获取滑动缺口的距离

使用ddddocr(源码使用是的cv2)

import ddddocr
import numpy as np
from base64 import b64decode

slide = ddddocr.DdddOcr(det=False, ocr=False)


with open('target.png', 'rb') as f:
    target_bytes = f.read()
with open('background.jpeg', 'rb') as f:
    background_bytes = f.read()

# 217
t_image = 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V/hj6vyH/L0H+Cz+q6m9d662pAAAAAElFTkSuQmCC"
b_image = 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"

background_bytes = np.frombuffer(b64decode(b_image), dtype="uint8")
target_bytes = np.frombuffer(b64decode(t_image), dtype="uint8")

res = slide.slide_match(target_bytes, background_bytes, simple_target=True)
print(res)

使用cv2

import cv2
import numpy as np
from base64 import b64encode, b64decode


def get_distance(slider_image, bg_image):
    ''' 获取缺口位置
    '''
    distance = 0
    try:
        # 滑块处理
        b_image = np.frombuffer(b64decode(slider_image), dtype="uint8")
        # b_image = np.frombuffer(slider_image, dtype="uint8")
        target_rgb = cv2.imdecode(b_image, cv2.IMREAD_COLOR)
        target_gray = cv2.cvtColor(target_rgb, cv2.COLOR_BGR2GRAY)

        # 背景图片处理
        template = np.frombuffer(b64decode(bg_image), dtype="uint8")
        # template = np.frombuffer(bg_image, dtype="uint8")
        template_rgb = cv2.imdecode(template, cv2.IMREAD_COLOR)
        template_gray = cv2.cvtColor(template_rgb, cv2.COLOR_BGR2GRAY)

        # 距离计算
        res = cv2.matchTemplate(target_gray, template_gray, cv2.TM_CCOEFF_NORMED)
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
        print(min_val, max_val, min_loc, max_loc )
        # if abs(1 - min_val) <= abs(1 - max_val):
            # distance = min_loc[0]
        # else:
            # distance = max_loc[0]
    except Exception as e:
        print(e)

    return distance
posted @   二二二狗子  阅读(231)  评论(0编辑  收藏  举报
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