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### Stolen from https://huggingface.co/spaces/Datatrooper/zero-shot-image-classification/tree/main
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):
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=[["caesar.jpg", "dog,cat,bird"],
["benny.jpg", "dog,cat,bird"],
["turtle.jpg", "belgium,colombia,bird,turtle"]])
iface.launch() |