AMSTE

Dependencies

• Python 3.8.13
• PyTorch 1.12.0
• Numpy
• Sklearn

Datasets

• USCD Ped2 [dataset]
• CUHK Avenue [dataset]
• ShanghaiTech [dataset]

These datasets are from an official github of "Future Frame Prediction for Anomaly Detection - A New Baseline (CVPR 2018)". Download the datasets into your_dataset_directory.

Training

python train.py # for training You can freely define parameters with your own settings like

Evaluation

Test your own model Check your dataset_type (ped2, Avenue or shanghai) python evaluate.py # for Evaluation

We also provide the pre-trained models and the labels of UCSD Ped2, Avenue and ShanghaiTech datasets at https://pan.baidu.com/s/1zcDMUZYfdo4jPI_i2dudIg?pwd=fmsi. To test these models, you need download and put them in weight folder.