Instructions to use guicon/techchallenge-pet-computer-vision-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use guicon/techchallenge-pet-computer-vision-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://guicon/techchallenge-pet-computer-vision-model") - Notebooks
- Google Colab
- Kaggle
| import gradio as gr | |
| from predict import predict | |
| def diagnostico(image): | |
| result = predict(image) | |
| return f"Classe: {result['classe']}\nConfiança: {result['confidence']:.2%}" | |
| demo = gr.Interface( | |
| fn=diagnostico, | |
| inputs=gr.Image(type="pil"), | |
| outputs="text", | |
| title="Pet AI Diagnosis", | |
| description="Classificação de raças e análise dermatológica" | |
| ) | |
| demo.launch() | |