Computer Vision Best Practice
This MLHub package provides a demo of Microsoft's Computer Vision Best Practice repository available from https://github.com/microsoft/ComputerVision, providing examples and command line tools for computer vision tasks. A collection of pre-built Computer Vision models are exposed as command line tools building on the notebook examples from the repository.
Visit the github repository for more details: https://github.com/microsoft/cvbp
- To install mlhub (Ubuntu)
$ pip3 install mlhub
- To install and configure the package:
$ ml install cvbp $ ml configure cvbp
Command Line Tools
A demonstration of the package is presented below using the demo command. The package also provides a number of useful command line tools which we introduce here.
The tag command will identify the dominant object in a photo with a reported level of confidence. The confidence and tag and filename are returned from the command, and can be piped on to other commands within a command line to, for example, add the tag to the meta-data of the image file.
This first example is classified 100% as a koala.
$ ml tag cvbp https://upload.wikimedia.org/wikipedia/commons/2/2d/Koala_in_Australia.JPG 1.00,koala,https://upload.wikimedia.org/wikipedia/commons/2/2d/Koala_in_Australia.JPG
Perhaps we would like to download this photo and then add the appropriate tag to it:
$ wget https://upload.wikimedia.org/wikipedia/commons/2/2d/Koala_in_Australia.JPG -O koala.jpg $ ml tag cvbp koala.jpg | cut -d, -f2 | xargs bash -c 'mogrify -comment $0 koala.jpg' $ exiftool koala.jpg | grep -i comment Comment : koala
Here we identify the primary tag for a collection of photos.
$ ml tag cvbp image_*.png 0.78,chickadee,image_01_bw_color.png 1.00,custard_apple,image_02_bw_color.png 0.98,echidna,image_03_bw_color.png 0.45,clumber,image_04_bw_color.png 1.00,beacon,image_05_bw_color.png 0.49,Tibetan_terrier,image_06_bw_color.png 0.90,great_white_shark,image_07_bw_color.png 0.65,bell_pepper,image_09_bw_color.png 0.87,redshank,image_10_bw_color.png
Perhaps we wish to add a tag to each photo in the current folder:
$ ml tag cvbp *.jpg | cut -d, -f2,3 | tr ',' ' ' | xargs -d'\n' -n1 bash -c 'mogrify -comment $0 $1'
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