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123 lines
3.6 KiB
123 lines
3.6 KiB
#!/usr/bin/env/ python
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# -*- coding: utf-8 -*-
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"""
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@Time : 2023/2/12 11:20
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@Author : 余半盏
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@File : rotate_captcha.py
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@Software: PyCharm
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"""
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import cv2
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import math
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import numpy as np
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from loguru import logger
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import time
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from utils.tool import cost_time
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def circle_point_px(img, accuracy_angle, r=None):
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rows, cols, _ = img.shape
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assert 360 % accuracy_angle == 0
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x0, y0 = r0, _ = (rows // 2, cols // 2)
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if r: r0 = r
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angles = np.arange(0, 360, accuracy_angle)
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cos_angles = np.cos(np.deg2rad(angles))
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sin_angles = np.sin(np.deg2rad(angles))
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x = x0 + r0 * cos_angles
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y = y0 + r0 * sin_angles
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x = np.round(x).astype(int)
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y = np.round(y).astype(int)
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circle_px_list = img[x, y]
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return circle_px_list
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def rotate(image, angle, center=None, scale=1.0): # 1
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(h, w) = image.shape[:2] # 2
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if center is None: # 3
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center = (w // 2, h // 2) # 4
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M = cv2.getRotationMatrix2D(center, angle, scale) # 5
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rotated = cv2.warpAffine(image, M, (w, h)) # 6
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return rotated
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def HSVDistance(c1, c2):
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"""
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计算两个颜色的 HSV（Hue, Saturation, Value）空间中的距离
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:param c1:
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:param c2:
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:return:
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"""
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y1 = 0.299 * c1[0] + 0.587 * c1[1] + 0.114 * c1[2]
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u1 = -0.14713 * c1[0] - 0.28886 * c1[1] + 0.436 * c1[2]
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v1 = 0.615 * c1[0] - 0.51498 * c1[1] - 0.10001 * c1[2]
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y2 = 0.299 * c2[0] + 0.587 * c2[1] + 0.114 * c2[2]
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u2 = -0.14713 * c2[0] - 0.28886 * c2[1] + 0.436 * c2[2]
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v2 = 0.615 * c2[0] - 0.51498 * c2[1] - 0.10001 * c2[2]
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rlt = math.sqrt((y1 - y2) * (y1 - y2) + (u1 - u2) * (u1 - u2) + (v1 - v2) * (v1 - v2))
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return rlt
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def crop_to_square(image):
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height, width = image.shape[:2]
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size = min(height, width)
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start_y = (height - size) // 2
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start_x = (width - size) // 2
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cropped = image[start_y:start_y+size, start_x:start_x+size]
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return cropped
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@cost_time
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def single_discern(inner_image_brg:bytes, outer_image_brg:bytes):
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inner_image = cv2.cvtColor(inner_image_brg, cv2.COLOR_BGR2HSV) # 颜色转换
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outer_image = cv2.cvtColor(outer_image_brg, cv2.COLOR_BGR2HSV)
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outer_image = crop_to_square(outer_image)
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all_deviation = []
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for result in range(0, 360):
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inner = rotate(inner_image, -result) # 顺时针
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outer = rotate(outer_image, 0)
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inner_circle_point_px = circle_point_px(inner, 1, 95)
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outer_circle_point_px = circle_point_px(outer, 1, 105)
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total_deviation = 0
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for i in range(len(inner_circle_point_px)):
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in_px = inner_circle_point_px[i]
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out_px = outer_circle_point_px[i]
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deviation = HSVDistance(in_px, out_px)
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total_deviation += deviation
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all_deviation.append(total_deviation)
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result = all_deviation.index(min(all_deviation))
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return result
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def export_single_discern(fg_path, bg_path):
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"""
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对于下载的图片转为content处理
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:param fg_path:
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:param bg_path:
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:return:
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"""
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if isinstance(fg_path, str):
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with open(fg_path, "rb") as f:
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inner_image_brg = f.read()
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with open(bg_path, "rb") as f:
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outer_image_brg = f.read()
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else:
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inner_image_brg = fg_path
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outer_image_brg = bg_path
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image = np.asarray(bytearray(inner_image_brg), dtype="uint8")
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inner_image_brg = cv2.imdecode(image, cv2.IMREAD_COLOR)
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image = np.asarray(bytearray(outer_image_brg), dtype="uint8")
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outer_image_brg = cv2.imdecode(image, cv2.IMREAD_COLOR)
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result = single_discern(inner_image_brg, outer_image_brg)
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return result
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if __name__ == '__main__':
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export_single_discern('./tmp/fg_2.png', './tmp/bg_2.png') # 310
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