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# Ackownledgement: https://huggingface.co/spaces/kadirnar/Yolov10/blob/main/app.py
# Thanks to @kadirnar
import gradio as gr
from ultralytics import YOLOv10
def yolov10_inference(image, model_path, image_size, conf_threshold):
model = YOLOv10(model_path)
model.predict(source=image, imgsz=image_size, conf=conf_threshold, save=True)
return model.predictor.plotted_img[:, :, ::-1]
def app():
with gr.Blocks():
with gr.Row():
with gr.Column():
image = gr.Image(type="pil", label="图片")
model_id = gr.Dropdown(
label="选择模型",
choices=[
"yolov10n.pt",
"yolov10s.pt",
"yolov10m.pt",
"yolov10b.pt",
"yolov10l.pt",
"yolov10x.pt",
],
value="yolov10s.pt",
)
image_size = gr.Slider(
label="图片大小",
minimum=320,
maximum=1280,
step=32,
value=640,
)
conf_threshold = gr.Slider(
label="阈值", #Confidence Threshold
minimum=0.0,
maximum=1.0,
step=0.1,
value=0.25,
)
yolov10_infer = gr.Button(value="Detect Objects")
with gr.Column():
output_image = gr.Image(type="numpy", label="处理后的图片")
yolov10_infer.click(
fn=yolov10_inference,
inputs=[
image,
model_id,
image_size,
conf_threshold,
],
outputs=[output_image],
)
gr.Examples(
examples=[
[
"ultralytics/assets/bus.jpg",
"yolov10s.pt",
640,
0.25,
],
[
"ultralytics/assets/zidane.jpg",
"yolov10s.pt",
640,
0.25,
],
],
fn=yolov10_inference,
inputs=[
image,
model_id,
image_size,
conf_threshold,
],
outputs=[output_image],
cache_examples=True,
)
gradio_app = gr.Blocks()
with gradio_app:
gr.HTML(
"""
<h1 style='text-align: center'>
YOLOv10
</h1>
""")
with gr.Row():
with gr.Column():
app()
gradio_app.launch(debug=True)
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