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import cv2 |
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import numpy as np |
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from PIL import Image |
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class pixL: |
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def __init__(self,numOfSquaresW = None, numOfSquaresH= None, size = [False, (512,512)],square = 6,ImgH = None,ImgW = None,images = [],background_image = None): |
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self.images = images |
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self.size = size |
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self.ImgH = ImgH |
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self.ImgW = ImgW |
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self.square = square |
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self.numOfSquaresW = numOfSquaresW |
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self.numOfSquaresH = numOfSquaresH |
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def preprocess(self): |
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for image in self.images: |
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size = (image.shape[0] - (image.shape[0] % 4), image.shape[1] - (image.shape[1] % 4)) |
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image = cv2.resize(image, size) |
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image = cv2.cvtColor(image.astype(np.uint8), cv2.COLOR_BGR2RGB) |
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if len(self.images) == 1: |
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return self.images[0] |
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else: |
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return self.images |
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def toThePixL(self,images, pixel_size): |
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self.images = [] |
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self.square = pixel_size |
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for image in images: |
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image = Image.fromarray(image) |
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image = image.convert("RGB") |
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self.ImgW, self.ImgH = image.size |
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self.images.append(pixL.epicAlgorithm(self, image)) |
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return pixL.preprocess(self) |
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def numOfSquaresFunc(self): |
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self.numOfSquaresW = round((self.ImgW / self.square) + 1) |
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self.numOfSquaresH = round((self.ImgH / self.square) + 1) |
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def epicAlgorithm(self, image): |
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pixValues = [] |
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pixL.numOfSquaresFunc(self) |
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for j in range(1,self.numOfSquaresH): |
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for i in range(1,self.numOfSquaresW): |
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pixValues.append((image.getpixel(( |
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i * self.square - self.square//2, |
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j * self.square - self.square//2)), |
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(i * self.square - self.square//2, |
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j * self.square - self.square//2))) |
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background = 255 * np.ones(shape=[self.ImgH - self.square, |
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self.ImgW - self.square*2, 3], |
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dtype=np.uint8) |
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for pen in range(len(pixValues)): |
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cv2.rectangle(background, |
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pt1=(pixValues[pen][1][0] - self.square,pixValues[pen][1][1] - self.square), |
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pt2=(pixValues[pen][1][0] + self.square,pixValues[pen][1][1] + self.square), |
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color=(pixValues[pen][0][2],pixValues[pen][0][1],pixValues[pen][0][0]), |
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thickness=-1) |
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background = np.array(background).astype(np.uint8) |
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background = cv2.resize(background, (self.ImgW,self.ImgH), interpolation = cv2.INTER_AREA) |
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return background |
