Hello I want need more resources

[choimin1243]

I tried to make a wep aplication I use the webcam
But it doesnt work because of lack of resoureces

What should I do?

If I pay the more money can i get the more resoureces??

Actually i have a interested in video app

So i need more resoureces

How can I have more resources??

[dataprofessor]

Hi @choimin1243,

There’s actually quite a few tutorials on the topic of using webcam with Streamlit.

Streamlit provides the st.camera_input (st.camera_input - Streamlit Docs) command that can make use of user’s webcam. The previously link also provides a working example as well.

Additionally, here are a few that I found from Googling:

• GitHub - tconkling/streamlit-webcam
• Building a Web-Based Real-Time Computer Vision App with Streamlit - DEV Community
• Live Webcam with Streamlit. A web demo application for hand… | by Nicola Landro | MLearning.ai | Medium
• Real-Time Video Streams With Streamlit-WebRTC | by Ng Wai Foong | Better Programming

Hope this helps

[choimin1243]

No If only I can access the program I made, it’s fine, but if more than 6 people connect, I get a resource shortage error. Could you please help? I use opencv and machine learning algorithem

[dataprofessor]

Your app likely exceeded the default allowed resource allocation. Perhaps @Caroline could provide further recommendations on this?

[choimin1243]

Chaloline could u help me?? TT

1giga is enough for me to run machine learning? AnywAy

[choimin1243]

First of all, it’s nice to see someone I met on YouTube like this~ I’m enjoying your videos in Korea. The resource I can use is 1 GB per app. In my opinion, 1 gigabyte per app is not enough for more than 6 people to use the mideapipe library and opencv algorithm. Isn’t it? Anyway, I don’t know much about machine learning or coding.

[Caroline]

Hi @choimin1243, thanks for reaching out! apps on Streamlit Cloud are guaranteed 1GB but usually have access to 3GB, which is enough for most apps. That said, we don’t recommend deploying an app with Streamlit Cloud that trains an ML model, since that would require more resources. We also have a great blog post which covers some recommendations on minimizing resource consumption.