forked from s444420/AL-2020
29 lines
582 B
Python
29 lines
582 B
Python
import numpy as np
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from PIL import Image
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import matplotlib.pyplot as plt
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import cv2
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img = cv2.cvtColor(cv2.imread('test.jpg'), cv2.COLOR_BGR2GRAY)
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img = cv2.GaussianBlur(img, (15, 15), 0) # poprawia jakosc
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img = cv2.resize(img, (8, 8), interpolation=cv2.INTER_AREA)
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print(type(img))
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print(img.shape)
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print(img)
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plt.imshow(img ,cmap='binary')
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plt.show()
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data = []
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rows, cols = img.shape
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for i in range(rows):
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for j in range(cols):
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k = img[i, j]
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if k > 200:
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k = 0 # brak czarnego
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else:
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k = 1
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data.append(k)
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print(data) |