array([[[round(180*float(x-302)/298), 255, 255]]], dtype=np.uint8) line_color = [int(c) for c in cv2.cvtColor(color_pixel, cv2.COLOR_HSV2BGR)[0][0]] cv2.line(canvas, (x, 0), (x, 147), line_color) # 如果定义圆的线宽大于半斤,则等效于画圆点,随机在画面右下角的框内...
motion_blur_kernel = cv2.warpAffine(motion_blur_kernel, M, (degree, degree)) motion_blur_kernel = motion_blur_kernel / degree blurred = cv2.filter2D(image, -1, motion_blur_kernel)# convert to uint8cv2.normalize(blurred, blurred,0,255, cv2.NORM_MINMAX) blurred = np.array(blurred, dtype...
cv2.THRESH_TOZERO_INV : THRESH_TOZERO 的反转 #直方图统计 cv2.calcHist(images,channels,mask,histSize,ranges) images: 原图像图像格式为unit8,或float32,当传入函数时应该用[]括起来,例如[img] channels:如果传入的图像是灰度值,那他的值就是[0],如果图像是彩色图像,传入的参数可以是[0][1][2],他们...
比如在上面的代码中,实现了从uint8到float32的转换。如下图所示: 其原型如下: dst = ndarray.astype(dtype[, order='K'[, casting='unsafe'[, subok=True[, copy=True]]]) 1. 先说下其名称中的字母“as”是怎么来的。这个函数的作用的英文表述为“Copy of the array, cast to a specified type.”...
combo_image = np.zeros((max(scene_h, obj_h), scene_w + obj_w), np.uint8) combo_image[0:obj_h, 0:obj_w] = obj # copy the obj into the combo image combo_image[0:scene_h, obj_w:obj_w + scene_w] = scene # same for the scene ...
img=np.zeros((512,512,3),np.uint8)# 画直线,图片对象,起始坐标(x轴,y轴),结束坐标,颜色,宽度 cv2.line(img,(0,0),(311,511),(255,0,0),10)# 画矩形,图片对象,左上角坐标,右下角坐标,颜色,宽度 cv2.rectangle(img,(30,166),(130,266),(0,255,0),3)# 画圆形,图片对象,中心点坐标,半...
= 6 Static PARAM_FLOAT := 7 Static PARAM_UNSIGNED_INT := 8 Static PARAM_UINT64 := 9 Static PARAM_UCHAR := 11 Static PARAM_SCALAR := 12 ; Code Static ERROR_StsOk := 0 Static ERROR_StsBackTrace := -1 Static ERROR_StsError := -2 Static ERROR_StsInternal := -3 Static ERROR_Sts...
Z = np.float32(Z) criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0) K = 8 ret, label, center = cv2.kmeans(Z, K, None, criteria, 10, cv2.KMEANS_RANDOM_CENTERS) center = np.uint8(center) res = center[label.flatten()] ...
= 6 Static PARAM_FLOAT := 7 Static PARAM_UNSIGNED_INT := 8 Static PARAM_UINT64 := 9 Static PARAM_UCHAR := 11 Static PARAM_SCALAR := 12 ; Code Static ERROR_StsOk := 0 Static ERROR_StsBackTrace := -1 Static ERROR_StsError := -2 Static ERROR_StsInternal := -3 Static ERROR_Sts...
# 生成与原始图像相同大小的随机噪声图像 noise = np.random.randn(*img.shape[:2]) * 50 # 调整50来控制噪声的幅度 noise = cv2.GaussianBlur(noise.astype(np.float32), (5, 5), 0) # 应用高斯模糊以平滑噪声 noise = cv2.normalize(noise, None, 0, 255, cv2.NORM_MINMAX).astype(np.uint8) ...