image-processing

问题 Is it possible to opencv (using python) as default read an image as order of RGB ? in the opencv documentation imread method return image as order of BGR but in code imread methods return the image as RGB order ? I am not doing any converting process. Just used imread methods and show on the screen. It shows as on windows image viewer. is it possible ? EDIT 1: my code is below. left side cv.imshow() methods and the other one plt.imshow() methods. cv2.imshow() methods shows image as RGB and

问题 In my custom dataset, one kind of image is in one folder which torchvision.datasets.Imagefolder can handle, but how to split the dataset into train and test? 回答1: You can use torch.utils.data.Subset to split your ImageFolder dataset into train and test based on indices of the examples. For example: orig_set = torchvision.datasets.Imagefolder(...) # your dataset n = len(orig_set) # total number of examples n_test = int(0.1 * n) # take ~10% for test test_set = torch.utils.data.Subset(orig_set,

问题 In my custom dataset, one kind of image is in one folder which torchvision.datasets.Imagefolder can handle, but how to split the dataset into train and test? 回答1: You can use torch.utils.data.Subset to split your ImageFolder dataset into train and test based on indices of the examples. For example: orig_set = torchvision.datasets.Imagefolder(...) # your dataset n = len(orig_set) # total number of examples n_test = int(0.1 * n) # take ~10% for test test_set = torch.utils.data.Subset(orig_set,

问题 In my custom dataset, one kind of image is in one folder which torchvision.datasets.Imagefolder can handle, but how to split the dataset into train and test? 回答1: You can use torch.utils.data.Subset to split your ImageFolder dataset into train and test based on indices of the examples. For example: orig_set = torchvision.datasets.Imagefolder(...) # your dataset n = len(orig_set) # total number of examples n_test = int(0.1 * n) # take ~10% for test test_set = torch.utils.data.Subset(orig_set,

问题 While using zca_whitening , my code gets stuck somewhere, neither it shows any error nor the output. When i skip the zca_whitening and apply other transformations, the code runs perfectly. I am attaching the code snippet here. Pl help me if I am doing anything wrong here : datagen = ImageDataGenerator(zca_whitening=True) datagen.fit(x_train) where >> x_train is the set of training images (dim = 50 x 64 x 64 x 3) . After running datagen.fit , the code shows no further output or error, seems to

问题 While using zca_whitening , my code gets stuck somewhere, neither it shows any error nor the output. When i skip the zca_whitening and apply other transformations, the code runs perfectly. I am attaching the code snippet here. Pl help me if I am doing anything wrong here : datagen = ImageDataGenerator(zca_whitening=True) datagen.fit(x_train) where >> x_train is the set of training images (dim = 50 x 64 x 64 x 3) . After running datagen.fit , the code shows no further output or error, seems to

问题 While using zca_whitening , my code gets stuck somewhere, neither it shows any error nor the output. When i skip the zca_whitening and apply other transformations, the code runs perfectly. I am attaching the code snippet here. Pl help me if I am doing anything wrong here : datagen = ImageDataGenerator(zca_whitening=True) datagen.fit(x_train) where >> x_train is the set of training images (dim = 50 x 64 x 64 x 3) . After running datagen.fit , the code shows no further output or error, seems to

问题 To create an image thumbnail using an older version of ImageMagick, it was possible in the following ways: (To aid in futher referencing, examples are numbered.) 1. convert.exe image.jpg -thumbnail 100x100 ./converted/converted_image.jpg 2. mogrify.exe -thumbnail 100x100 -path ./converted image.png Now I have ImageMagick 7 (downloaded just yesterday), and during installation I intentionally turned "Install legacy utilities (e.g. convert.exe)" checkbox off. That is, I have only one utility in

问题 I have some image processing that allows me to extract a binary image containing thick segments and i'm facing the issue that these segments may cross each other. Hence I need to find an efficient way to separate them, i'll have to implement this in C++ so anything OpenCV-based would help. Here is a sample input image, both "blobs" would need to be split in 3 different segments. I have tried 2 ideas until now, I'm stuck with both of them and that's why I'm asking here if there are any "state

问题 I am writing some code for a little program in macOS to play with image processing with Metal Performance Shaders. For some reason, the code below produces an image that looks significantly darker than the original. The code simply takes a texture, performs a little guassian blur on it, and then outputs the image to the MTKView. I cannot figure out why the resulting image is so dark, though. import Cocoa import Metal import MetalKit import CoreGraphics import MetalPerformanceShaders class