image-processing

问题 In all the tutorials i've seen for tensorflow, they've used the MNIST dataset, i've understood the modelling but how do i load this dataset into tensorflow? https://www.nist.gov/itl/iad/image-group/emnist-dataset 回答1: The EMNIST dataset uses the same binary format as the original MNIST dataset. Therefore you can take the input pipeline code from any tutorial that uses the original MNIST dataset, and point it at the set of files you get from downloading the EMNIST dataset to train on that

问题 I'm trying to analyze images of bio-films of pseudomona, I'm doing this in order to find some kind of correlation between its grow and distribution with some independent variables. I've applied a segmentation to obtain a circular area of interest and now I was thinking in applying some color segmentation to the image with its HSV values to just leave the areas with bio-film. I've trying to think in a way to completely isolate all the areas that are important, I applied a bitwise_not to the

问题 I want to remove the antialiasing from an image. This code will get the 4 major colors from an image, compare each pixel to the 4 major colors and assign the closest color. import numpy as np from PIL import Image image = Image.open('pattern_2.png') image_nd = np.array(image) image_colors = {} for row in image_nd: for pxl in row: pxl = tuple(pxl) if not image_colors.get(pxl): image_colors[pxl] = 1 else: image_colors[pxl] += 1 sorted_image_colors = sorted(image_colors, key=image_colors.get,

问题 I need to convert bytes of an image to original image. My byte array which is created by WritableRaster.And Itried to convert to original form ,but it produced image without original colors.My tries are below try { BufferedImage readImage = ImageIO.read(new File("C:\\Users\\Public\\Pictures\\Sample Pictures\\Desert.jpg")); byte imageData[] = get_byte_data(readImage); // Then I need to convert this to original image DataBuffer buffer = new DataBufferByte(imageData, imageData.length);

问题 I have two images. One has more green color and another one has better quality (it has right color). How can I improve the first one to have the similar color as the second one.I used the contrast enhancement as //Contrast enhancement for (int y = 0; y < rotated.rows; y++) { for (int x = 0; x < rotated.cols; x++) { for (int c = 0; c < 3; c++) { //"* Enter the alpha value [1.0-3.0]: " //"* Enter the beta value [0-100]: "; rotated.at<Vec3b>(y, x)[c] = saturate_cast<uchar>(2.5*(rotated.at<Vec3b>

问题 I tried to detect all the rectangles in image using threshold, canny edge and applied contour detection but it was not able to detect all the rectangles. Finally, I thought of detect the same using hough transforms but when I tried to detect lines in image, I'm getting all the lines. I need to detect only rectangular boxes in the image. Can someone help me? I'm new to opencv. Input image Code: import cv2 import matplotlib.pyplot as plt import numpy as np img = cv2.imread("demo-hand-written

问题 In order to make an image with better quality, I had do lots of research on filters. Filters are categorized into low, medium and high. After an analysis of these categories of filters, I conclude that Gaussian low-pass filter is the most suitable for me. And I had researched on how to code it in Android. Finally I found that OpenCV has this function. After a few days of headache, I still can't find any solution since I am new to OpenCV. Does anyone can help me? 回答1: Take a look at this

问题 I'm trying to get the fft of an image and then plot the fraq of that fft with using matplotlib. However, this error message: "ValueError: x and y can be no greater than 2-D, but have shapes (2592,) and (2592, 1, 3)". I tried to reshape my np.array like so: import numpy as np from PIL import Image import matplotlib.pyplot as plt import tkinter from scipy.fftpack import fft, fft2, fftshift resim = Image.open(r'yeni.jpg') resim_data = np.asarray(resim) fourier = fft2(resim_data) #psd2D = np.abs

问题 I have a picture of 2 colors. Red color pixels are in form of cluster. I would like to know the max dimension of each cluster to compare with the acceptable tolerance. How to do? Is there any function to perform it? 回答1: For this kind of image analysis, you can check out EBImage : install.packages("BiocManager") BiocManager::install("EBImage") Your workflow might look something like this. First, load the packages and read in your image. We'll also display it to show we're on the right track:

问题 I have two images, one is the result of applying an affine transform to the other. I can register them using homography by extracting the points using the ORB_create function in OpenCV. However, I want to calculate the Affine matrix needed for this transformation. is there any way of doing it simply by having the two images? 回答1: Detect a rotated rectangle and use its corners to get your transformation matrix Use : getPerspectiveTransform or getAffineTransform Edit: regarding rotated