#!/usr/bin/env python3

#

# Copyright, TU Dortmund 2020

# MIT License

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import argparse

import pandas as pd

from utils import path_join

parser = argparse.ArgumentParser(

description='This script reads and analyzes the validation IoU files of '

'either Deeplab or FCN networks, '

'and orders the respective network checkpoints by mean IoU.')

parser.add_argument('val_results_root',

help='Root directory containing all checkpoint evaluations')

parser.add_argument('--output_file',

help='If set, this will contain the mIoU for each epoch.')

parser.add_argument('--epochs', type=int, default=100,

help='Number of epochs used in training of the model')

args = parser.parse_args()

mIOU = []

for i in list(range(0, args.epochs, 5)) + [args.epochs - 1]:

iou_df_i_path = path_join(args.val_results_root, f'ep{i}/iou.csv')

iou_df_i = pd.read_csv(iou_df_i_path)

mIOU_i = iou_df_i.drop(['truth_path', 'pred_path'], axis=1).mean(

axis=0, skipna=True)

mIOU_i['mIoU'] = mIOU_i.mean()

mIOU_i['Epoch'] = i

mIOU.append(mIOU_i)

mIOU = pd.DataFrame(mIOU)

mIOU.sort_values('mIoU', ascending=False, inplace=True)

if args.output_file is not None:

mIOU.to_csv(args.output_file)

print(mIOU.head())