metadata

title: Waste Classifier
emoji: ♻️
colorFrom: green
colorTo: gray
sdk: streamlit
sdk_version: 1.25.0
pinned: false

Waste Classifier

Waste Classifier Streamlit App

Overview

The Waste Classifier Streamlit App is designed to detect waste in images using the EfficientDet and classify them with a fine-tuned resnet50 model into different classes. Users can upload an image containing trash, and the app will display both the uploaded and classified images in parallel columns.

Instructions

Installation

Make sure you have Python installed. Clone the repository and navigate to the project directory:

git clone <repository_url>
cd <project_directory>

Create a virtual environment and install dependencies:

python -m venv venv-waste-classifier
source venv-waste-classifier/bin/activate  # On Windows, use 'venv-waste-classifier\Scripts\activate'
pip install -r requirements.txt

Running the App

Execute the Streamlit app with the following command:

streamlit run app.py

This will launch a local development server, and you can access the app in your web browser at http://localhost:8501.

Usage

Upload an image with trash using the provided file uploader.
The app will display the uploaded image in the left column.
Click the "Classify trash" button to initiate the classification process.
The classified image will be displayed in the right column.

Dependencies

Streamlit
Pillow
Other dependencies as specified in the requirements.txt file.