diff --git a/README.md b/README.md index 56f198616ab231f4861eaf50d698d183418663eb..6ed0373a6344b008798eea2e4e36f6e4f6e83012 100644 --- a/README.md +++ b/README.md @@ -3,6 +3,20 @@ This source code is for submission at workshop RRPR 2020. We reproduce the results for Fall detection and extend 3D convolutional autoencoder for Intrusion detection task. +**Installation** + +1. Install conda from https://docs.conda.io/en/latest/miniconda.html depending on your OS. + +2. Create conda environment from the given environment.yml file. + + Go to root location of this project in your terminal and run the following command + + `conda env create -f environment.yml` + +3. Activate conda environment + + `source activate stcae` + **Code Usage:** The code base is split into two main subsets @@ -13,11 +27,15 @@ stcae_test.py - For testing different models **Training:** -To use this code, first run the training module. A model is then saved to Models/Dataset/.... +To use this code, first run the training module as: + +`python3 stcae_train.py ` -Specify: +A model is then saved to Models/Dataset/.... -Dataset (Task) - dset = 'Thermal_Intrusion' or 'Thermal_Fall' +Specify in stcae_train.py: + +Dataset (Task) - dset = 'Thermal_Intrusion' or 'Thermal_Fall' or 'Thermal_Dummy' Model - Upsampling, Deconvolution or C3D @@ -27,7 +45,11 @@ and other parameters. **Testing:** -To evaluate the model, run the test module. The results of testing will be saved to AEComparisons. +To evaluate the model, run the test module as: + +`python3 stcae_test.py ` + +The results of testing will be saved to AEComparisons. Once training has completed, find the saved model under Models/Thermal/{model_name}. To evaluate the model, set the variable pre_load to the path to this model. Run stcae_test.py and find the results in AEComparisons. diff --git a/environment.yml b/environment.yml index 87771eb96a2379ade6509c2a9d15d5412820eb9d..6bd87e85a0416c21b57de84d9d6f540b9ac853fd 100644 --- a/environment.yml +++ b/environment.yml @@ -1,4 +1,4 @@ -name: deepfall +name: stcae channels: - menpo - conda-forge