app.py

from turtle import title
import gradio as gr
from transformers import pipeline
import numpy as np
from PIL import Image


pipe = pipeline("zero-shot-image-classification", model="openai/clip-vit-base-patch32")


def shot(image, labels_text):
    PIL_image = Image.fromarray(np.uint8(image)).convert('RGB')
    labels = labels_text.split(",")
    res = pipe(images=PIL_image,
           candidate_labels=labels,
           hypothesis_template= "This is a photo of a {}")
    return {dic["label"]: dic["score"] for dic in res}

iface = gr.Interface(shot,
                    ["image", "text"],
                    "label",
                    description="Ajouter une image avc une liste de labels séparées par la virgule",
                    title="Zero-shot Image Classification")

iface.launch()