Extract a feature vector for any image and find the cosine similarity for comparison using Pytorch. I have used ResNet-18 to extract the feature vector of images. Finally a Django app is developed to input two images and to find the cosine similarity.

This Jupyter notebook implements a machine learning-based image classification model to classify images of skies. It demonstrates the process of loading image data, extracting features using the img2vec library, training a Random Forest model for classification, and making predictions. The model achieves an accuracy of 96%.

類似画像検出器

simple python Image to Vector Api for Elastic ImageSearch

EDA, pre-processing the data, selecting and testing a range of classification models, from simple machine learning models to neural networks models, and achieving a classifier with up to 95% accuracy.