I am using histogram of oriented gradients for image classification using clustering in scikit learn. I am using hog from scikit-image to generate hog from 512x512 grayscale image. Here is an example: fd, hog_image = hog(image, orientations=8, pixels_per_cell=(16, 16), cells_per_block=(1, 1), visualize=True, channel_axis=-1) Where fd is used as features in classification. I wonder if there is a way to retrieve image from fitted coefficients in clustering model, in order to see how features differ between the clusters.(i.e go from fd …
I have been doing this for 2 days now. I want to make a model using sklearn that uses the HoG (Histogram oriented Gradients) features to classify the image (MNIST dataset having 70,000 images both training and testing combine) in Google CO-LAB, but somehow the model is taking much time then it is intended, and I don't know what mistake I am making. Can anyone help me out? My HoG feature vector size is 6084. I have also divided the …
I am doing some research on Logistic regression and SVM using different parameters using HOG features. I am facing a bit of problem while understanding each classifier with combination of different parameters and different HOG features. My findings and confusions are given below, For Hog: orientations=18, pixelsPerCell=(6,6), cellsPerBlock=(1,1) Classifier: SVC(C=1000.0, gamma=0.1, kernel='rbf'), Output: Total dataset=216, Correct prediction=210,Wrong Prediction=6 Classifier: SVC(C=100.0, gamma=0.1, kernel='rbf') Output: Total dataset=216, Correct prediction=210,Wrong Prediction=6 Classifier: SVC(C=1.0, gamma=0.1, kernel='rbf') Output: Total dataset=216, Correct prediction=209,Wrong Prediction=7 , For …
I'm wondering if e-commerce companies where products are offered by users, such as EBay, are using Object Recognition to ensure that an uploaded image corresponds to an specific type of object (clothing, shoes, glasses, etc) either to classify automatically or more importantly to filter undesired images (such as non related or even illegal types). If so, which algorithms and/or open platforms could be use for doing so? From what I've looked it seems that HOG+Exemplar SVM might be one of …