Here's how I got Darkflow working: https://gist.github.com/simonw/0f93bec220be9cf8250533b603bf6...
For Darknet, I just ran "make" as documented here: https://pjreddie.com/darknet/install/ and then followed the instructions on https://pjreddie.com/darknet/yolo/ and https://pjreddie.com/darknet/nightmare/ to try it out.
For OpenCV classification tutorials this is another great resource to keep playing around with DIY projects. FYI avoid his email list unless you enjoy 3-4 sales emails every week.
> Rasp Pi + Camera/PIR to photograph birds
> Connect to internet and post to wp, twitter and instagram
The final aim is to add an AI component to see if we can detect birds and keep a count
Love the project.
which one is the cheapest and the most funnest to work with ?
The Google Vision Kit will run models on a custom neural processing chip connected to the Raspberry Pi Zero. With the DIY setup from the blog bost, the neural network runs on a "large pc" (potentially with GPU). Depending on the hardware you have at your disposal, you can run more complex (and therefore more powerful) neural networks. At the same time, you'll need wifi set-up and streaming to work. Completely embedded devices are easier to just put in the wild.
In theory, you should be able to use the models from the Vision Kit if you follow their instructions and just put the on a Raspberry Pi directly, and get an additional Movidius compute stick: https://developer.movidius.com/