| import glob | |
| import os | |
| import time | |
| from collections import OrderedDict | |
| import numpy as np | |
| import cv2 | |
| import matplotlib.pyplot as plt | |
| from natsort import natsort | |
| from tqdm import tqdm | |
| def fiFindByWildcard(wildcard): | |
| return natsort.natsorted(glob.glob(wildcard, recursive=True)) | |
| if __name__ == "__main__": | |
| out_data_path = fiFindByWildcard("./results_crop (1)/out/*") | |
| gt_data_path = fiFindByWildcard("./results_crop (1)/target/*") | |
| source_data_path = fiFindByWildcard("./results_crop (1)/source/*") | |
| for src_path, out_path, gt_path in tqdm(list(zip(source_data_path, out_data_path, gt_data_path))): | |
| fig, (ax1, ax2, ax3) = plt.subplots(1, 3) | |
| ax1.set_title("Bicubic") | |
| ax2.set_title("Baseline") | |
| ax3.set_title("Ground truth") | |
| src = cv2.imread(src_path)[:, :, [2, 1, 0]] | |
| out = cv2.imread(out_path)[:, :, [2, 1, 0]] | |
| gt = cv2.imread(gt_path)[:, :, [2, 1, 0]] | |
| src = cv2.resize(src, None, fx=4, fy=4, interpolation=cv2.INTER_CUBIC) | |
| ax1.set_yticklabels([]) | |
| ax1.set_xticklabels([]) | |
| ax2.set_yticklabels([]) | |
| ax2.set_xticklabels([]) | |
| ax3.set_yticklabels([]) | |
| ax3.set_xticklabels([]) | |
| ax1.imshow(src) | |
| ax2.imshow(out) | |
| ax3.imshow(gt) | |
| fig.savefig(f"./result_compare_crop_new/{os.path.basename(gt_path)}", bbox_inches='tight' , dpi=1200) | |
| plt.close() | |