eval_sample: A sample input and label image that can be used to help debug the model.
model: Contains code for loading image data (get_data.py) and running the model (model.py). Usage is python model.py. Note that model.py expects data to be in a data folder at the top level; we could not upload our data to github due to insufficient space. Please email [email protected] for google drive access if you wish to download it.
outputs: Folder for holding sampled model output.
test_run_records: folders that contain records of various implementation tests that we ran. Each contains at least one .csv file (pipe-separated) with record of training and testing loss/accuracy over several epochs, as well as sampled output from the model. The arch_test subfolder represent architecture tests; see the model_arch_x.txt files to see what architecture was being tested in each run.
tif_processing.py: code used to preprocess and slice the raw .tif images into the 100x100 .png images we used for training/testing.
requirements.txt: Lists some packages not included in the commonly used homework packages that are necessary for this project.