Metadata-Version: 2.1
Name: telesto-base
Version: 0.0.4
Summary: Base tools for telesto.ai models
Home-page: https://github.com/telesto-ai/telesto-base
Author: telesto.ai
Author-email: contact@telesto.ai
License: UNKNOWN
Description: # telesto-base
        Base Docker image and tools for telesto.ai models.
        
        # Instructions
        
        `telesto-base` contains a pip-installable Python package and a Docker image, allowing you to
        easily package your models for telesto.ai competitions.
        
        ## telesto-base package
        To install the module, you can simply use pip:
        ```
        pip install telesto-base
        ```
        If you would like to use the latest not yet released version, you can install the one in the 
        `develop` branch.
        ```
        pip install git+https://github.com/telesto-ai/telesto-base.git@develop
        ```
        
        ## The base image
        The base image contains the pre-installed `telesto-base` module. Your submissions will use this
        as a base, so you'll only have to worry about the algorithms and not the packaging. To use it
        locally, you can pull the image from Docker Hub:
        ```
        docker pull telestoai/model-api-base:latest
        ```
        
        Alternatively, the image can also be built locally with the command 
        ```
        docker build -t telestoai/model-api-base -f Dockerfile .
        ```
        
        ## An example model
        If you are stuck on how to prepare your model for submission, we have prepared a concrete example
        for you. The example is available in the [telesto-models](https://github.com/telesto-ai/telesto-models) repository with further instructions
        on the usage.
        
        ## Test classification model API
        
        Build and start a container
        ```
        docker build -t telestoai/model-api-base -f Dockerfile .
        docker run -p 9876:9876 --name model-api-base --rm --env USE_FALLBACK_MODEL=1 \
            telestoai/model-api-base classification
        ```
        
        Send a sample input
        ```
        curl -X POST -H "Content-Type:application/json" --data-binary @tests/data/class/example-input.json -i \
            http://localhost:9876/
        ...
        {
            "predictions": [
                {"probs": {"cat": 0.32015, "dog": 0.67985}, "prediction": "dog"},
                {"probs": {"cat": 0.81545, "dog": 0.18455}, "prediction": "cat"}
            ]
        }
        ```
        
        ## Test segmentation model API
        
        Build and start a container
        ```
        docker build -t telestoai/model-api-base -f Dockerfile .
        docker run -p 9876:9876 --name model-api-base --rm --env USE_FALLBACK_MODEL=1 \
            telestoai/model-api-base segmentation
        ```
        
        Post a sample input
        ```
        curl -X POST -H "Content-Type:application/json" --data-binary @tests/data/segm/example-input.json -i \
            http://localhost:9876/jobs
        ...
        {
            "job_id": "b741bd19767441f6b7abd022744083c9"
        }
        ```
        
        Get the result
        ```
        curl -H "Content-Type:application/json" -i http://localhost:9876/jobs/b741bd19767441f6b7abd022744083c9
        ...
        {
            "mask": {
                "content": "<BASE_64_IMAGE>"
            }
        }
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
