Metadata-Version: 2.1
Name: flowvision
Version: 0.0.53
Summary: oneflow vision codebase
Home-page: https://github.com/Oneflow-Inc/vision
Author: flow vision contributors
Author-email: rentianhe@oneflow.org
License: BSD
Description: # vision
        Datasets, Transforms and Models specific to Computer Vision
        
        
        ## Installation
        - First install the nightly version of `OneFlow`
        ```bash
        python3 -m pip install oneflow -f https://staging.oneflow.info/branch/master/cu102
        ```
        
        - Then install the latest stable release of `flowvision`
        ```bash
        pip install flowvision==0.0.53
        ```
        
        - Or install the nightly release of `flowvision`
        ```bash
        pip install -i https://test.pypi.org/simple/ flowvision==0.0.53
        ```
        
        ## Supported Model
        All of the supported models can be found in our model summary page [here](MODEL_SUMMARY.md).
        
        
        ## Usage
        <details>
        <summary> <b> Quick Start </b> </summary>
        
        - list supported model
        ```python
        from flowvision import ModelCreator
        ModelCreator.model_table()
        ```
        
        - search supported model by wildcard
        ```python
        from flowvision import ModelCreator
        ModelCreator.model_table("*vit*", pretrained=True)
        ModelCreator.model_table("*vit*", pretrained=False)
        ModelCreator.model_table('alexnet')
        ```
        
        - create model use `ModelCreator`
        ```python
        from flowvision import ModelCreator
        model = ModelCreator.create_model('alexnet', pretrained=True)
        ```
        
        </details>
        
        <details>
        <summary> <b> ModelCreator </b> </summary>
        
        - Create model in a simple way
        ```python
        from flowvision.models import ModelCreator
        model = ModelCreator.create_model('alexnet', pretrained=True)
        ```
        the pretrained weight will be saved to `./checkpoints`
        
        - Supported model table
        ```python
        from flowvision.models import ModelCreator
        ModelCreator.model_table()
        ```
        ```
                   Models            
        ┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓
        ┃ Name         ┃ Pretrained ┃
        ┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩
        │ alexnet      │ true       │
        │ vit_b_16_224 │ false      │
        │ vit_b_16_384 │ true       │
        │ vit_b_32_224 │ false      │
        │ vit_b_32_384 │ true       │
        │ vit_l_16_384 │ true       │
        │ vit_l_32_384 │ true       │
        └──────────────┴────────────┘
        ```
        show all of the supported model in the table manner
        
        - List models with pretrained weights
        ```python
        from flowvision.models import ModelCreator
        ModelCreator.model_table(pretrained=True)
        ```
        ```
                   Models            
        ┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓
        ┃ Name         ┃ Pretrained ┃
        ┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩
        │ alexnet      │ true       │
        │ vit_b_16_384 │ true       │
        │ vit_b_32_384 │ true       │
        │ vit_l_16_384 │ true       │
        │ vit_l_32_384 │ true       │
        └──────────────┴────────────┘
        ```
        - Search for model by Wildcard
        ```python
        from flowvision.models import ModelCreator
        ModelCreator.model_table('vit*')
        ```
        ```
                   Models            
        ┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓
        ┃ Name         ┃ Pretrained ┃
        ┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩
        │ vit_b_16_224 │ false      │
        │ vit_b_16_384 │ true       │
        │ vit_b_32_224 │ false      │
        │ vit_b_32_384 │ true       │
        │ vit_l_16_384 │ true       │
        │ vit_l_32_384 │ true       │
        └──────────────┴────────────┘
        ```
        - Search for model with pretrained weights by Wildcard
        ```python
        from flowvision.models import ModelCreator
        ModelCreator.model_table('vit*', pretrained=True)
        ```
        ```
                   Models            
        ┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓
        ┃ Name         ┃ Pretrained ┃
        ┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩
        │ vit_b_16_384 │ true       │
        │ vit_b_32_384 │ true       │
        │ vit_l_16_384 │ true       │
        │ vit_l_32_384 │ true       │
        └──────────────┴────────────┘
        ```
        
        </details>
        
        ## Model Zoo
        We have conducted all the tests under the same setting, please refer to the model page [here](MODEL_ZOO.md) for more details.
        
        ## Disclaimer on Datasets
        This is a utility library that downloads and prepares public datasets. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have license to use the dataset. It is your responsibility to determine whether you have permission to use the dataset under the dataset's license.
        
        If you're a dataset owner and wish to update any part of it (description, citation, etc.), or do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thanks for your contribution to the ML community!
        
Keywords: computer vision
Platform: any
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
