app.py

from helper import load_image_from_url, render_results_in_image
from transformers import pipeline

from transformers.utils import logging
logging.set_verbosity_error()

from helper import ignore_warnings
ignore_warnings()

od_pipe = pipeline("object-detection", "facebook/detr-resnet-50")

from PIL import Image




import os
import gradio as gr

def get_pipeline_prediction(pil_image):
    
    pipeline_output = od_pipe(pil_image)
    processed_image = render_results_in_image(pil_image, pipeline_output)
    return processed_image


demo = gr.Interface(
  fn=get_pipeline_prediction,
  inputs=gr.Image(label="Input image", 
                  type="pil"),
  outputs=gr.Image(label="Output image with predicted instances",
                   type="pil")
)


demo.launch(share=True)