PoC .NET Tensorflow

A proof of concept (PoC) to demonstrate the integration of .NET Core and TensorFlow for real-time image recognition.

---

Introduction

This project showcases the power of .NET Core combined with TensorFlow to perform real-time image recognition. Using TensorFlow's model inference capabilities, the PoC allows users to process images and identify objects in real-time.

The implementation is inspired by Paulo Torres' Medium article, with enhancements to demonstrate practical use cases.

---

Diagram

graph TD
    A[Input Device Camera/Local Images] -->|Image Data| B[.NET Core App]
    B -->|Pre-Processing| C[TensorFlow Model]
    C -->|Model Inference| D[Recognition Results]
    D -->|Output| E[Display/Logging]

Loading

---

Features

• Real-Time Image Processing: Capture images from a live camera feed or load pre-saved images.
• TensorFlow Integration: Leverage TensorFlow models for accurate object detection.
• Platform Independence: Built using .NET Core for cross-platform support.
• Extensible Design: Easy to integrate with different TensorFlow models and extend for additional functionality.

---

Useful Links

• Real-Time Image Recognition with .NET Core and TensorFlow (Medium Article)
• TensorFlow Official Documentation
• .NET Core Documentation

---

How to Run

1. Clone the repository:

   git clone https://github.com/your-repository-url.git
   cd your-repository-folder

2. Install prerequisites:

   • Ensure you have .NET Core SDK installed (Download).
   • Install TensorFlow runtime for your platform.

3. Restore dependencies:

   dotnet restore

4. Build the project:

   dotnet build

5. Run the application:

   dotnet run

6. Usage:

   • Provide an image input (via file or live camera feed).
   • Observe real-time recognition results in the console or UI.

---

License

This project is licensed under the MIT License. See the LICENSE file for details.