api_py/utils/rotate_captcha.py

#!/usr/bin/env/ python
# -*- coding: utf-8 -*-
"""
@Time    : 2023/2/12 11:20
@Author  : 余半盏
@File    : rotate_captcha.py
@Software: PyCharm
"""
import cv2
import math
import numpy as np
from loguru import logger
import time

from utils.tool import cost_time


def circle_point_px(img, accuracy_angle, r=None):
    rows, cols, _ = img.shape
    assert 360 % accuracy_angle == 0
    x0, y0 = r0, _ = (rows // 2, cols // 2)
    if r: r0 = r
    angles = np.arange(0, 360, accuracy_angle)
    cos_angles = np.cos(np.deg2rad(angles))
    sin_angles = np.sin(np.deg2rad(angles))

    x = x0 + r0 * cos_angles
    y = y0 + r0 * sin_angles

    x = np.round(x).astype(int)
    y = np.round(y).astype(int)

    circle_px_list = img[x, y]
    return circle_px_list


def rotate(image, angle, center=None, scale=1.0):  # 1
    (h, w) = image.shape[:2]  # 2
    if center is None:  # 3
        center = (w // 2, h // 2)  # 4
    M = cv2.getRotationMatrix2D(center, angle, scale)  # 5
    rotated = cv2.warpAffine(image, M, (w, h))  # 6
    return rotated


def HSVDistance(c1, c2):
    """
    计算两个颜色的 HSV（Hue, Saturation, Value）空间中的距离
    :param c1:
    :param c2:
    :return:
    """
    y1 = 0.299 * c1[0] + 0.587 * c1[1] + 0.114 * c1[2]
    u1 = -0.14713 * c1[0] - 0.28886 * c1[1] + 0.436 * c1[2]
    v1 = 0.615 * c1[0] - 0.51498 * c1[1] - 0.10001 * c1[2]
    y2 = 0.299 * c2[0] + 0.587 * c2[1] + 0.114 * c2[2]
    u2 = -0.14713 * c2[0] - 0.28886 * c2[1] + 0.436 * c2[2]
    v2 = 0.615 * c2[0] - 0.51498 * c2[1] - 0.10001 * c2[2]
    rlt = math.sqrt((y1 - y2) * (y1 - y2) + (u1 - u2) * (u1 - u2) + (v1 - v2) * (v1 - v2))
    return rlt


def crop_to_square(image):
    height, width = image.shape[:2]
    size = min(height, width)
    start_y = (height - size) // 2
    start_x = (width - size) // 2
    cropped = image[start_y:start_y+size, start_x:start_x+size]
    return cropped


@cost_time
def single_discern(inner_image_brg:bytes, outer_image_brg:bytes):
    inner_image = cv2.cvtColor(inner_image_brg, cv2.COLOR_BGR2HSV)  # 颜色转换
    outer_image = cv2.cvtColor(outer_image_brg, cv2.COLOR_BGR2HSV)
    outer_image = crop_to_square(outer_image)
    all_deviation = []
    for result in range(0, 360):
        inner = rotate(inner_image, -result)  # 顺时针
        outer = rotate(outer_image, 0)
        inner_circle_point_px = circle_point_px(inner, 1, 95)
        outer_circle_point_px = circle_point_px(outer, 1, 105)
        total_deviation = 0
        for i in range(len(inner_circle_point_px)):
            in_px = inner_circle_point_px[i]
            out_px = outer_circle_point_px[i]
            deviation = HSVDistance(in_px, out_px)
            total_deviation += deviation
        all_deviation.append(total_deviation)
    result = all_deviation.index(min(all_deviation))

    return result


def export_single_discern(fg_path, bg_path):
    """
    对于下载的图片转为content处理
    :param fg_path:
    :param bg_path:
    :return:
    """
    if isinstance(fg_path, str):
        with open(fg_path, "rb") as f:
            inner_image_brg = f.read()
        with open(bg_path, "rb") as f:
            outer_image_brg = f.read()
    else:
        inner_image_brg = fg_path
        outer_image_brg = bg_path

    image = np.asarray(bytearray(inner_image_brg), dtype="uint8")
    inner_image_brg = cv2.imdecode(image, cv2.IMREAD_COLOR)

    image = np.asarray(bytearray(outer_image_brg), dtype="uint8")
    outer_image_brg = cv2.imdecode(image, cv2.IMREAD_COLOR)

    result = single_discern(inner_image_brg, outer_image_brg)
    return result



if __name__ == '__main__':
    export_single_discern('./tmp/fg_2.png', './tmp/bg_2.png') # 310