CSRNet-Keras
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An unofficial implementation of CSRNet for crowd counting.
CSRNet-Keras
An unofficial implementation of CSRNet for crowd counting in Keras-Tensorflow.
Paper:
- Original_paper: CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes.
Results now:
| Dataset | MAE | RMSE | Sum of Frobenius Norm | MAPE | PSNR | SSIM |
|---|---|---|---|---|---|---|
| SHB | 8.31 | 14.36 | 5.26e-2 | 6.63% | 29.31 | 0.93 |
| SHA | 67.98 | 103.24 | 8.38e-1 | 17.29% | 21.51 | 0.60 |
Weights can be downloaded in the release.
Dataset:
- ShanghaiTech dataset: dropbox or Baidu Disk.
Training Parameters:
-
Loss = MSE;
-
Optimizer = Adam(lr=1e-5);
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Batch size: 1;
-
Data augmentation: Flip horizontally online randomly;
-
Weights: Got best weights of SHB in epoch 135, the best one of SHA in epoch 127, and here is the loss records:
- SHA:

- SHB:

-
Prediction example:


Run:
- Download dataset;
- Data generation: run the
generate_datasets.ipynb. - Run the
main.ipynbto train, test, analyze and evaluate the image quality.