app.py

#                                                                                                                 
# 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")

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", title="Sandbox")

demo.launch()