Created
April 22, 2024 08:58
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import cv2 | |
import numpy as np | |
import svgwrite | |
def find_and_vectorize_edges(image_path, K): | |
# Шаг 1: Уменьшение количества цветов | |
img = cv2.imread(image_path) | |
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) | |
Z = img.reshape((-1, 3)) | |
Z = np.float32(Z) | |
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0) | |
_, label, center = cv2.kmeans(Z, K, None, criteria, 10, cv2.KMEANS_RANDOM_CENTERS) | |
center = np.uint8(center) | |
res = center[label.flatten()] | |
reduced_img = res.reshape((img.shape)) | |
# Шаг 2: Обнаружение границ | |
edges = cv2.Canny(cv2.cvtColor(reduced_img, cv2.COLOR_RGB2GRAY), 50, 150) | |
# Шаг 3: Нахождение контуров и создание SVG | |
contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) | |
dwg = svgwrite.Drawing('vectorized_image.svg', profile='tiny') | |
# Аппроксимация контуров и запись в SVG | |
for cnt in contours: | |
epsilon = 0.02 * cv2.arcLength(cnt, True) | |
approx = cv2.approxPolyDP(cnt, epsilon, True) | |
points = ['{},{}'.format(point[0][0], point[0][1]) for point in approx] | |
polyline = dwg.polyline(points=points, stroke='black', fill='none') | |
dwg.add(polyline) | |
dwg.save() | |
return dwg.tostring() | |
# Путь к изображению и количество цветов | |
image_path = 'path_to_your_image.jpg' | |
K = 8 | |
# Генерация SVG | |
svg_output = find_and_vectorize_edges(image_path, K) | |
print(svg_output) |
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