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node-red-contrib-fv-detection-nodes
Advanced tools
Readme
Package contains the following nodes:
onprem-upload - runs prediction on an uploaded image file
onprem-snap - runs prediction on a captured image from detected camera
cloud-upload - runs prediction in the cloud on image file
Configure Camera - Sets a configuration on the selected vision camera
Release Camera - Releases camera acquisition of the selected vision camera
Open Camera - Starts camera acquisition of the selected vision camera
Disclaimer: To use the onprem nodes you must have a running Flexible Vision ONPREM SERVER.
Cloud Upload Setup
This node allows you to quickly deploy your AI vision models on your edge device. The following simple tutorial will have you creating and running your AI models in under 10 minutes.
Create a free Flexible Vision account by entering your email and password.
Install the node-red-contrib-fv-detection-nodes node via the Manage Pallet tool within node-red.
You can optionally install the node to your node-modules folder through your typical npm terminal command: npm install node-red-contrib-fv-detection-nodes
Install the optional camerapi node if acquiring an image through the raspberry pi camera. Otherwise skip this step.
Import the following flow into your node-red sketch:
[{"id":"3fcba4be.c7525c","type":"inject","z":"dbed9a85.13e278","name":"","topic":"","payload":"","payloadType":"date","repeat":"60","crontab":"","once":false,"onceDelay":0.1,"x":130,"y":140,"wires":[["20e65868.257208"]]},{"id":"20e65868.257208","type":"camerapi-takephoto","z":"dbed9a85.13e278","filemode":"1","filename":"image.jpg","filedefpath":"1","filepath":"","fileformat":"jpeg","resolution":"10","rotation":"0","fliph":"0","flipv":"0","brightness":"50","contrast":"0","sharpness":"0","quality":"80","imageeffect":"none","exposuremode":"auto","iso":"0","agcwait":"1.0","led":"0","awb":"auto","name":"","x":300,"y":140,"wires":[["98730e7f.472a3"]]},{"id":"98730e7f.472a3","type":"file in","z":"dbed9a85.13e278","name":"Save Image","filename":"/home/pi/Pictures/image.jpg","format":"utf8","chunk":false,"sendError":false,"encoding":"none","x":470,"y":140,"wires":[["89060b2d.967d38"]]},{"id":"89060b2d.967d38","type":"cloud-upload","z":"dbed9a85.13e278","username":"","password":"","project":"","auth":"","x":770,"y":140,"wires":[["934e64b.c25f298"]]},{"id":"934e64b.c25f298","type":"debug","z":"dbed9a85.13e278","name":"","active":true,"tosidebar":true,"console":false,"tostatus":false,"complete":"false","x":1090,"y":140,"wires":[]}]
Double click on the Cloud Upload Node and type in your Flexible Vision username and password.
Select Example Project from projects list.
Click “Done”, then click “Deploy”.
Within the debug window you can see all of the objects found in its raw json format. You can also visually see your results by logging into your Flexible Vision portal and reviewing your Detection History.
Visit the Resource Center for more information.
FAQs
Flexible Vision Detection Nodes
The npm package node-red-contrib-fv-detection-nodes receives a total of 4 weekly downloads. As such, node-red-contrib-fv-detection-nodes popularity was classified as not popular.
We found that node-red-contrib-fv-detection-nodes demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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