Replicating CLIP without PyTorch dependencies.
Project description
onnx_clip
About
The purpose of this repository is to replicate the functionality of CLIP without needing the
various PyTorch
dependencies. We do this by utilising a .onnx
format of the model, a pure NumPy
version of the tokenizer,
and an accurate approximation of the preprocess function.
Due to this final approximation, the output logits do
not perfectly match those of CLIP
but are close enough for our purposes.
git lfs
This repository uses Git LFS for the clip_model.onnx
file. Make sure to do git lfs install
before cloning.
In case you use the onnx_clip
project not as a repo, but as a package, the model will be downloaded from
the public S3 bucket.
Installation
To install, run the following in the root of the repository:
pip install .
Usage
All you need to do is call the OnnxClip
model class. An example can be seen below.
from onnx_clip import OnnxClip, softmax
from PIL import Image
images = [Image.open("onnx_clip/data/CLIP.png").convert("RGB")]
text = ["a photo of a man", "a photo of a woman"]
onnx_model = OnnxClip()
logits_per_image, logits_per_text = onnx_model.predict(images, text)
probas = softmax(logits_per_image)
Building & developing from source
Note: The following may give timeout errors due to the filesizes. If so, this can be fixed with poetry version 1.1.13 - see this related issue.
Install, run, build and publish with Poetry
Install Poetry
curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python -
To setup the project and create a virtual environment run the following command from the project's root directory.
poetry install
To build a source and wheel distribution of the library run the following command from the project's root directory.
poetry build
Instructions to publish the build artifacts for project maintainers
Copy this into your poetry config.toml file (or create a new one).
[repositories]
[repositories.onnx_clip]
url = "https://gitlab.com/api/v4/projects/41150990/packages/pypi"
The file should be located here on MacOs
~/Library/Application Support/pypoetry/config.toml
and here on Linux
~/.config/pypoetry/config.toml
With this setup you can now publish a package like so
poetry publish --repository onnx_clip -u <access_token_name> -p <access_token_key>
WARNING: Do not publish to the public pypi registry, e.g. always use the --repository option.
NOTE1: You must generate an access token
with scope set to api.
NOTE2: The push will fail if there is already a package with the same version. You can increment the version using poetry
poetry version
or by manually changing the version number in pyproject.toml.
Help
Please let us know how we can support: earlyaccess@lakera.ai.
LICENSE
See the LICENSE file in this repository.
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