add 71~75

Author: JimmyHHua

README.md

@@ -109,3 +109,8 @@ code_067 | [Top Hat](python/code_067/opencv_067.py)   | ✔️
 code_068 | [Black Hat](python/code_068/opencv_068.py)   | ✔️
 code_069 | [Morph Gradient](python/code_069/opencv_069.py)   | ✔️
 code_070 | [Contour based on Morph Gradient](python/code_070/opencv_070.py)   | ✏️
+code_071 | [Hit and Miss](python/code_071/opencv_071.py)   | ✔️
+code_072 | [Defect Detecting-1](python/code_072/opencv_072.py)   | ✔️
+code_073 | [Defect Detecting-2](python/code_073/opencv_073.py)   | ✔️
+code_074 | [Extract the Maximum Contour and Coding Key Points](python/code_074/opencv_074.py)   | ✔️
+code_075 | [Image Inpainting](python/code_075/opencv_075.py)   | ✔️

README_CN.md

@@ -108,3 +108,8 @@ code_067 | [顶帽](python/code_067/opencv_067.py)   | ✔️
 code_068 | [黑帽](python/code_068/opencv_068.py)   | ✔️
 code_069 | [图像梯度](python/code_069/opencv_069.py)   | ✔️
 code_070 | [基于梯度的轮廓发现](python/code_070/opencv_070.py)   | ✏️
+code_071 | [击中击不中](python/code_071/opencv_071.py)   | ✔️
+code_072 | [缺陷检测1](python/code_072/opencv_072.py)   | ✔️
+code_073 | [缺陷检测2](python/code_073/opencv_073.py)   | ✔️
+code_074 | [提取最大轮廓和编码关键点](python/code_074/opencv_074.py)   | ✔️
+code_075 | [图像修复](python/code_075/opencv_075.py)   | ✔️

python/code_071/binary2.png

@@ -0,0 +1,21 @@
+import cv2 as cv
+import numpy as np
+
+src = cv.imread("cross.png")
+cv.namedWindow("input", cv.WINDOW_AUTOSIZE)
+cv.imshow("input", src)
+
+# Binary image
+gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
+ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY_INV | cv.THRESH_OTSU)
+
+# Hit and Miss
+se = cv.getStructuringElement(cv.MORPH_CROSS, (12, 12))
+binary = cv.morphologyEx(binary, cv.MORPH_HITMISS, se)
+
+
+cv.imshow("hit miss", binary)
+cv.imwrite("binary2.png", binary)
+
+cv.waitKey(0)
+cv.destroyAllWindows()

python/code_071/cross.png

@@ -0,0 +1,66 @@
+#### 二值图像分析 – 缺陷检测
+
+1. 观察图像与提取图像ROI对象轮廓外接矩形与轮廓.
+```python
+# Get contours
+_, contours, hierarchy = cv.findContours(binary, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
+height, width = src.shape[:2]
+for c in range(len(contours)):
+    x, y, w, h = cv.boundingRect(contours[c])
+    area = cv.contourArea(contours[c])
+    if h > (height//2):
+        continue
+    if area < 150:
+        continue
+    cv.rectangle(src, (x, y), (x+w, y+h), (0, 0, 255), 1, 8, 0)
+    cv.drawContours(src, contours, c, (0, 255, 0), 2, 8)
+```
+<img src=ce_02.jpg width=300>
+<img src=binary2.png width=300>
+
+2. 对于得到的刀片外接矩形，首先需要通过排序，确定他们的编号.
+
+👀 [代码Code](../code_073/opencv_073.py)
+
+```
+# 排序轮廓
+rects = sorted(rects, key = lambda x:x[1])
+```
+3. 根据模板进行相减得到与模板不同的区域，对这些区域进行形态学操作，去掉边缘细微差异，最终就得到了可以检出的缺陷或者划痕刀片。
+
+```python
+# 获取模板
+def get_template(binary, boxes):
+    x, y, w, h = boxes[0]
+    roi = binary[y:y+h, x:x+w]
+    return roi
+
+# 缺陷检测函数
+def detect_defect(binary, boxes, tpl):
+    height, width = tpl.shape
+    index = 1
+    defect_rois = []
+    # 发现缺失
+    for x, y, w, h in boxes:
+        roi = binary[y:y + h, x:x + w]
+        roi = cv.resize(roi, (width, height))
+        mask = cv.subtract(tpl, roi)
+        se = cv.getStructuringElement(cv.MORPH_RECT, (5, 5), (-1, -1))
+        mask = cv.morphologyEx(mask, cv.MORPH_OPEN, se)
+        ret, mask = cv.threshold(mask, 0, 255, cv.THRESH_BINARY)
+        count = 0
+        for row in range(height):
+            for col in range(width):
+                pv = mask[row, col]
+                if pv == 255:
+                    count += 1
+        if count > 0:
+            defect_rois.append([x, y, w, h])
+        cv.imwrite("mask%d.png"%index, mask)
+        index += 1
+    return defect_rois
+
+```
+
+<img src=../code_073/ce_02.jpg width=300>
+<img src=../code_073/binary2.png width=300>

python/code_071/opencv_071.py

@@ -0,0 +1,33 @@
+import cv2 as cv
+import numpy as np
+
+src = cv.imread("ce_02.jpg")
+cv.namedWindow("input", cv.WINDOW_AUTOSIZE)
+cv.imshow("input", src)
+
+# get binary
+gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
+ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY_INV | cv.THRESH_OTSU)
+
+se = cv.getStructuringElement(cv.MORPH_RECT, (3, 3), (-1, -1))
+binary = cv.morphologyEx(binary, cv.MORPH_OPEN, se)
+cv.imshow("binary", binary)
+
+# Get contours
+_, contours, hierarchy = cv.findContours(binary, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
+height, width = src.shape[:2]
+for c in range(len(contours)):
+    x, y, w, h = cv.boundingRect(contours[c])
+    area = cv.contourArea(contours[c])
+    if h > (height//2):
+        continue
+    if area < 150:
+        continue
+    cv.rectangle(src, (x, y), (x+w, y+h), (0, 0, 255), 1, 8, 0)
+    cv.drawContours(src, contours, c, (0, 255, 0), 2, 8)
+
+cv.imshow("result", src)
+cv.imwrite("binary2.png", src)
+
+cv.waitKey(0)
+cv.destroyAllWindows()