app.py

import gradio as gr
from transformers import pipeline

pipe = pipeline("image-classification", model="TenzinNYeshey/car-type-model")

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 Car candidate", sources=['upload', 'webcam'], type="pil"),
    outputs = [gr.Image(label="Processed Image"), gr.Label(label="Result", num_top_classes=3)],

    title="Car Type???"
)

if __name__ == "__main__":
    gradio_app.launch()