I am working on Content Based Image Retrieval using LDA(Latent Dirichlet Allocation) Topic Modeling. I wish to use Python for the same. I am not able to find any libraries/packages in Python for LDA for image dataset.This package seems to work only for text corpus. Please suggest any packages in Python for image corpus or please briefly list down the steps needed to carry out LDA for images.
LDA in Python for Computer Vision
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I recently implemented image retrieval using LDA in python based on visual words. Take a look at my github page for details.
Visual words are cluster centers of image features extracted at image keypoints. In this example, dense SIFT features are extracted from a collection of 10 face images of 40 different people (the Olivetti faces dataset).
The 128-dimensional SIFT features are clustered using mini-batch K-means into a dictionary of K visual words. An online variational bayes algorithm is used to learn the LDA topic model and extract topic proportions for training image data.
Test image data is then converted into topic space and training images are retrieved based on cosine similarity between topic proportions of the train and test images.