# image_embeddings
Project description
image_embeddings
Using efficientnet to provide embeddings for retrieval.
Why this repo ? Embeddings are a widely used technique that is well known in scientific circles. But it seems to be underused and not very well known for most engineers. I want to show how easy it is to represent things as embeddings, and how many application this unlocks.
Workflow
- download some pictures
- run inference on them to get embeddings
- simple knn example, to understand what's the point : click on some pictures and see KNN
Simple Install
Run pip install image_embeddings
Example workflow
- run
image_embeddings save_examples_to_folder --output_folder=tf_flower_images
, this will retrieve the image files from https://www.tensorflow.org/datasets/catalog/tf_flowers (but you can also pick any other dataset) - run the inference
- run the knn
API
image_embeddings.downloader.save_examples_to_folder(output_folder, dataset="tf_flowers")
Save https://www.tensorflow.org/datasets/catalog/tf_flowers to folder Also works with other tf datasets
Advanced Installation
Prerequisites
Make sure you use python>=3.6
and an up-to-date version of pip
and
setuptools
python --version
pip install -U pip setuptools
It is recommended to install image_embeddings
in a new virtual environment. For
example
python3 -m venv image_embeddings_env
source image_embeddings_env/bin/activate
pip install -U pip setuptools
pip install image_embeddings
Using Pip
pip install image_embeddings
From Source
First, clone the image_embeddings
repo on your local machine with
git clone https://github.com/rom1504/image_embeddings.git
cd image_embeddings
make install
To install development tools and test requirements, run
make install-dev
Test
To run unit tests in your current environment, run
make test
To run lint + unit tests in a fresh virtual environment, run
make venv-lint-test
Lint
To run black --check
:
make lint
To auto-format the code using black
make black
Tasks
- simple downloader in python
- simple inference in python using https://github.com/qubvel/efficientnet
- build python basic knn example using https://github.com/facebookresearch/faiss
- build basic ui using lit element and some brute force knn to show what it does, put in github pages
- use to illustrate embeddings blogpost
Project details
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