app.py

# from helper import load_image_from_url, render_results_in_image
# from helper import ignore_warnings
# ignore_warnings()

from transformers import pipeline

from transformers.utils import logging
logging.set_verbosity_error()

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)