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import numpy as np
import gradio as gr
from src.detect import predict
gr.Interface(
predict,
inputs=[
gr.Image(label="Input Image"),
gr.Slider(0, 1, value=0.5, label="IOU Threshold"),
gr.Slider(0, 1, value=0.4, label="Threshold"),
gr.Checkbox(label="Show Grad Cam"),
gr.Slider(0, 1, value=0.5, label="Opacity of GradCAM"),
],
outputs=gr.Gallery(rows=2, columns=1),
title="YoloV3 on PASCAL VOC Dataset From Scratch (Slide for GradCam output)",
examples=[
["example_images/009922.jpg", 0.5, 0.4, True, 0.5],
["example_images/009938.jpg", 0.6, 0.5, True, 0.5],
["example_images/009948.jpg", 0.55, 0.45, True, 0.5],
["example_images/009952.jpg", 0.5, 0.4, True, 0.5],
["example_images/009953.jpg", 0.6, 0.7, True, 0.5],
["example_images/009956.jpg", 0.5, 0.4, True, 0.5],
["example_images/009957.jpg", 0.6, 0.5, True, 0.5],
["example_images/009960.jpg", 0.55, 0.45, True, 0.5],
["example_images/009961.jpg", 0.5, 0.4, True, 0.5],
["example_images/009962.jpg", 0.6, 0.7, True, 0.5],
],
layout="horizontal"
).launch() |