app.py

from huggingface_hub import hf_hub_download
from inference import YOLOv10

model_file = hf_hub_download(
    repo_id="onnx-community/yolov10n", filename="onnx/model.onnx"
)

model = YOLOv10(model_file)

def detection(image, conf_threshold=0.3):
    image = cv2.resize(image, (model.input_width, model.input_height))
    new_image = model.detect_objects(image, conf_threshold)
    return new_image

import gradio as gr
from gradio_webrtc import WebRTC

css = """.my-group {max-width: 600px !important; max-height: 600px !important;}
         .my-column {display: flex !important; justify-content: center !important; align-items: center !important;}"""

with gr.Blocks(css=css) as demo:
    gr.HTML(
        """
        <h1 style='text-align: center'>
        YOLOv10 Webcam Stream (Powered by WebRTC ⚡️)
        </h1>
        """
    )
    with gr.Column(elem_classes=["my-column"]):
        with gr.Group(elem_classes=["my-group"]):
            image = WebRTC(label="Stream", rtc_configuration=rtc_configuration)
            conf_threshold = gr.Slider(
                label="Confidence Threshold",
                minimum=0.0,
                maximum=1.0,
                step=0.05,
                value=0.30,
            )

        image.stream(
            fn=detection, inputs=[image, conf_threshold], outputs=[image], time_limit=10
        )

if __name__ == "__main__":
    demo.launch()