evaluate_model.py

import argparse

import matplotlib as mpl
mpl.use('Agg')

import matplotlib.pyplot as plt

from fnet.utils.figures import evaluate_model, eval_images, print_stats_all, print_stats_all_v2



import logging
import os
import pandas as pd
import sys
import warnings

import numpy as np
import glob

import pickle


import pdb

def str2bool(v):
    if v.lower() in ('yes', 'true', 't', 'y', '1'):
        return True
    elif v.lower() in ('no', 'false', 'f', 'n', '0'):
        return False
    else:
        raise argparse.ArgumentTypeError('Boolean value expected.')
    


if __name__ == '__main__':
    
    parser = argparse.ArgumentParser()
    parser.add_argument('--predictions_file', default=None, help='two column .csv of paths to path_prediction and path_target')
    parser.add_argument('--predictions_dir', default=None, help='project directory. Mutually exclusive of predictions_dir')
    parser.add_argument('--path_save_dir', default='saved_models', help='base directory for saving results')
    parser.add_argument('--save_error_maps', type=str2bool, default=False, help='Save error map images')
    parser.add_argument('--overwrite', type=str2bool, default=True, help='overwrite previous results')
    parser.add_argument('--reference_file', default=None, help='directory or images for calculating c_max')
    opts = parser.parse_args()
    
    print(opts)
    
    evaluate_model(**vars(opts))