一、查找圖像輪廓
- opencv-python中查找圖像輪廓的API為：findContours函數 該函數接受二值圖作為參數，根據參數，可查找物體外輪廓、內外輪廓，保存輪廓點、壓縮等等...
- 如：contours, hierarchy = cv2.findContours(binary,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
def findContours(image, mode, method, contours=None, hierarchy=None, offset=None): # real signature unknown; restored from __doc__
"""
findContours(image, mode, method[, contours[, hierarchy[, offset]]]) -> contours, hierarchy
. @brief Finds contours in a binary image.
.
. The function retrieves contours from the binary image using the algorithm @cite Suzuki85 . The contours
. are a useful tool for shape analysis and object detection and recognition. See squares.cpp in the
. OpenCV sample directory.
. @note Since opencv 3.2 source image is not modified by this function.
.
. @param image Source, an 8-bit single-channel image. Non-zero pixels are treated as 1's. Zero
. pixels remain 0's, so the image is treated as binary . You can use #compare, #inRange, #threshold ,
. #adaptiveThreshold, #Canny, and others to create a binary image out of a grayscale or color one.
. If mode equals to #RETR_CCOMP or #RETR_FLOODFILL, the input can also be a 32-bit integer image of labels (CV_32SC1).
. @param contours Detected contours. Each contour is stored as a vector of points (e.g.
. std::vector<std::vector<cv::Point> >).
. @param hierarchy Optional output vector (e.g. std::vector<cv::Vec4i>), containing information about the image topology. It has
. as many elements as the number of contours. For each i-th contour contours[i], the elements
. hierarchy[i][0] , hierarchy[i][1] , hierarchy[i][2] , and hierarchy[i][3] are set to 0-based indices
. in contours of the next and previous contours at the same hierarchical level, the first child
. contour and the parent contour, respectively. If for the contour i there are no next, previous,
. parent, or nested contours, the corresponding elements of hierarchy[i] will be negative.
. @param mode Contour retrieval mode, see #RetrievalModes
. @param method Contour approximation method, see #ContourApproximationModes
. @param offset Optional offset by which every contour point is shifted. This is useful if the
. contours are extracted from the image ROI and then they should be analyzed in the whole image
. context.
"""
pass
| 參數 | 作用 |
|---|---|
| cv2.RETR_EXTERNAL | 只查找外輪廓 |
| cv2.RETR_LIST | 檢測所有輪廓,保存到一個arry(鏈表) |
| cv2.RETR_CCOMP | 建立兩個等級的輪廓(外/內),只組織兩層 |
| cv2.RETR_TREE | 檢測所有輪廓,重構嵌套輪廓全部層次 |
| cv2.CHAIN_APPROX_NONE | 存儲所有邊界點 |
| cv2.CHAIN_APPROX_SIMPLE | 壓縮垂直、水平、對角方向，只保留端點 |
| cv2.CHAIN_APPROX_TX89_L1 | 使用teh-Chini近似算法 |
| cv2.CHAIN_APPROX_TC89_KCOS | 使用teh-Chini近似算法 |
cv2.drawContours(image, contours, contourIdx, color[, thickness[, lineType[, hierarchy[, maxLevel[, offset ]]]]])
第一個參數是指明在哪幅圖像上繪制輪廓；
第二個參數是輪廓本身，在Python中是一個list。
第三個參數指定繪制輪廓list中的哪條輪廓，如果是-1，則繪制其中的所有輪廓。后面的參數很簡單。其中thickness表明輪廓線的寬度，如果是-1（cv2.FILLED），則為填充模式
二、外接矩形
#找到輪廓 contours, hierarchy = cv2.findContours(binary,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
contours多維數組，包含多個輪廓cnt
x, y, w, h = cv2.boudingrect(cnt) # 獲得外接矩形
參數說明：x，y, w, h 分別表示外接矩形的x軸和y軸的坐標，以及矩形的寬和高， cnt表示輸入的輪廓值