Instructions to use nonamelife/garbage-detection-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use nonamelife/garbage-detection-model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://nonamelife/garbage-detection-model") - Notebooks
- Google Colab
- Kaggle
Garbage Detection AI Demo
This is an AI-powered web tool that classifies images as 'Clean' or 'Dirty' using a trained TensorFlow/Keras model.
How to Use
- Navigate to the
/toolendpoint (https://huggingface.co/spaces/nonamelife/garbage-detection-demo). - Upload an image (JPG, JPEG, or PNG).
- The application will predict whether the image depicts a "Clean" or "Dirty" environment.
Model Details
The underlying machine learning model (model.keras) is hosted on the Hugging Face Hub:
nonamelife/garbage-detection-model
Technologies
- Python (Flask)
- TensorFlow / Keras
- HTML, CSS
Source Code
The full source code for this demo is available on GitHub: Source Code
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