| import os | |
| import gradio as gr | |
| from helper import load_image_from_url, render_results_in_image | |
| from transformers import pipeline | |
| from transformers.utils import logging | |
| logging.set_verbosity_error() | |
| od_pipe = pipeline("object-detection", "./models/facebook/detr-resnet-50") | |
| 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_blocks.queue().launch(server_name="0.0.0.0", server_port=7860) |