Anchor_image_computation.py
d5e2a6155c22master

Anchor_image_computation.py
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			#%%

			import matplotlib.pyplot as plt
			import numpy as np
			from PIL import Image
			import glob



			#%%

			path = ...\Data\.. # use your path
			all_files = glob.glob(path + "/*.png")
			ims = []
			for filename in all_files:
			print(filename)
			ims.append(Image.open(filename, mode='r'))


			ims = np.array([np.array(im) for im in ims])
			imave = np.average(ims,axis=0)
			print(imave.shape)

			result = Image.fromarray(imave.astype('uint8'))

			result.save('C:/Users/srpv/Desktop/C4 Science/DED Contrastive Learning/Semi supervised/Data/Anchor/Normal/result.png')

			plt.figure(figsize=(20,4))
			plt.imshow(np.transpose(result, (0, 1, 2)))