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#
# gradio demo
#
import gradio as gr
from transformers import AutoImageProcessor, AutoModelForImageClassification
preprocessor = AutoImageProcessor.from_pretrained("google/mobilenet_v2_1.0_224")
model = AutoModelForImageClassification.from_pretrained("google/mobilenet_v2_1.0_224")
title = "Sandbox"
description = "Place to try various models"
def classify(image):
inputs = preprocessor(images=image, return_tensors="pt")
outputs = model(**inputs)
logits = outputs.logits
predicted_class_idx = logits.argmax(-1).item()
return model.config.id2label[predicted_class_idx]
demo = gr.Interface(fn=classify, inputs="image", outputs="text")
demo.launch() |