semvec/pypi-packages huggingface dataset:
cvlab-dl 0.0.1
An unified laboratory/framework for Computer Vision research, development and deployment.
License: MIT
Requires Python: >=3.6.0

# cvlab

An unified laboratory/framework for Computer Vision research, development and
deployment. Here we cover the whole life cycle of CV models: building, training,
evaluation, optimization and deployment.

We roughly target these platform/frameworks internally:

```
Python >= 3.6
PyTorch >= 1.6
TensorFlow >= 1.15
ONNX >= 1.7
TensorRT >= 6
```

Other dependencies could be found in `requirements.txt`.

## About the project

This project empowers CV developers with several tool boxes, and we try our best
to make each of them independent enough so that you can extract them from this
project and use them in your own.

**Curated models**. Loads of new models are coming to the world every day,
but only some of them are proven to be real applicable, these models are hand
picked by our own experience during everyday work, covering multiple tasks
including image classification, detection, segmentation, etc. We provide
*implementation of these models*, *pre-trained weights*, and *an nice guide to
re-train/fine tune them* on your own data. Utilizing our optimization and
deployment tools, these models can be deployed and start creating **real value**
for you.

You can absolutely build new models and train, test, evaluate, optimize, deploy
them with exactly the same tool chain which already existed models used.

**Deployment toolbox**. Nice models are just the first step towards application,
the work after training a model is often complicated and painful, such as model
conversion from one platform to others, quantization and compressing, graph
optimization for inference and so on. We provide several utilities about these
tasks, hope they can be helpful.

**Evaluation metrics**. Without reasonable metrics we can't tell the performance
of anything. We provide easy-to-use tools to measure the performance of your
models with the most popular metrics of certain tasks. We believe by providing
such unified tools can greatly improve the everyday work experience for us.

**Miscellaneous tools**. We provide a bunch of tools that are nice if you have
them, so you don't need to write them over and over again, such as visualization
tools, dataset adapters, loggers, etc.

## LICENSE

MIT © [AlanDecode](https://www.imalan.cn)