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An unofficial implementation of CSRNet for crowd counting.

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CSRNet-Keras

An unofficial implementation of CSRNet for crowd counting in Keras-Tensorflow.


Paper:

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:

Training Parameters:

  1. Loss = MSE;

  2. Optimizer = Adam(lr=1e-5);

  3. Batch size: 1;

  4. Data augmentation: Flip horizontally online randomly;

  5. Weights: Got best weights of SHB in epoch 135, the best one of SHA in epoch 127, and here is the loss records:

    • SHA:

    Loss_records_SHB

    • SHB:

    Loss_records_SHB

  6. Prediction example:

    example

    example

Run:

  1. Download dataset;
  2. Data generation: run thegenerate_datasets.ipynb .
  3. Run the main.ipynb to train, test, analyze and evaluate the image quality.

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An unofficial implementation of CSRNet for crowd counting.

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