| import glob |
| import gradio as gr |
| from inference import * |
| from PIL import Image |
|
|
|
|
| def gradio_app(image_path): |
| """A function that send the file to the inference pipeline, and filters |
| some predictions before outputting to gradio interface.""" |
|
|
| predictions = run_inference(image_path) |
|
|
| out_img = Image.fromarray(predictions.render()[0]) |
|
|
| return out_img |
|
|
|
|
| Title = "Marine Life Identification" |
| description = ( |
| "" |
| ) |
|
|
| examples = glob.glob("images/*.png") |
|
|
| gr.Interface(gradio_app, |
| inputs=[gr.inputs.Image(type="filepath")], |
| outputs=gr.outputs.Image(type="pil"), |
| enable_queue=True, |
| title=Title, |
| description=description, |
| examples=examples).launch() |