Metadata-Version: 2.1
Name: cvlab-dl
Version: 0.0.1
Summary: An unified laboratory/framework for Computer Vision research, development and deployment.
Home-page: https://github.com/AlanDecode/cvlab
Author: AlanDecode
Author-email: zytbuaa1415@gmail.com
License: MIT
Description: 
        # 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)
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.6.0
Description-Content-Type: text/markdown
