The Eying App 👀

The Eying App is an object detection application built using Streamlit 🎪, capable of analyzing images for objects and annotating them with bounding boxes.

This app uses the Hugging Face Transformers library with Facebook detr-resnet-101 object detection model.

Eying App Demo: here

Features

• Object Detection: Upload an image and detect objects present in the image.
• Annotation: Annotate detected objects with bounding boxes and confidence scores.
• Download Annotated Image: Download the annotated image with detected objects highlighted.
• Interactive Interface: User-friendly interface with options to upload images, analyze them, and view results.

Installation

To run the app locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/your-username/eying-app.git
   cd eying-app
   

2. Get an HUGGINGFACE_HUB API KEY to run the model used in this application:

   • Visit https://huggingface.co/
   • Create an Account
   • Go to settings
   • Go to Access tokens
   • Generate a token

3. Create a .env file inside eying-app and write: HUGGINGFACE_HUB_API_KEY="your-api-key"

4. Create a virtual environment and activate it following these steps:

   python -m venv name_of_env
   source name_of_env\Scripts\activate
   

5. install all the requirements:

   pip install -r requirements.txt
   

6. Get Streamlit working:

    streamlit run main.py
   

7. Be my guest and Enjoyy! ✨