Spaces:
Sleeping
Sleeping
| title: Waste Classifier | |
| emoji: ♻️ | |
| colorFrom: green | |
| colorTo: gray | |
| sdk: streamlit | |
| sdk_version: 1.25.0 | |
| pinned: false | |
| # 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: | |
| ```bash | |
| git clone <repository_url> | |
| cd <project_directory> | |
| ``` | |
| Create a virtual environment and install dependencies: | |
| ```bash | |
| 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 | |
| ``` | |
| Create a `.env` file and set the following properties: | |
| - CLAS_FILENAME --> The name of the waste classificator model checkpoint | |
| - DET_FILENAME --> The name of the waste detector model checkpoint | |
| - HF_DET_REPO_NAME --> The huggingface repository name of the detector model | |
| - For example: [rootstrap-org/waste-detector](https://huggingface.co/rootstrap-org/waste-detector) | |
| - HF_CLAS_REPO_NAME --> The huggingface repository name of the classifier model | |
| - For example: [rootstrap-org/waste-classifier](https://huggingface.co/rootstrap-org/waste-classifier) | |
| You can ommit setting the last two properties if you download the models manually and put them under the `models` directory. | |
| ### Running the App | |
| Execute the Streamlit app with the following command: | |
| ```bash | |
| 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 | |
| 1. Upload an image with trash using the provided file uploader. | |
| 2. The app will display the uploaded image in the left column. | |
| 3. Click the "Classify trash" button to initiate the classification process. | |
| 4. The classified image will be displayed in the right column. | |
| ## Possible Classes | |
| The app can classify waste into the following classes: | |
| - Cardboard | |
| - Compost | |
| - Glass | |
| - Metal | |
| - Paper | |
| - Plastic | |
| - Trash | |
| ## Dependencies | |
| - Streamlit | |
| - Pillow | |
| - Other dependencies as specified in the `requirements.txt` file. | |