Real-time browser-ready computer vision apps with Streamlit｜Yuichiro Tachibana｜PyCon APAC 2022

PyCon APAC 2022｜一般演講 Talks｜國泰金控 Cathay Financial Holdings / 美光科技 Micron 冠名贊助

✏️ 共筆 Note：https://hackmd.io/@pycontw/HkTp86XJs 🖐🏻 Slido：https://app.sli.do/event/peUkfwVcPamsp56SBtkm8W 💬 語言 Language：英文 English 🎯 層級 Level：中階 Intermediate 🔎 分類 Category：其他 Other

💡 摘要 Abstract 💡 By using Streamlit and streamlit-webrtc, we can create web-based real-time computer vision apps only with ~10 or 20 additional lines of Python code. It's a new easy way to turn computer vision models into web-based demos and has some advantages over the conventional ways which use OpenCV. In this talk, I will demonstrate the development process using these libraries and show a variety of examples so that we see how easy and useful they are and can make use of them in daily development and research.

🪄 說明 Description 🪄 Streamlit is a fast-growing framework with which developers can build web-based data apps only with Python code. streamlit-webrtc is a custom component for Streamlit which allows to use real-time video/audio streams on Streamlit apps. With a combination of these libraries, we can create web-based real-time video apps quickly. The speaker is the author of streamlit-webrtc, and has been selected as a member of the Streamlit Creators program for the contributions including it.

A lightning talk about these technologies at PyCon JP 2021 is available: https://youtu.be/_LuLs8H1gJc

About development using these libraries, following articles have been published:

• Developing Web-Based Real-Time Video/Audio Processing Apps Quickly with Streamlit
• Real-Time Video Streams With Streamlit-WebRTC As linked from the streamlit-webrtc repo, demo apps I have developed are available online:
• Demo showcase including real-time object detection: https://share.streamlit.io/whitphx/streamlit-webrtc-example/main/app.py
  • Source code: https://github.com/whitphx/streamlit-webrtc-example/blob/main/app.py
• Real-time Speech-to-Text: https://share.streamlit.io/whitphx/streamlit-stt-app/main/app_deepspeech.py
  • Source code: https://github.com/whitphx/streamlit-stt-app
• Real-time style transfer: https://share.streamlit.io/whitphx/style-transfer-web-app/main/app.py
  • Source code: https://share.streamlit.io/whitphx/style-transfer-web-app/main/app.py
• Real-time Tokyo 2020 Pictogram: https://share.streamlit.io/whitphx/tokyo2020-pictogram-using-mediapipe/streamlit-app
  • Source code: https://github.com/whitphx/Tokyo2020-Pictogram-using-MediaPipe
• Video chat: online demo is not available because it does not have an auth mechanism and is only for private use.
  • Source code: https://github.com/whitphx/streamlit-video-chat-example

🚀 關於講者 About Speaker - Yuichiro Tachibana 🚀 Yuichiro works as a professional software developer and also loves contributing to OSS projects. As a Pythonista, he has participated in various projects including web development, multimedia streaming, data management, computer vision, and machine learning.

#pycontw #pyconapac2022 #python #opencv #streamlit #webrtc #computervision

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