Tool for creating nanowire tools with the flask structure.
Project description
Nanowire flask
This library is designed to allow a python developer to easily create a nanowire plugin using the flask APIs structure.
The function you mount, using the class ImagesAPI, must have the arguments img and variables if you want initialise a model or other variables when the sever starts you may make the function to be mounted into a function of a class which is initiated with the desired variables. In this case your variables will be self, img and variables. You should expect img to be a PIL RGB image object and variables to be a dictionary containing the variables sent to the plugin in the curl request.
The curl requests for images may be formatted 2 ways. The first involves sending the image as a file attached to the curl request. For example:
curl -F "image=@./1.jpg" -XPOST http://0.0.0.0:5000/model/predict?threshold=0.5
alternativly the file may be sent as a link using a dictionary eg.
curl -X POST -H "Content-Type:application/json" -d '{"contentURL":"http://127.0.0.1:8000/1.jpg", "threshold":0.5}' http://0.0.0.0:5000/model/predict
At the moment it can only handle images however it will soon be expanded to handle text and eventually video and sound. The currently supported image formats are:
jpg
png
bmp
tif
ppm
Notes for advanced users
mount_Image_function
Parameters
function:- The function to be mounted on the API. The function must take img and variable as arguments and return a dictionary
debug_mode:- Activate or deactivate debug mode. When active will return full traceback from API when an error occurs during processing.Input must be boolean
host:- default is ‘0.0.0.0’. Set the IP address to host the API on
port:- default 5000. Set the port to host the API on
path:- default ‘/model/predict’. Set the path for the API
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