python cv2 绘制不规则形状的最小外接矩形、最大内接矩形、最大内接圆、最小外接圆、拟合椭圆

2023-08-01 05:21| 来源: 网络整理| 查看: 265

一、最小外接矩形

二、最大内接矩形

三、最大内接圆

四、最小外接圆

五、拟合椭圆

一、最小外接矩形

这里的图片是mask，类似于这样的：

绘制如上图片的最小外接矩阵：

def draw_min_rect_rectangle(mask_path): image = cv2.imread(mask_path) thresh = cv2.Canny(image, 128, 256) contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) img = np.copy(image) for cnt in contours: x, y, w, h = cv2.boundingRect(cnt) # 绘制矩形 cv2.rectangle(img, (x, y+h), (x+w, y), (0, 255, 255))

绘制结果：

也可以将矩形区域作成新的mask：

# 将最小内接矩形填充为白色 white = [255, 255, 255] for col in range(x, x+w): for row in range(y, y+h): image[row, col] = white

那么我们的最小内接矩阵mask就绘制好了：

也可以通过x，y，w，h对图片进行切割：

pic = cv2.imread(original_img_path) # 读取mask对应的图片 cut = pic[y:y+h, x:x+w] # 根据内接矩形的顶点切割图片 cv2.imwrite(save_path, cut) # 保存切割好的图片

也可以通过最小内接矩形mask来进行切割：

rectangle_mask_gray = cv2.cvtColor(rectangle_mask, cv2.COLOR_RGB2GRAY) # 此处的image是我们之前获取的最小内接矩形的mask pic = cv2.imread(original_img_path) # 读取mask对应的图像 out = cv2.bitwise_and(pic, pic, mask=rectangle_mask) # 根据mask切割 cv2.imshow("min rect rectangle mask cut img", out)

效果如下：

二、最大内接矩形

def maximum_internal_rectangle(mask_path): img = cv2.imread(mask_path) img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) ret, img_bin = cv2.threshold(img_gray, 0, 255, cv2.THRESH_BINARY) contours, _ = cv2.findContours(img_bin, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE) contour = contours[0].reshape(len(contours[0]), 2) rect = [] for i in range(len(contour)): x1, y1 = contour[i] for j in range(len(contour)): x2, y2 = contour[j] area = abs(y2 - y1) * abs(x2 - x1) rect.append(((x1, y1), (x2, y2), area)) all_rect = sorted(rect, key=lambda x: x[2], reverse=True) if all_rect: best_rect_found = False index_rect = 0 nb_rect = len(all_rect) while not best_rect_found and index_rect < nb_rect: rect = all_rect[index_rect] (x1, y1) = rect[0] (x2, y2) = rect[1] valid_rect = True x = min(x1, x2) while x < max(x1, x2) + 1 and valid_rect: if any(img[y1, x]) == 0 or any(img[y2, x]) == 0: valid_rect = False x += 1 y = min(y1, y2) while y < max(y1, y2) + 1 and valid_rect: if any(img[y, x1]) == 0 or any(img[y, x2]) == 0: valid_rect = False y += 1 if valid_rect: best_rect_found = True index_rect += 1 if best_rect_found: # 如果要在灰度图img_gray上画矩形，请用黑色画（0,0,0） cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 0), 1) cv2.imshow("rec", img) cv2.waitKey(0) else: print("No rectangle fitting into the area") else: print("No rectangle found")

三、最大内接圆

先看效果：

再放代码：

# 读取图片，转灰度 mask = cv2.imread(mask_path) mask_gray = cv2.cvtColor(mask, cv2.COLOR_BGR2GRAY) # 识别轮廓 contours, _ = cv2.findContours(mask_gray, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) # 计算到轮廓的距离 raw_dist = np.empty(mask_gray.shape, dtype=np.float32) for i in range(mask_gray.shape[0]): for j in range(mask_gray.shape[1]): raw_dist[i, j] = cv2.pointPolygonTest(contours[0], (j, i), True) # 获取最大值即内接圆半径，中心点坐标 minVal, maxVal, _, maxDistPt = cv2.minMaxLoc(raw_dist) minVal = abs(minVal) maxVal = abs(maxVal) # 画出最大内接圆 result = cv2.cvtColor(mask_gray, cv2.COLOR_GRAY2BGR) radius = np.int(maxVal) center_of_circle = maxDistPt cv2.circle(result, maxDistPt, radius, (0, 255, 0), 2, 1, 0) cv2.imshow('Maximum inscribed circle', result) cv2.waitKey(0) 四、最小外接圆

效果：

代码：

def minimum_external_circle(mask_path): img = cv2.imread(mask_path) img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) contours, _ = cv2.findContours(img_gray, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE) cnt = contours[0] (x, y), radius = cv2.minEnclosingCircle(cnt) center = (int(x), int(y)) # 最小内接圆圆心 radius = int(radius) cv2.circle(img, center, radius, (0, 255, 0), 2) cv2.circle(img, center, 1, (0, 255, 0), 2) cv2.imshow('ret', img) cv2.waitKey(0) 五、拟合椭圆

效果：

代码：

def fit_ellipse(mask_path): img = cv2.imread(mask_path) img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) contours, _ = cv2.findContours(img_gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # 拟合椭圆 ellipse = cv2.fitEllipse(contours[0]) cv2.ellipse(img, ellipse, (255, 0, 255), 2) ellipse_center = (int(ellipse[0][0]), int(ellipse[0][1])) # 椭圆圆心坐标 cv2.circle(img, ellipse_center, 1, (255, 0, 255), 2) cv2.imshow('ellipse', img) cv2.waitKey(0)

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