import os
import os.path as osp
import csv
from collections import Counter

csv_file = './output/test/resnet50-224.csv'
output_prefix = './test/'
class_to_idx = {'Card': 0, 'Flyer': 1, 'Infographic': 2, 'Logo': 3, 'Poster': 4, 'T-shirt': 5}
idx_to_class = {v:k for k, v in class_to_idx.items()}

def read_csv_file(csv_file):
    with open(csv_file, 'r') as f:
        reader = csv.reader(f)
        next(reader) # skip header
        for row in reader:
            filename, indexs, probs = row
            indexs = list(filter(None, indexs[1:-1].split(' ')))
            probs = list(filter(None, probs[1:-1].split(' ')))
            # print(indexs, probs)
            yield filename, int(indexs[0]), float(probs[0]), int(indexs[1]), float(probs[1])

def main():
    print('''Result

| pic | gt | top1 | top1_prob | top2 | top2_prob |
|-|-|-|-|-|-|''')
    category_counter = Counter()
    for filename, top1, top1_prob, top2, top2_prob in read_csv_file(csv_file):
        gt_category = osp.dirname(filename)
        category_counter[gt_category] += 1
        if category_counter[gt_category] > 20:
            continue
        # output filename as MD image
        print(f'| <img src="{osp.join(output_prefix, filename)}" alt="{filename}" width="200"/> | {gt_category} | {idx_to_class[top1]} | {top1_prob} | {idx_to_class[top2]} | {top2_prob} |')

        

if __name__ == '__main__':
    main()