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from transformers import pipeline | |
classification = pipeline ("zero-shot-image-classification", model ="openai/clip-vit-large-patch14") | |
import gradio as gr | |
def classify_image(image): | |
labels = ["groupe1", "groupe2", "groupe3"] | |
classification = classification(image, labels) | |
return classification | |
image_input = gr.Image() | |
label_output = gr.Label(num_top_classes=3) | |
gr.Interface(fn=classify_image, inputs=image_input, outputs=label_output, | |
title="Zero-Shot Image Classification", | |
description="Classify images into predefined classes without fine-tuning the model.", | |
allow_flagging=False).launch() |