lbph-algorithm

问题 I am trying to work with the open_cv library in android. I have never worked on it before, so this may be a very basic question. I have an opencv_face.LBPHFaceRecognizer object in my Recognizer Activity. My requirement is to read the histogram values for previously-stored faces. opencv_face.LBPHFaceRecognizer mFaceRecognizer = = createLBPHFaceRecognizer(2, 8, 8, 8, 95); File file = new File(RegisterActivity.getFilePath(mContext)); mFaceRecognizer.load(file.getAbsolutePath()); opencv_core

问题 I´m developing currently a webapp with object detection using the js-objectdetect libary. Therefore I´m converting opencv HAAR-cascades to the needed js-objectdetect format with a python script. My question is, if it´s possible to convert opencv LBP-cascades to the js-objectdetect format too. I need this, because I already have an opencv application in use and I need to use the same LBP-cascades. I don´t find anything on Javascript object-/ face detection with LBP-cascades on the internet.

问题 I generated a texture image like this I have to compare two textures. I have used histogram comparison method. image_file = 'output_ori.png' img_bgr = cv2.imread(image_file) height, width, channel = img_bgr.shape hist_lbp = cv2.calcHist([img_bgr], [0], None, [256], [0, 256]) print("second started") image_fileNew = 'output_scan.png' img_bgr_new = cv2.imread(image_fileNew) height_new, width_new, channel_new = img_bgr_new.shape print("second lbp") hist_lbp_new = cv2.calcHist([img_bgr_new], [0],

问题 I generated a texture image like this I have to compare two textures. I have used histogram comparison method. image_file = 'output_ori.png' img_bgr = cv2.imread(image_file) height, width, channel = img_bgr.shape hist_lbp = cv2.calcHist([img_bgr], [0], None, [256], [0, 256]) print("second started") image_fileNew = 'output_scan.png' img_bgr_new = cv2.imread(image_fileNew) height_new, width_new, channel_new = img_bgr_new.shape print("second lbp") hist_lbp_new = cv2.calcHist([img_bgr_new], [0],

问题 I have already seen that OpenCV provides a classifier based on LBP histograms: But I want to have access to the LBP histogram itself. For instance: histogram = calculate_LBP_Histogram( image ) Is there any function that performs this in OpenCV? 回答1: You can get the C++ code for computing LBP using OpenCV's Mat data structure here: http://www.bytefish.de/blog/local_binary_patterns You should be able to find the Python version as well on the same site. The code is written by Philipp Wagner, who

问题 Closed . This question needs details or clarity. It is not currently accepting answers. Want to improve this question? Add details and clarify the problem by editing this post. Closed 5 days ago . This is an algorithm question on the detectMultiScale(...) function from the opencv library. I need help to understand what opencv's detectMulitScale() function exactly does. I have understood from reading the C++ code that the source image is scaled with several scales based on scaleFactor and size

问题 I've been running into problems recently where the local binary pattern method in python skimage is producing unexpected results. Have a look at the cartoon example below. It shows two flat color circles on a flat color background. The local binary pattern (P=8 samples, Radius=1) output is: (Image is color coded in jet colors). The gray color correctly represents 255. However, the blue color is 85 (binary 01010101) . So while the method correctly shows the background and the circle on the

问题 I'm trying to get some c++ code to run on my Android device; however, I'm running into a small little problem with the type of Mat I'm using. The code I'm trying to convert is as follow (the second function calls the first): static Mat histc_(const Mat& src, int minVal=0, int maxVal=255, bool normed=false) { Mat result; // Establish the number of bins. int histSize = maxVal-minVal+1; // Set the ranges. float range[] = { static_cast<float>(minVal), static_cast<float>(maxVal+1) }; const float*

问题 Running the code of linear binary pattern for Adrian. This program runs but gives the following warning: C:\Python27\lib\site-packages\sklearn\svm\base.py:922: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations. "the number of iterations.", ConvergenceWarning I am running python2.7 with opencv3.7, what should I do? 回答1: Normally when an optimization algorithm does not converge, it is usually because the problem is not well-conditioned, perhaps due to a poor

问题 For example, the lbp code of the pixel with coordinate (1, 1) is possible to calculate it with the pixels (0, 0); (0, 1); (0, 2); (1, 2); (2, 2); (2, 1); (2, 0); (1, 0) but the pixels of the extremes do not have those 8 neighborhood pixels, that is, the pixel (0, 0) only has 3 neighbors. This question comes to me because I have obtained the LBP image using sicikit image, the code is as follows: lbp = feature.local_binary_pattern (gray, 8, 1, 'ror') Then I printed the values ​​of the gray