# 需要导入模块: import cv2 [as 别名]# 或者: from cv2 importCC_STAT_AREA[as 别名]defget_mean_cell_size(mask_contours):nuclei_sizes = []formask_contourinmask_contours: mask = mask_contour[:,:,0] contour = mask_contour[:,:,1] new_mask = (mask*255).astype(np.uint8) new_contour ...
# 需要導入模塊: import cv2 [as 別名]# 或者: from cv2 importcontourArea[as 別名]defget_single_centerpoint(self, mask):contour, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE) contour.sort(key=lambdax: cv2.contourArea(x), reverse=True)#only save the biggest one'''debug...
使用掩模:要统计图像某个局部区域的直方图只需要构建一副掩模图像,将要统计的部分设置成白色,其余部分为黑色,就构成了一副掩模图像。构建掩模图像例子mask = np.zeros(img.shape[:2], np.uuint8) Mask[100:300, 100:400] = 255 Masked_img = cv2.bitwise_and(img, img, mask=mask) (2)直方图均衡化 如...
inpaint( src=srcimg, inpaintMask=mask, # 基于掩膜的图像复原,二值掩膜图中修复处为1 inpaintRadius=radius, # 修复半径 flags=cv2.INPAINT_NS # cv2.INPAINT_TELEA ) 灰度图转彩图 def transform(img,channel=3): # 各种图像的预处理操作都可以全部写在transform里 res=np.zeros((*img.shape,channel),...
shape[1])), contour, cv2.cv.CV_CONTOURS_MATCH_I2, 0) if similarity <= 0.2: cv2.fillPoly(contourMask, [poly], 255) return ellipseMask, contourMask Example #10Source File: load_saved_model.py From document-ocr with Apache License 2.0 7 votes def mask_to_bbox(mask, image, num_...
res = cv2.bitwise_and(frame, frame, mask=mask)# 对原图像和掩模进行位运算 # 显示图像 cv2.imshow('frame', frame) cv2.imshow('mask', mask) cv2.imshow('res', res) k = cv2.waitKey(5)&0xFF if k == 27: break cv2.destroyAllWindows() ...
= 7 Static MAT_DEPTH_MASK := OpenCV.DEPTH_MAX - 1 Static CV_8UC1 := OpenCV.MAKETYPE(OpenCV.CV_8U, 1) Static CV_8UC2 := OpenCV.MAKETYPE(OpenCV.CV_8U, 2) Static CV_8UC3 := OpenCV.MAKETYPE(OpenCV.CV_8U, 3) Static CV_8UC4 := OpenCV.MAKETYPE(OpenCV.CV_8U, 4) Static CV_...
WARP_INVERSE_MAP) return out # TODO: Modify this method to get a better face contour mask Example #25Source File: helpers.py From songoku with MIT License 5 votes def perspective_transform(img, transformation_matrix, original_shape=None): warped = img if original_shape is not None: if ...
fromPILimportImage img_path="seg_smooth.png" img=cv2.imread(img_path,0) mask=np.zeros_like(img) display(Image.fromarray(img)) 2. 设置阈值获取轮廓线集合 1 2 3 4 5 6 7 8 ret, img=cv2.threshold(img,127,255, cv2.THRESH_BINARY) ...
getLabelContourMask(False) # stitch foreground & background together mask_inv = cv2.bitwise_not(mask) result_bg = cv2.bitwise_and(img, img, mask=mask_inv) result_fg = cv2.bitwise_and(color_img, color_img, mask=mask) result = cv2.add(result_bg, result_fg) mask_inv = cv.bitwise_...