| | import os |
| | import gradio as gr |
| |
|
| | from helper import load_image_from_url, render_results_in_image |
| | from PIL import Image |
| | from transformers import pipeline |
| |
|
| | 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 |
| |
|
| | |
| | od_pipe = pipeline("object-detection", model = "facebook/detr-resnet-50") |
| |
|
| | 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) |
