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https://github.com/serizba/cppflow
Run TensorFlow models in C++ without installation and without Bazel
https://github.com/serizba/cppflow
c cpp inference model neural-networks tensorflow tensorflow-cpp tensorflow-examples tensorflow-models
Last synced: 28 days ago
JSON representation
Run TensorFlow models in C++ without installation and without Bazel
- Host: GitHub
- URL: https://github.com/serizba/cppflow
- Owner: serizba
- License: mit
- Created: 2019-05-16T20:40:05.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2024-08-16T20:39:22.000Z (3 months ago)
- Last Synced: 2024-09-30T17:05:14.012Z (about 1 month ago)
- Topics: c, cpp, inference, model, neural-networks, tensorflow, tensorflow-cpp, tensorflow-examples, tensorflow-models
- Language: C++
- Homepage: https://serizba.github.io/cppflow/
- Size: 8.36 MB
- Stars: 785
- Watchers: 26
- Forks: 178
- Open Issues: 50
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
Awesome Lists containing this project
README
# 
Run TensorFlow models in c++ without Bazel, without TensorFlow installation and without compiling Tensorflow. Perform tensor manipulation, use eager execution and run saved models directly from C++.
```c++
// Read the graph
cppflow::model model("saved_model_folder");
// Load an image
auto input = cppflow::decode_jpeg(cppflow::read_file(std::string("image.jpg")));
// Cast it to float, normalize to range [0, 1], and add batch_dimension
input = cppflow::cast(input, TF_UINT8, TF_FLOAT);
input = input / 255.f;
input = cppflow::expand_dims(input, 0);
// Run
auto output = model(input);
// Show the predicted class
std::cout << cppflow::arg_max(output, 1) << std::endl;
```
You can take a look to the [examples](https://github.com/serizba/cppflow/tree/master/examples/) to see a full example on how to load a deep network and feed it with a sample image.
CppFlow uses [Tensorflow C API](https://www.tensorflow.org/install/lang_c) to run the models, meaning you can use it without installing Tensorflow and without compiling the whole Tensorflow repository with bazel, you just need to download the C API. With this project you can manage and run your models in C++ without worrying about void, malloc or free. With CppFlow you easily can:
* Open saved models created with Python
* Execute Tensorflow neural networks in C++
* Perform tensor manipulation directly from C++
## How To Run It
Since it uses TensorFlow 2 C API you just have to [download it](https://www.tensorflow.org/install/lang_c), check the [docs](https://serizba.github.io/cppflow/installation.html) to see a guide on how to do it.
Afterwards, you can install the library:
```sh
git clone [email protected]:serizba/cppflow.git
cd cppflow/examples/load_model
mkdir build
cd build
cmake ..
make -j
make install
```
Now you can check the [quickstart guide](https://serizba.github.io/cppflow/quickstart.html) to run a program using cppflow.
## Documentation
Check the docs at [https://serizba.github.io/cppflow/](https://serizba.github.io/cppflow/).
There you can find quickstart guides and more information about how to install the library and run the examples.
## Development
CppFlow is basically a wrapper over Tensorflow C API. The basic class, [tensor](https://github.com/serizba/cppflow/blob/master/include/cppflow/tensor.h) is a wrapper of a TF eager tensor, and it just constains a pointer to its TF representation.
The TF C API provides the tools to call all the TF [raw ops](https://www.tensorflow.org/api_docs/python/tf/raw_ops), but using them is confusing. CppFlow includes a facade over these functions, so they can be called easily as normal C++ functions. To achieve this, the file [ops](https://github.com/serizba/cppflow/blob/master/include/cppflow/raw_ops.h) contains (mostly) all the TF raw ops functions, but with a simple C++ interface. This file has been generated automatically using a [small script](https://github.com/serizba/cppflow/blob/master/include/cppflow/ops_generator/generator.py).
CppFlow also includes a wrapper on TF saved models, the [model](https://github.com/serizba/cppflow/blob/master/include/cppflow/model.h) class, so they can be easily opened and executed.
## Contributors
If you are willing to contribute to this project, please go ahead an visit the [development roadmap of cppflow](https://github.com/users/serizba/projects/3). Specially `contributor_wanted` labelled PR or issues are very welcome to new contributors.
# Citation
If you use this code or find this work useful in your research, please cite us:
```
@software{
izquierdo2019cppflow,
author = {Izquierdo, Sergio},
doi = {10.5281/zenodo.7107618},
title = {{cppflow: Run TensorFlow models in C++ without installation and without Bazel}},
url = {https://github.com/serizba/cppflow},
version = {2.0.0},
month = {5},
year = {2019}
}
```
## Style guide
We use the [Google's C++ style guide](https://google.github.io/styleguide/cppguide.html) using static code linker [cpplint](https://github.com/cpplint/cpplint).
We use the [Google's Python style guide](https://google.github.io/styleguide/pyguide.html) using static code linker [pylint](https://pylint.pycqa.org/en/latest/user_guide/installation/index.html) using attached pylintrc configuration.
## Remark
CppFlow is not related with TensorFlow. The CppFlow icon is a modified version of the TensorFlow logo. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.