快速照片扫描方法记录

import cv2
import numpy
import os

def cv_imread(file_path):
    cv_img = cv2.imdecode(numpy.fromfile(file_path, dtype=numpy.uint8), -1)
    return cv_img

def cv_imwrite(path ,img):
    suffix = os.path.splitext(path)[-1]
    cv2.imencode(suffix, img)[1].tofile(path)

Path = r"C:/Users/24385/Pictures/ControlCenter4/Scan/"

# 参数 根据自己的情况更改
kernelSize = 150
hsv_low = numpy.array([0, 0, 0])
hsv_high = numpy.array([255, 255, 245])

for fileName in os.listdir(Path):
    img = cv_imread(Path + fileName)
    padding = int(img.shape[1]/25)
    img = cv2.copyMakeBorder(img, padding, padding, padding, padding,
        cv2.BORDER_CONSTANT, value=[255, 255, 255])
        
    dst = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) # BGR转HSV
    dst = cv2.inRange(dst, hsv_low, hsv_high) # 通过HSV的高低阈值，提取图像部分区域

    # 开运算 先腐蚀再膨胀 去除毛刺
    kernel = numpy.ones((kernelSize, kernelSize), dtype=numpy.uint8)
    dst = cv2.morphologyEx(dst, cv2.MORPH_OPEN, kernel, 3)

    img_debug = img.copy()
    line_width = int(img.shape[1]/100)

    # 找边缘
    contours, hierarchy = cv2.findContours(dst, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    # 面积最大的区域
    c = max(contours, key = cv2.contourArea)

    
    # 用蓝色画出边缘
    cv2.drawContours(img_debug, contours, -1, (255, 0, 0), line_width)

    # 找出可包住面积最大区域的方框
    x, y, w, h = cv2.boundingRect(c)
    # 用绿色绘制方框
    cv2.rectangle(img_debug,(x, y), (x + w, y + h), (0, 255, 0), line_width)

    # 找出可包住面积最大区域的最小方框 红色绘制
    rect = cv2.minAreaRect(c)
    box = cv2.boxPoints(rect)
    box = numpy.int0(box)
    cv2.drawContours(img_debug, [box], 0, (0, 0, 255), line_width)

    # 计算图片倾斜角度
    angle = rect[2]
    if angle < -45:
        angle = 90 + angle

    # 设定红框中心为旋转轴心 防止照片位置偏太多导致转出图片
    w = box[0][0] + box[1][0] + box[2][0] + box[3][0]
    h = box[0][1] + box[1][1] + box[2][1] + box[3][1]
    center = (w // 4, h // 4)

    # 计算旋转矩阵
    M = cv2.getRotationMatrix2D(center, angle, 1.0)


    # 旋转图片
    (h, w) = img.shape[:2]
    rotated = cv2.warpAffine(img_debug, M, (w, h),
        flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_CONSTANT)
    img_final = cv2.warpAffine(img, M, (w, h),
        flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_CONSTANT)

    # 旋转红框坐标
    pts = numpy.int0(cv2.transform(numpy.array([box]), M))[0]

    # 计算旋转后红框的范围
    y_min = min(pts[0][0], pts[1][0], pts[2][0], pts[3][0])
    y_max = max(pts[0][0], pts[1][0], pts[2][0], pts[3][0])
    x_min = min(pts[0][1], pts[1][1], pts[2][1], pts[3][1])
    x_max = max(pts[0][1], pts[1][1], pts[2][1], pts[3][1])

    # 裁切图片
    img_crop = rotated[x_min:x_max, y_min:y_max]
    img_final = img_final[x_min-20:x_max+20, y_min-20:y_max+20]
    # cv2.namedWindow('show',0)
    # cv2.imshow('show', img_final)
    # cv2.waitKey(0)
    cv_imwrite(Path+"Cut_"+fileName,img_final)