This is a simple face recognition example of using deep learning to recognise faces within a picture. It originates from Adrian Rosebrock's article -- Face recognition with OpenCV, Python, and deep learning.
See the GitHub repository for examples of its usage: https://github.com/simonzhaoms/facematch
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To install and demonstrate the algorithm:
$ pip3 install mlhub $ ml install facematch $ ml configure facematch $ ml demo facematch
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To recognise an arbitrary person who can be found in the Internet, you can just type:
$ ml score facematchIt will use Microsoft Bing image search API to search a person's photo you want to recognise. In order to use the API, you must have a subcription key. A 7-days free account can be created at https://azure.microsoft.com/en-us/try/cognitive-services/?api=search-api-v7
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To match you in camera:
$ ml score facematch --capture --cameraIt will open your camera to capture 5 photos of you to generate your face database, then recognise you in a live camera video.
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You can also provide the path or URL of a person's photos via option
--data, and let facematch to recognise him/her in a photo via the option--match:$ ml score facematch --data <photo-of-the-person> --match <photo-for-recognition>or video via the option
--video:$ ml score facematch --data <photo-of-the-person> --video <video-for-recognition>
The photos used for recognition here are collected by using Bing image search API. The code for collecting photos is adapted from How to (quickly) build a deep learning image dataset.
In the interactive mode of ml score facematch, a subscription key of
Bing image search API is required. You can get 7-days free account
together with a subscription key at Try Microsoft Azure Cognitive
Services.
More details about how to use Bing image search API can be found at