extractors. The project also includes learning rate scheduling through step and cosine methods, optimizer choices between Adam and SGD, adaptive learning rate behavior based on batch size, image cropping, FPS testing, video prediction, and batch prediction. It is a practical reference for users who want a more classical two-stage detector workflow in PyTorch.
Features
- Faster R-CNN PyTorch implementation
- VOC-format dataset training
- VGG and ResNet backbone support
- Custom class file configuration
- Prediction and evaluation scripts
- FPS, video, and batch prediction support
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/faster-rcnn.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.