C-3-Framework

Why we included this project

Crowd counting is one of those computer vision problems where the data pipeline can eat your week before you even train a model. C-3-Framework bundles six mainstream crowd-counting datasets into one PyTorch dev kit, so you can get straight to training classic backbones like AlexNet, VGG, or ResNet and comparing them against published baselines. It also logs losses and TensorBoard visualizations, and snapshots the whole code package with its parameter settings, so a finished experiment can be rerun exactly as it was. That last bit matters more than it sounds when you are trying to tell whether your new model actually beats the numbers in a paper. The catch is maintenance: the author has stopped updating it and points people to NWPU-Crowd-Sample-Code instead, so treat this as a solid reference for baselines and reproduction, not something to build a long-term pipeline on.