gjy3035/C-3-Framework
A PyTorch development framework for supervised crowd counting using deep neural networks.
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This is an open-source framework for crowd counting, a computer vision regression task that estimates the number of people in images or video frames. It provides baseline implementations of classic CNN architectures (AlexNet, VGG, ResNet) and supports six mainstream datasets for evaluation. The framework includes training pipelines, loss logging, TensorBoard visualization, and experiment reproducibility features.
Frequently asked
- What is gjy3035/C-3-Framework?
- A PyTorch development framework for supervised crowd counting using deep neural networks.
- Is C-3-Framework open source?
- Yes — gjy3035/C-3-Framework is open source, released under the MIT license.
- What language is C-3-Framework written in?
- gjy3035/C-3-Framework is primarily written in Jupyter Notebook.
- How popular is C-3-Framework?
- gjy3035/C-3-Framework has 731 stars on GitHub.
- Where can I find C-3-Framework?
- gjy3035/C-3-Framework is on GitHub at https://github.com/gjy3035/C-3-Framework.