# applying gaussian blur on the image blur_img = cv2.GaussianBlur(image,(5,5),cv2.BORDER_DEFAULT) # show the image on the newly created image window cv2.imshow('Blur image',blur_img) Output : Example 2: Using GaussianBlur() method with src,ksize and sigmaX parameters. Python 1 2 3 ...
self.bsb = cv2.createBackgroundSubtractorMOG2(history) self.clahe = cv2.createCLAHE(clipLimit=clip_limit, tileGridSize=tile_grid) self.gaussian_blur_factor = gauss_blur self.median_blur_factor = med_blur 开发者ID:Alexanders101,项目名称:Funky-Vision,代码行数:7,代码来源:Key_Points.py 示例15:...
# 需要導入模塊: import cv2 [as 別名]# 或者: from cv2 importbilateralFilter[as 別名]defface_smooth(self, im_bgr, smooth_rate=0.7, bi_ksize=15, sigma=100, ga_ksize=3):"""Face smoothing. Parameters --- im_bgr: mat The Mat data format of reading from the original image using opencv....
Parameters --- input_arr : numpy array, HxW size filter : numpy array, H1xW1 size Returns --- result : numpy array, HxW size """ return cv2.filter2D(input_arr, -1, filter, borderType=cv2.BORDER_CONSTANT) Example #8Source File: util.py From BasicSR with Apache License 2.0 6 votes...
def set_blur_and_threshold(self, blur_kernel=0, blur_type="gaussian", blur_passes=1, threshold=0): """ Set the internal blur kernel and threshold amount for returned masks Parameters --- blur_kernel: int, optional The kernel size, in pixels to apply gaussian blurring to the mask. Set...
Static CIRCLES_GRID_FINDER_PARAMETERS_ASYMMETRIC_GRID := 1; anonymous Static STEREO_MATCHER_DISP_SHIFT := 4 Static STEREO_MATCHER_DISP_SCALE := (BitShift(1, -OpenCV.STEREO_MATCHER_DISP_SHIFT)); anonymous Static STEREO_BM_PREFILTER_NORMALIZED_RESPONSE := 0 ...
ArgumentParser( description='Enhance fingerprint image with diferent parameters.') parser.add_argument( "image_path", help="Specify image path location") args = parser.parse_args() pre_processor = preprocessing.PreProcessFingerImage(args.image_path) pre_processor.process_image() image_pre = pre_...
How do we choose optimal Canny edge detection parameters? As you can tell, depending on your input image you’ll need dramatically different hysteresis threshold values — and tuning these values can be a real pain. You might be wondering, is there a way toreliablytune these parameters without...
For each valid frame, we run it through a gaussian blur, convert it to grayscale, run cv2.Canny() on it and write it using the VideoWriter to the disk, and display using cv2.imshow() for a live view. Finally, we release the capture and video writer, as they're both working with ...
Applying a7×7Gaussian blur Applying Gaussian blurring helps remove some of the high frequency edges in the image that we are not concerned with and allow us to obtain a more “clean” segmentation. Now, let’s go ahead and apply the actual thresholding: ...