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import gradio as gr
from transformers import pipeline
classifier = pipeline("image-classification", model="Pemmmm/apple_tomatoe_model1")
def predict(input_img):
predictions = pipe(input_img)
return input_img, {p["label"]: p["score"] for p in predictions}
import gradio as gr
gradio_app = gr.Interface(
predict,
inputs = gr.Image(label = "Select Image", sources=['upload', 'webcam'], type="pil"),
outputs = [gr.Image(label="Processed Image"), gr.Label(label="Result", num_top_classes=2)],
title="Apple or Tomato??"
)
if __name__ == "__main__":
gradio_app.launch()