46 lines
1.3 KiB
Python
46 lines
1.3 KiB
Python
import numpy as np
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from matplotlib import pyplot as plt, gridspec
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def plot_two_images(a: np.ndarray, b: np.ndarray):
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plt.figure(figsize=[10, 10])
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plt.subplot(121)
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plt.imshow(a)
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plt.title("A")
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plt.subplot(122)
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plt.imshow(b)
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plt.title("B")
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plt.show()
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def plot_results(source, source_anime, results, anime_faces_set, method):
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cols = len(results)
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plt.figure(figsize=[3*cols, 7])
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gs = gridspec.GridSpec(2, cols)
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plt.subplot(gs[0, cols // 2 - 1])
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plt.imshow(source)
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plt.title('Your image')
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plt.axis('off')
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plt.subplot(gs[0, cols // 2])
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plt.imshow(source_anime)
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plt.title('Your image in Anime style')
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plt.axis('off')
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plt.figtext(0.5, 0.525, "Predictions", ha="center", va="top", fontsize=16)
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for idx, prediction in enumerate(results):
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result_img = anime_faces_set['values'][anime_faces_set['labels'].index(prediction['name'])]
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plt.subplot(gs[1, idx])
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plt.imshow(result_img, interpolation='bicubic')
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plt.title(f'{prediction["name"].partition(".")[0]}, score={str(round(prediction["score"], 4))}')
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plt.axis('off')
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plt.tight_layout()
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plt.figtext(0.5, 0.01, f"Metric: {method}", ha="center", va="bottom", fontsize=12)
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plt.subplots_adjust(wspace=0, hspace=0.1)
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plt.show()
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