| import matplotlib.pyplot as plt
|
| import numpy as np
|
| from PIL import Image
|
| import argparse
|
|
|
| parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
|
| parser.add_argument('--image', type=str, help='input image')
|
| parser.add_argument('--output', type=str, help='output file')
|
| parser.add_argument('--mask', type=str, default='', help='ground truth mask (optional)')
|
| args = parser.parse_args()
|
|
|
| image_path = args.image
|
| output_path = args.output
|
| mask_path = args.mask
|
|
|
| result = np.load(output_path)
|
|
|
| cols = 3
|
| if mask_path != '':
|
| cols += 1
|
| mask = Image.open(mask_path)
|
| else:
|
| mask = None
|
|
|
| if 'np++' in result:
|
| cols += 1
|
| noisepr = result['np++']
|
| else:
|
| noisepr = None
|
|
|
| fig, axs = plt.subplots(1, cols)
|
| fig.suptitle('score: %.3f' % result['score'])
|
|
|
| for ax in axs:
|
| ax.axis('off')
|
|
|
| index = 0
|
| ax = axs[index]
|
| ax.imshow(Image.open(image_path)), ax.set_title('Image')
|
|
|
| if mask is not None:
|
| index += 1
|
| ax = axs[index]
|
| ax.imshow(mask, cmap='gray'), ax.set_title('Ground Truth')
|
| ax.set_yticks(list()), ax.set_xticks(list()), ax.axis('on')
|
|
|
| if noisepr is not None:
|
| index += 1
|
| ax = axs[index]
|
|
|
| ax.imshow(noisepr[16:-16:5, 16:-16:5], cmap='gray'), ax.set_title('Noiseprint++')
|
|
|
| index += 1
|
| ax = axs[index]
|
| ax.imshow(result['map'], cmap='RdBu_r', clim=[0,1]), ax.set_title('Localization map')
|
|
|
| index += 1
|
| ax = axs[index]
|
| ax.imshow(result['conf'], cmap='gray', clim=[0,1]), ax.set_title('Confidence map')
|
| ax.set_yticks(list()), ax.set_xticks(list()), ax.axis('on')
|
|
|
| plt.show()
|
|
|
