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doc: add menu and deployment section

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  1. README.md +37 -8
README.md CHANGED
@@ -14,18 +14,32 @@ short_description: Object detection via Gradio
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  Aim: AI-driven object detection (on COCO image dataset)
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- ## Direct object detection via python scripts
 
 
 
 
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- ### 1. Use of torch library
 
 
 
 
 
 
 
 
 
 
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  > python detect_torch.py
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- ### 2. Use of transformers library
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  > python detect_transformers.py
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- ### 3. Use of HuggingFace pipeline library
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  > python detect_pipeline.py
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- ## Object detection via User Interface
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  Use of Gradio library for web interface
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  Command line:
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  <b>Note:</b> The Gradio app should now be accessible at http://localhost:7860
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- ## Object detection via Gradio client API
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  <b>Note:</b> Use of existing Gradio server (running locally, in a Docker container, or in the cloud as a HuggingFace space or AWS)
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- ### 1. Creation of docker container
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  Command lines:
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  > sudo docker build -t gradio-app .
@@ -46,6 +60,21 @@ Command lines:
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  The Gradio app should now be accessible at http://localhost:7860
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- ### 2. Direct inference via API
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  Command line:
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  > python inference_API.py
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  Aim: AI-driven object detection (on COCO image dataset)
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+ Machine learning models:
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+ - facebook/detr-resnet-50,
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+ - facebook/detr-resnet-101,
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+ - hustvl/yolos-tiny,
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+ - hustvl/yolos-small
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+ ### <b>Table of contents:</b>
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+ - [Execution via command line](#1-execution-via-command-line)
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+ - [Execution via User Interface ](#2-execution-via-user-interface)
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+ - [Execution via Gradio client API](#3-execution-via-gradio-client-api)
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+ - [Deployment on Hugging Face](#4-deployment-on-hugging-face)
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+ - [Deployment on Docker Hub](#5-deployment-on-docker-hub)
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+
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+
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+ ## 1. Execution via command line
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+
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+ ### 1.1. Use of torch library
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  > python detect_torch.py
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+ ### 1.2. Use of transformers library
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  > python detect_transformers.py
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+ ### 1.3. Use of HuggingFace pipeline library
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  > python detect_pipeline.py
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+ ## 2. Execution via User Interface
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  Use of Gradio library for web interface
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  Command line:
 
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  <b>Note:</b> The Gradio app should now be accessible at http://localhost:7860
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+ ## 3. Execution via Gradio client API
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  <b>Note:</b> Use of existing Gradio server (running locally, in a Docker container, or in the cloud as a HuggingFace space or AWS)
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+ ### 3.1. Creation of docker container
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  Command lines:
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  > sudo docker build -t gradio-app .
 
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  The Gradio app should now be accessible at http://localhost:7860
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+ ### 3.2. Direct inference via API
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  Command line:
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  > python inference_API.py
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+
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+ ## 4. Deployment on Hugging Face
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+ This web application is available on Hugging Face, via a Gradio space
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+ URL: https://huggingface.co/spaces/cvachet/object_detection_gradio
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+ ## 5. Deployment on Docker Hub
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+ This web application is available as a container on Docker Hub
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+ URL: https://hub.docker.com/r/cvachet/object-detection-gradio
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+