sacmehta/EdgeNets
A PyTorch library of efficient CNN architectures for image classification, object detection, and semantic segmentation.
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This repository provides implementations of efficient convolutional neural network architectures (ESPNetV2, ShuffleNetV2, DiceNet) optimized for edge devices. It includes training pipelines and pre-trained models for standard computer vision benchmarks including ImageNet classification, MS-COCO object detection, and semantic segmentation on CityScapes and PASCAL VOC datasets.
Frequently asked
- What is sacmehta/EdgeNets?
- A PyTorch library of efficient CNN architectures for image classification, object detection, and semantic segmentation.
- Is EdgeNets open source?
- Yes — sacmehta/EdgeNets is open source, released under the MIT license.
- What language is EdgeNets written in?
- sacmehta/EdgeNets is primarily written in Python.
- How popular is EdgeNets?
- sacmehta/EdgeNets has 413 stars on GitHub.
- Where can I find EdgeNets?
- sacmehta/EdgeNets is on GitHub at https://github.com/sacmehta/EdgeNets.