filename:要保存的文件的路径和名称,包括文件扩展名 img:要保存的 OpenCV 图像,nparray 多维数组 paras:不同编码格式的参数,可选项 cv2.CV_IMWRITE_JPEG_QUALITY:设置 .jpeg/.jpg 格式的图片质量,取值为 0-100(默认值 95),数值越大则图片质量越高; cv2.CV_IMWRITE_WEBP_QUALITY:设置 .webp 格式的图片质量,...
importnumpyasnp fromPILimportImage importmatplotlib.pyplotasplt %matplotlibinline # read image raw_image=Image.open("panda.jpg") # image resize image_resize=raw_image.resize((128,128)) # image to array image_array=np.array(image_resize) # array to image image_output=Image.fromarray(image_ar...
defreadImg(im_fn):im=cv2.imread(im_fn)ifim is None:print('{} cv2.imread failed'.format(im_fn))tmp=imageio.mimread(im_fn)iftmp is not None:imt=np.array(tmp)imt=imt[0]im=imt[:,:,0:3]returnim 代码语言:javascript 代码运行次数:0 运行 AI代码解释 help(imageio.mimread) 关于cv2....
实现 importrandomdefsp_noise(image,prob):'''添加椒盐噪声prob:噪声比例'''output=np.zeros(image.shape,np.uint8)thres=1-probforiinrange(image.shape[0]):forjinrange(image.shape[1]):rdn=random.random()ifrdn<prob:output[i][j]=0elifrdn>thres:output[i][j]=255else:output[i][j]=image[i...
blurred = cv2.filter2D(image, -1, motion_blur_kernel)# convert to uint8cv2.normalize(blurred, blurred,0,255, cv2.NORM_MINMAX) blurred = np.array(blurred, dtype=np.uint8)returnblurredelse:returnimagedefaugment_hsv(img, hgain =0.0138, sgain =0.678, vgain =0.36): ...
只需使用Image.fromarray方法,需要注意pil图片的通道顺序是RGB,因此也需要先对通道进行反转。 2. PIL image pil to tensor importtorchvision.transforms.functional as F F.pil_to_tensor(image_pil)/ 255. pil to ndarray image_nd = np.array(image_pil) ...
a=np.array([[[3,4]],[[1,2]],[[5,7]],[[3,7]],[[1,8]]]) 其shape是(5, 1, 2)。与我们的轮廓是相同的。那么a[:,0]的结果就是: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 [3,4],[1,2],[5,7],[3,7],[1,8] ...
kernel_x = np.array([[0, 0, 0],[-1, 1, -0],[0, 0, 0]]) img_x = cv2.filter2D(img, -1, kernel) # MAX-MIN滤波器 img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) kernel = np.ones((3,3)) img_max = cv2.dilate(img, kernel) ...
url = "https://www.cleverfiles.com/howto/wp-content/uploads/2018/03/minion.jpg" # Fetch JPEG data d = requests.get(url) # Decode in-memory, compressed JPEG into Numpy array frame = cv2.imdecode(np.frombuffer(d.content,np.uint8), cv2.IMREAD_COLOR) cv2.imshow("dfsdf",frame) 本...
im = Image.open(imgname) cv2_im = np.array(im) #x,y,w,h aus Image Labeler box= [505.54, 398.334, 1334.43, 2513.223] x,y,w,h = box a = (x, y) b = (x+w, y+h) #First rectanglecall cv2.rectangle(img=cv2_im, pt1=a, pt2=b, color=(0, 255, 0), thickness=3, line...