python目標定位（借鑑csdn上大神）

寫博客是爲了記錄下來，畢竟好多東西記不住，看過就忘了，收藏又太多，還不如搬運到本身博客下面，隨時可翻~~~

近期再學目標識別與定位，看着原理都很簡單，可是真本身作，又以爲困難重重。

csdn上一個大神發了一個蟲子的定位切割程序，跑了一下效果不錯，所以記錄下來，能夠在此基礎上改進。

import cv2 import numpy as np def get_image(path): #獲取圖片
    img=cv2.imread(path) gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) return img, gray def Gaussian_Blur(gray): # 高斯去噪
    blurred = cv2.GaussianBlur(gray, (9, 9),0) return blurred def Sobel_gradient(blurred): # 索比爾算子來計算x、y方向梯度
    gradX = cv2.Sobel(blurred, ddepth=cv2.CV_32F, dx=1, dy=0) gradY = cv2.Sobel(blurred, ddepth=cv2.CV_32F, dx=0, dy=1) gradient = cv2.subtract(gradX, gradY) gradient = cv2.convertScaleAbs(gradient) return gradX, gradY, gradient def Thresh_and_blur(gradient):  #濾波，二值化
 blurred = cv2.GaussianBlur(gradient, (9, 9),0) (_, thresh) = cv2.threshold(blurred, 90, 255, cv2.THRESH_BINARY) return thresh def image_morphology(thresh):   #形態學，補齊邊緣
    # 創建一個橢圓核函數
    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (25, 25))    #返回指定形狀和尺寸的結構元素，
    # 定義一個25x25的橢圓形內核
    # 執行圖像形態學, 細節直接查文檔，很簡單
    closed = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)    #開運算，開運算即爲先腐蝕再膨脹，目的是消除白色點點
    closed = cv2.erode(closed, None, iterations=4)    #腐蝕
    closed = cv2.dilate(closed, None, iterations=4)   #膨脹

    return closed def findcnts_and_box_point(closed):  #尋找目標輪廓和中心點
    # 這裏opencv3返回的是三個參數
    (_, cnts, _) = cv2.findContours(closed.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) c = sorted(cnts, key=cv2.contourArea, reverse=True)[0]    #倒序排列 #cv2.contourArea是輪廓的面積，所以是按照面積由大到小的順序排序
    # compute the rotated bounding box of the largest contour
    rect = cv2.minAreaRect(c) #旋轉的邊界矩形，面積最小，返回值爲Box2D結構，分別爲左上角座標、寬和高，旋轉角度
    box = np.int0(cv2.boxPoints(rect)) #搭配cv2.minAreaRect函數，用於繪製旋轉邊界矩形
    return box def drawcnts_and_cut(original_img, box):   #畫輪廓
    # 由於這個函數有極強的破壞性，全部須要在img.copy()上畫
    # draw a bounding box arounded the detected barcode and display the image
    draw_img = cv2.drawContours(original_img.copy(), [box], -1, (0, 0, 255), 3)    #繪製全部輪廓
 Xs = [i[0] for i in box] Ys = [i[1] for i in box] x1 = min(Xs) x2 = max(Xs) y1 = min(Ys) y2 = max(Ys) hight = y2 - y1 width = x2 - x1 crop_img = original_img[y1:y1+hight, x1:x1+width] return draw_img, crop_img def walk(): img_path = r'F:\pycharm\test\iterable\cz.png' save_path = r'F:\pycharm\test\iterable\cz_save.png' original_img, gray = get_image(img_path) blurred = Gaussian_Blur(gray) gradX, gradY, gradient = Sobel_gradient(blurred) thresh = Thresh_and_blur(gradient) closed = image_morphology(thresh) box = findcnts_and_box_point(closed) draw_img, crop_img = drawcnts_and_cut(original_img,box) # 暴力一點，把它們都顯示出來看看
    cv2.imshow('original_img', original_img) cv2.imshow('blurred', blurred) cv2.imshow('gradX', gradX) cv2.imshow('gradY', gradY) cv2.imshow('final', gradient) cv2.imshow('thresh', thresh) cv2.imshow('closed', closed) cv2.imshow('draw_img', draw_img) cv2.imshow('crop_img', crop_img) cv2.waitKey(20171219) cv2.imwrite(save_path, crop_img) walk()

但願本身早日寫出實現功能的代碼。

原做網址爲：https://blog.csdn.net/sinat_36458870/article/details/78825571。

感謝。