91 lines
2.3 KiB
Python
91 lines
2.3 KiB
Python
import logging
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from PIL import Image, ImageFilter
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import scipy.signal
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import numpy as np
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logging.getLogger(__name__)
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sobel_x_kernel = np.array((
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(1, 0, -1),
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(2, 0, -2),
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(1, 0, -1)
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))
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sobel_y_kernel = np.transpose(sobel_x_kernel)
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def difference_of_gaussians(img: Image.Image, blur_strength_1: float | None = 1.0, blur_strength_2: float | None = 1.2, threshold: int | None = 128*3) -> Image.Image:
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blur_1 = img.filter(ImageFilter.GaussianBlur(blur_strength_1))
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blur_2 = img.filter(ImageFilter.GaussianBlur(blur_strength_2))
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w, h = img.size
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dog = Image.new(img.mode, img.size)
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for pixel_y in range(h):
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for pixel_x in range(w):
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coords = (pixel_x, pixel_y)
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p1 = blur_1.getpixel(coords)
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p2 = blur_2.getpixel(coords)
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p1 = np.array(p1)
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p2 = np.array(p2)
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new_pixel = p2 - p1
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# if new_pixel.sum() < threshold:
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# new_pixel = np.zeros(3).astype(np.uint8)
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dog.putpixel(coords, tuple(new_pixel.tolist()))
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return dog
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def sobel(img: Image.Image, gradient_threshold: int | None = 20) -> tuple[Image.Image, np.ndarray]:
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logging.debug(img.size)
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img = img.convert('L')
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img.save('debug/test-L.png')
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logging.debug('Sobel Operator')
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logging.debug(img.size)
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pixels = np.array(img)
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logging.debug(f'pixels size: {pixels.size}')
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dx = scipy.signal.correlate(pixels, sobel_x_kernel, mode='same')
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dy = scipy.signal.correlate(pixels, sobel_y_kernel, mode='same')
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logging.debug(f'dx size: {dx.size}')
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edges = np.sqrt(np.square(dx) + np.square(dy))
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edges[edges>255] = 255
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logging.debug(f'edges size: {edges.size}')
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gradient = np.arctan2(dy.flatten(), dx.flatten())
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gradient = np.absolute(gradient)
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print(gradient)
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print(np.average(gradient))
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gradient[gradient > gradient_threshold] = 0
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pil_edges = edges.astype(np.uint8)
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newimg = Image.fromarray(pil_edges, mode='L')
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logging.debug(f'New Img Size: {newimg.size}')
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return (newimg, gradient)
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def average_colors(colors: list) -> tuple:
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colors = np.array(colors)
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np.average(colors)
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sum = np.zeros(len(colors[0]))
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for c in colors:
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sum += c
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sum /= len(colors)
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return tuple(sum.astype(np.uint8).tolist())
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