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") images="dog.jpg" @spaces.GPU 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", examples=[["dog.jpg", "dog,cat,bird"], ["germany.jpg", "germany,belgium,colombia"], ["colombia.jpg", "germany,belgium,colombia"]], description="Add a picture and a list of labels separated by commas", title="Zero-shot Image Classification") iface.launch()