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)))