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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" | |
def shot(image, labels_text="signature,passport photo"): | |
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", | |
"label", | |
examples=[["profile.jpg"],["sign.png"]], | |
description="Add a picture", | |
title="Sign Image Classification") | |
iface.launch() | |