import gradio as gr
from transformers import pipeline

# Load the pipeline
pipe = pipeline("zero-shot-image-classification", model="patrickjohncyh/fashion-clip")

# Define the Gradio interface
def classify_image(image):
    # Perform zero-shot image classification
    result = pipe(image)
    labels = result["labels"]
    scores = result["scores"]
    return {label: score for label, score in zip(labels, scores)}

# Create a Gradio interface
iface = gr.Interface(
    fn=classify_image,
    inputs=gr.inputs.Image(),
    outputs=gr.outputs.Label(num_top_classes=3)  # Adjust the number of top classes as needed
)

# Launch the interface
iface.launch()