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b/usage/plotter.py |
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import matplotlib.pyplot as plt |
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import cv2 |
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import numpy as np |
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im_path = 'train_15/ref_Training_phase_1_003.png' |
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img = np.transpose(cv2.imread(im_path),[1,0,2]) |
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img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) |
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t_w = img.shape[0] |
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w = img.shape[0]//5 |
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slide = img[4*w:t_w,:,:] |
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gt = img[3*w:4*w,:,:] |
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prob_map = img[1*w:2*w,:,:] |
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prob_map = np.mean(prob_map, axis=2) |
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prob_map/=255 |
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pred = img[2*w:3*w,:,:] |
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# raise ValueError |
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fig, ax = plt.subplots(2, 2, figsize=(24, 24)) |
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fig.tight_layout() |
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im_ = ax[0][0].imshow(slide) |
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ax[0][0].set_xticklabels([]) |
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ax[0][0].set_yticklabels([]) |
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ax[0][0].set_xticks([]) |
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ax[0][0].set_yticks([]) |
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ax[0][0].set_aspect('equal') |
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ax[0][0].tick_params(bottom='off', top='off', labelbottom='off', right='off', left='off', labelleft='off' ) |
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# ax[0][0].title.set_text("WSI Slide") |
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gt_ = ax[0][1].imshow(gt,cmap='gray') |
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ax[0][1].set_xticklabels([]) |
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ax[0][1].set_yticklabels([]) |
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ax[0][1].set_xticks([]) |
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ax[0][1].set_yticks([]) |
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ax[0][1].set_aspect('equal') |
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ax[0][1].tick_params(bottom='off', top='off', labelbottom='off', right='off', left='off', labelleft='off' ) |
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# ax[0][1].title.set_text("Ground Truth") |
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pred_ = ax[1][1].imshow(pred,cmap='gray') |
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ax[1][1].set_xticklabels([]) |
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ax[1][1].set_yticklabels([]) |
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ax[1][1].set_xticks([]) |
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ax[1][1].set_yticks([]) |
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ax[1][1].set_aspect('equal') |
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ax[1][1].tick_params(bottom='off', top='off', labelbottom='off', right='off', left='off', labelleft='off' ) |
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# ax[1][1].title.set_text("Ground Truth") |
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prob_map_ = ax[1][0].imshow(prob_map, cmap=plt.cm.jet) |
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ax[1][0].set_xticklabels([]) |
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ax[1][0].set_yticklabels([]) |
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ax[1][0].set_xticks([]) |
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ax[1][0].set_yticks([]) |
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ax[1][0].set_aspect('equal') |
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ax[1][0].tick_params(bottom='off', top='off', labelbottom='off', right='off', left='off', labelleft='off' ) |
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# ax[1][0].title.set_text("Probability Map") |
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cax = fig.add_axes([ax[1][0].get_position().x1 + 0.01, |
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ax[1][0].get_position().y0, |
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0.01, |
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ax[1][0].get_position().y1-ax[1][0].get_position().y0]) |
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fig.colorbar(prob_map_, cax=cax) |
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plt.savefig('characteristic-plots/im2.png',bbox_inches = 'tight',pad_inches = 0.1) |