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| import os | |
| import gradio as gr | |
| from transformers import pipeline | |
| from helper import render_results_in_image | |
| od_pipe = pipeline("object-detection", "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"), | |
| title="Object Detection with DETR-ResNet-50", | |
| description="Model Info: [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50)", | |
| allow_flagging="never", | |
| examples=["catdog.jpg", "bus.jpg"] | |
| ) | |
| demo.launch() |