I have been trying to implement an api to integrate with live meeting to face recognize. Not sure if Ms teams allows access to the live video.
We can include Preciate to our Microsoft Teams to add Employees Recognition and also we have Recognize which is an extension for Employee Recognition for MS Teams.
Also, we have something called Face under Cognitive Service in Microsoft Azure which is used for Identity verification.
We can detect faces using few Clients Library SDK’s and has a guide to Detect and analyze face.
Here is a quick start for using face library with multiple languages such as C#, Go, JavaScript, Python and Rest API.
Device capabilities, Tab Device Permission Demo - These documentation will help you to capture the images in the video. But there isn't any API to implement face recognition in Microsoft teams.
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I am working on a real-time problem to identify an emotion of the music. I would to do this with Azure bot framework and my challenge here is to make bot which I create to accept the music file upload mechanism in between the chat conversation and need to identify the emotion of the music and categorize it.
The thing I also want to make my bot to identify is the original album recognition of the music bit uploaded.
I hope this sounds crazy, but I would like to combine azure bot services, cognitive services and natural language processing to work in my bot.
Any solution for this!
In combine, there is no such solution till now as new voices are added recently into the speech algorithms. There is a possibility to do this individually.
Create a chatbot with azure bot framework and enable to upload the files
https://learn.microsoft.com/en-us/microsoftteams/platform/resources/bot-v3/bots-files
When the files are uploaded, it must be connected to a logic app where cognitive services are enabled.
Perform the task internally and present the result in the chat.
There are new language updates came out.
https://azure.microsoft.com/en-us/blog/announcing-new-voices-and-emotions-to-azure-neural-text-to-speech/
How do I add filters or process the live video stream in Aws elemental medialive like putting face filters and AR effects in my own code?
MediaLive does not have an in-built capability to apply filters to live video stream.
You might want to look into Amazon Rekognition service. This service enables you to identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content using machine learning. You will use the service API to query the image or video stored on S3.
Here is a good primer for this service's capabilities.
A C# Example for using Micorosft Cognitive Vision API on Real time videos can be found here. https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/vision-api-how-to-topics/howtoanalyzevideo_vision
I cannot find something similar for Python.
How would I go about do that in Python?
I am developing a Python application for real-time translation. I need to recognize speech in real time: as user says something it automatically sends this piece of audio to Google Speech API and returns a text. So I want the recognized text appearing immediately while speaking.
I've found Streaming Speech Recognition but it seems that I still need to record the full speech first and then send it to the server. Also, there are no examples of how to use it in Python
Is it possible to do this with Google Speech API?
You can do it with Google Speech API.
But, it has a 1 minute content limit.
Please check the link below.
https://cloud.google.com/speech/quotas
So you have to restart every 1 minute.
and the link below is example code of microphone streaming by python.
https://cloud.google.com/speech/docs/streaming-recognize#speech-streaming-recognize-python
Check this link out:
https://github.com/Uberi/speech_recognition/blob/master/examples/microphone_recognition.py
This is an example for obtaining audio from the microphone. There are several components for the recognition process. In my experience the Sphinx Recognition lacks on accuracy. The Google Speech Recognition works very well.
Working with Google Speech API for real-time transcription is a bit cumbersome. You can use this repository for inspiration
https://github.com/saharmor/realtime-transcription
It transcribes client-side's microphone in real-time (disclaimer: I'm the author).
I have developed a face recognition software.It detects and identify human faces infront of the connected web camera.Now I need to deploy it in a website.so that,Anyone with a computer should be able to access this service through this website and should be able to perform face detection and identification using the camera in his premises.
Is it possible to integrate python application with website?
Is Django framework is suitable for my work?
Can anybody recommed any tutorials in this direction?
This has got absolutely nothing to do with Django. Django is running in your server, whereas you need to capture image at your client. Therefore it has to do about your front-end and not your back-end.
Traditionally this has been a feature not at all possible. A web browser could not access the client's peripherals and end of story. Flash, activex etc have been workarounds for this.
HTML5 now allows it. Read more on MDN about MediaDevices.getUserMedia().
Unfortunately this is still fresh at the time of writing and is only supported by some browser versions: read more on caniuse.com.
You could use some js library for feature detection such as modernizr.