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https://github.com/passadis/python-aivision
Azure Vision AI - Object Detection
https://github.com/passadis/python-aivision
azure azure-sdk azureai cognitive-services flask python terraform vscode
Last synced: 4 days ago
JSON representation
Azure Vision AI - Object Detection
- Host: GitHub
- URL: https://github.com/passadis/python-aivision
- Owner: passadis
- License: mit
- Created: 2024-01-08T15:03:06.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-09-13T11:59:47.000Z (5 months ago)
- Last Synced: 2024-09-14T01:49:46.111Z (5 months ago)
- Topics: azure, azure-sdk, azureai, cognitive-services, flask, python, terraform, vscode
- Language: HCL
- Homepage: https://www.cloudblogger.eu/2023/10/18/semantic-kernel-container-apps-with-react-and-python/
- Size: 94.7 KB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- Contributing: DOCS/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: DOCS/CODE_OF_CONDUCT.md
- Security: DOCS/SECURITY.md
Awesome Lists containing this project
README
Azure AI Vision Integration with Web App
## Introduction
In an era marked by groundbreaking technologies, Artificial Intelligence stands out as a field where Cloud Vendors are investing extensively. Azure AI Services, including Cognitive Services, are at the forefront, offering a range of accessible products for both novice and experienced users in development and production environments.
Our focus today is on exploring **Azure AI Vision** with the integration of the **Computer Vision API** in a web application for object detection. This project expands to the use of Azure Container Registry for Web Apps and involves building a Python application with Flask, containerizing it with Docker, and configuring Continuous Deployment with Webhooks.
## Deployment
This project involves a deployment setup using Terraform. Here's a brief overview of the deployment process:
### Prerequisites
- **Code Editor**: We are using VSCode for our development.
- **Standard Files**: The necessary files for deployment, focusing on Infrastructure as Code (IaC) principles.
### Terraform Configuration
- **`main.tf`**: This file is the core of our Terraform configuration.
- _Reference Blog_: For more detailed insights, check out our blog post "AZURE VISION AI – OBJECT DETECTION WEB APP WITH DOCKER AND CONTAINER REGISTRY" at [CloudBlogger](https://www.cloudblogger.eu/2023/10/06/azure-vision-ai-object-detection-web-app-with-docker-and-container-registry/).
### Steps
1. **Set Up Your Environment**: Ensure you have VSCode and other required tools installed.
2. **Configuration**: Review and modify the `main.tf` file as per your project requirements.
3. **Deployment**: Use Terraform commands to initialize, plan, and apply your configuration to deploy the resources.
## Getting Started
To get started with this project:
1. Clone the repository to your local machine.
2. Install the necessary dependencies and tools.
3. Follow the deployment steps outlined above.
## Contribution
Contributions are welcome! If you have suggestions or improvements, feel free to fork the repository, make your changes, and submit a pull request.
## Instructions
**Follow the Blog for Detailed Instructions**: For step-by-step guidance, visit [Azure Vision AI – Object Detection Web App with Docker and Container Registry](https://www.cloudblogger.eu/2023/10/06/azure-vision-ai-object-detection-web-app-with-docker-and-container-registry/).
## Architecture
