commit 9a0e39a154072de65d34f48f9069b5733917cc07
Author: Miraitowa <3204824559@qq.com>
Date:   Mon Nov 25 17:35:39 2024 +0800

    上传文件至 书本图像的透视矫正

diff --git a/书本图像的透视矫正/test.py b/书本图像的透视矫正/test.py
new file mode 100644
index 0000000..adf0246
--- /dev/null
+++ b/书本图像的透视矫正/test.py
@@ -0,0 +1,71 @@
+# 图像的透视校正
+import cv2
+import numpy as np
+import math
+
+# 读入待处理的图像并显示
+img = cv2.imread("./data/shu3.jpg")
+cv2.imshow("1_yuanshituxima", img)
+
+# 灰度化 并显示
+img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+cv2.imshow("2.huidu", img_gray)
+
+# 模糊化处理 去掉过小的细节
+blurred = cv2.GaussianBlur(img_gray, (5, 5), 0)
+cv2.imshow("3.mohu", blurred)
+
+# 膨胀-抖小的细节合并
+dilate = cv2.dilate(blurred, (3, 3))
+cv2.imshow("4_pengzhang", dilate)
+
+# 边缘提取
+canny = cv2.Canny(dilate, 50, 240)
+cv2.imshow("5_bianyuntiqu", canny)
+
+# 轮廓检测
+imag, cnts, hie = cv2.findContours(canny.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+# 绘制轮廓
+img_cnt = cv2.drawContours(img.copy(), cnts, -1, (0, 0, 255), 2)
+cv2.imshow("6_lunkuxian", img_cnt)
+
+docCnt = None  # 定义一个空数组
+
+# 计算面积, 排序
+if len(cnts) > 0:
+    cnts = sorted(cnts, key=cv2.contourArea, reverse=True)
+    for c in cnts:
+        peri = cv2.arcLength(c, True)  # 求出该轮廓线的周长
+        approx = cv2.approxPolyDP(c, 0.02 * peri, True)  # 轮廓线的多边形组合
+        if len(approx) == 4:  # 找到边为4的多边形
+            docCnt = approx  # 将找到的多边形赋值给另外一个变量docCnt
+            break
+
+# 绘制找到的四边形的点,画圆
+points = []
+for peak in docCnt:
+    peak = peak[0]
+    print("peak:", peak)
+    cv2.circle(img_cnt, tuple(peak), 10, (0, 255, 0), 2)  # 圆所在的图像, 圆心, 半径, 颜色, 线宽
+    points.append(peak)
+
+cv2.imshow("7-sibianxingdingdian", img_cnt)
+print("points:", points)
+
+# 校正
+# 原纸张逆时针方向的4个角点
+src = np.float32([points[0], points[1], points[2], points[3]])
+
+# 根据勾股定理计算宽度,再做透视变换
+h = int(math.sqrt((points[1][0] - points[0][0]) ** 2 + (points[1][1] - points[0][1]) ** 2))  # 高度
+w = int(math.sqrt((points[2][0] - points[1][0]) ** 2 + (points[2][1] - points[1][1]) ** 2))  # 宽度
+print("w, h", w, h)
+
+dst = np.float32([[0, 0], [0, h], [w, h], [w, 0]])
+M = cv2.getPerspectiveTransform(src, dst)  # 生成透视矩阵
+result = cv2.warpPerspective(img.copy(), M, (w, h))  # 透视变换
+
+cv2.imshow("8_leguo", result)
+cv2.waitKey()
+cv2.destroyAllWindows()
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