app.py

import gradio as gr
from transformers import pipeline

image_classifier = pipeline(task="image-classification", model="models/aioxlabs/dvoice-darija")

def predict(input_img):
    predictions = image_classifier(input_img)
    return input_img, {p["label"]: p["score"] for p in predictions}

gr_interface = gr.Interface(
    predict,
    inputs=gr.inputs.Image(label="Select hot dog candidate", source=['upload', 'webcam'], type="pil"),
    outputs=[gr.outputs.Image(label="Processed Image"), gr.outputs.Label(label="Result", num_top_classes=2)],
    title="Hot Dog? Or Not?",
)

if __name__ == "__main__":
    gr_interface.launch()