mirror of
https://github.com/HumanAIGC-Engineering/gradio-webrtc.git
synced 2026-02-04 17:39:23 +08:00
101 lines
3.0 KiB
Python
101 lines
3.0 KiB
Python
import logging
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import os
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import random
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import cv2
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import gradio as gr
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from gradio_webrtc import AdditionalOutputs, WebRTC
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from huggingface_hub import hf_hub_download
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from inference import YOLOv10
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from twilio.rest import Client
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# Configure the root logger to WARNING to suppress debug messages from other libraries
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logging.basicConfig(level=logging.WARNING)
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# Create a console handler
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console_handler = logging.FileHandler("gradio_webrtc.log")
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console_handler.setLevel(logging.DEBUG)
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# Create a formatter
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formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
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console_handler.setFormatter(formatter)
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# Configure the logger for your specific library
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logger = logging.getLogger("gradio_webrtc")
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logger.setLevel(logging.DEBUG)
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logger.addHandler(console_handler)
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model_file = hf_hub_download(
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repo_id="onnx-community/yolov10n", filename="onnx/model.onnx"
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)
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model = YOLOv10(model_file)
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account_sid = os.environ.get("TWILIO_ACCOUNT_SID")
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auth_token = os.environ.get("TWILIO_AUTH_TOKEN")
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if account_sid and auth_token:
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client = Client(account_sid, auth_token)
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token = client.tokens.create()
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rtc_configuration = {
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"iceServers": token.ice_servers,
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"iceTransportPolicy": "relay",
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}
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else:
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rtc_configuration = None
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def detection(frame, conf_threshold=0.3):
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print("frame.shape", frame.shape)
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frame = cv2.flip(frame, 0)
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return AdditionalOutputs(1)
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css = """.my-group {max-width: 600px !important; max-height: 600 !important;}
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.my-column {display: flex !important; justify-content: center !important; align-items: center !important};"""
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with gr.Blocks(css=css) as demo:
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gr.HTML(
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"""
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<h1 style='text-align: center'>
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YOLOv10 Webcam Stream (Powered by WebRTC ⚡️)
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</h1>
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"""
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)
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gr.HTML(
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"""
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<h3 style='text-align: center'>
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<a href='https://arxiv.org/abs/2405.14458' target='_blank'>arXiv</a> | <a href='https://github.com/THU-MIG/yolov10' target='_blank'>github</a>
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</h3>
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"""
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)
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with gr.Column(elem_classes=["my-column"]):
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with gr.Group(elem_classes=["my-group"]):
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image = WebRTC(
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label="Stream", rtc_configuration=rtc_configuration,
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mode="send",
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track_constraints={"width": {"exact": 800},
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"height": {"exact": 600},
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"aspectRatio": {"exact": 1.33333}
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},
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rtp_params={"degradationPreference": "maintain-resolution"}
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)
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conf_threshold = gr.Slider(
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label="Confidence Threshold",
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minimum=0.0,
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maximum=1.0,
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step=0.05,
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value=0.30,
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)
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number = gr.Number()
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image.stream(
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fn=detection, inputs=[image, conf_threshold], outputs=[image], time_limit=10
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)
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image.on_additional_outputs(lambda n: n, outputs=number)
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demo.launch()
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