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import gradio as gr
import cv2
from huggingface_hub import hf_hub_download
from gradio_webrtc import WebRTC
from twilio.rest import Client
import os
from inference import YOLOv10
model_file = hf_hub_download(
repo_id="onnx-community/yolov10n", filename="onnx/model.onnx"
)
model = YOLOv10(model_file)
account_sid = os.environ.get("TWILIO_ACCOUNT_SID")
auth_token = os.environ.get("TWILIO_AUTH_TOKEN")
client = Client(account_sid, auth_token)
token = client.tokens.create()
rtc_configuration = {
"iceServers": token.ice_servers,
"iceTransportPolicy": "relay",
}
rtc_configuration = None
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
css = """.my-group {max-width: 600px !important; max-height: 600 !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>
"""
)
gr.HTML(
"""
<h3 style='text-align: center'>
<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.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.webrtc_stream(
fn=detection, inputs=[image, conf_threshold], stream_every=0.05, time_limit=30,
concurrency_limit=10
)
if __name__ == "__main__":
demo.launch()
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