oke-aditya / Image_similarity
Licence: apache-2.0
PyTorch Blog Post On Image Similarity Search
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Image Similarity using PyTorch
Auto-encoder based Image-Similarity Engine
Blog Post is here
Published in Official PyTorch Medium Channel. Thank you PyTorch team !
- Builds a simple Convolutional Auto-encoder based Image similarity engine.
- This solves the problem of finding similar images using unsupervised learning. There are no labels for images.
Tasks that it can do.
- [x] Similar images using Auto-encoders.
- [x] Similar image search from image features.
- [x] Clustering similar images.
Repostory Structure.
=== data Read data from here. It is in gitignore so it won't appear here.
=== docs Documentation using mkdocs.
=== image_similarity
====== cluster_images.py Clusters the embeddings learnt using PCA and T-SNE.
====== torch_data.py Contains Dataset class to create PyTorch dataset from folder.
====== torch_model.py Convolutional Auto-enocder Model.
====== torch_engine.py Train_step and validation_step for training.
====== torch_train.py Trainng script. Trains Auto-enocder and saves the embeddings.
====== torch_infer.py Contains inference code
====== config.py Configurations of models and paths.
====== torch_inference.ipynb Inference code in .ipynb to play with.
====== torch_train.ipynb Stand-alone code to train in Jupyter.
=== tests Contains tests for CI
Documentation
Please visit here for documentation.
It contains detailed description of work.
Image similarity Outputs
Some sample outputs of recommendations.
More outputs can be found in outputs folder.
Models
- Some models trained using a sample dataset are given in this link.
- It contains encoder, decoder and numpy embeddings generated from auto-enocoders.
- These are obtained by running
torch_train.py
script.
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