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import gradio as gr
from ultralytics import YOLO
def yolov10_inference(image, model_id, image_size, conf_threshold):
model = YOLO(f'{model_id}.engine')
results = model.predict(source=image, imgsz=image_size, conf=conf_threshold)
annotated_image = results[0].plot()
return annotated_image[:, :, ::-1], None
def yolov10_inference_for_examples(image, model_path, image_size, conf_threshold):
annotated_image, _ = yolov10_inference(image, model_path, image_size, conf_threshold)
return annotated_image
def app():
with gr.Blocks():
with gr.Row():
with gr.Column():
image = gr.Image(type="pil", label="Image", visible=True)
model_id = gr.Dropdown(
label="Model",
choices=[
"yolov10s",
"yolov10m",
"yolov10m_ssvd_0.4",
"yolov10m_wsvd_0.4",
],
value="yolov10s",
)
image_size = gr.Slider(
label="Image Size",
minimum=320,
maximum=1280,
step=32,
value=640,
)
conf_threshold = gr.Slider(
label="Confidence Threshold",
minimum=0.0,
maximum=1.0,
step=0.05,
value=0.25,
)
yolov10_infer = gr.Button(value="Detect Smoke")
with gr.Column():
output_image = gr.Image(type="numpy", label="Annotated Image", visible=True)
yolov10_infer.click(
fn=yolov10_inference,
inputs=[image, model_id, image_size, conf_threshold],
outputs=[output_image],
)
gr.Examples(
examples=[
[
"examples/smoke1.jpg",
"yolov10s",
1280,
0.25,
],
[
"examples/smoke2.jpg",
"yolov10s",
1280,
0.25,
],
[
"examples/smoke3.jpg",
"yolov10s",
1280,
0.25,
],
[
"examples/smoke4.jpg",
"yolov10s",
1280,
0.25,
],
[
"examples/smoke5.jpg",
"yolov10s",
1280,
0.25,
],
],
fn=yolov10_inference_for_examples,
inputs=[
image,
model_id,
image_size,
conf_threshold,
],
outputs=[output_image],
cache_examples='lazy',
)
if __name__ == '__main__':
gradio_app = gr.Blocks()
with gradio_app:
gr.HTML(
"""
<h1 style='text-align: center'>
YOLOv10 for early fire detection with low resource consumption
</h1>
""")
gr.HTML(
"""
<h3 style='text-align: center'>
Original paper and code:
<a href='https://arxiv.org/abs/2405.14458' target='_blank'>arXiv</a> | <a href='https://github.com/THU-MIG/yolov10' target='_blank'>github</a>
</h3>
""")
with gr.Row():
with gr.Column():
app()
gradio_app.launch() |