5 ms·
X is in the range 0, 255. They don't show code converting it to a much saner range for the network they've chosen. Is the full source somewhere?
by ipunchghosts 10y ago
X is in the range 0, 255. They don't show code converting it to a much saner range for the network they've chosen. Is the full source somewhere?
- cr0sh 10y agoHave you already looked at the pickled data? Because it looks like the model is outputting a single label value out of 256 labels; depending on the training data (steering angle) and how it is represented in the data (signed float or integer?), each one of those 256 learned should (?) be similar - I think. Again, I'm not an expert. Or - maybe it is outputting a number 0-255, and then taking that number and converting it (and maybe other operations) into values suitable for the servo on the car (perhaps centered around 0 - so -128 to 127 or something like that - then scaled for servo PPM width or whatever values needed)... All guesses, of course.
- wroscoe 10y agoThe input values are image arrays 120x160 pixels with 3 channels for red,green,blue. The values range from 0-255 and are not normalized before they are fed into the convolution layer. I found this did not make a difference. The output of the model is a single real number between -90(left) and 90(right). I believe a better approach would be to bin the outputs and use a classifier. This way you'd know when the model was getting confused (ie, approaching a perpendicular line.
- cr0sh 10y agoAlso the full repo is mentioned (I think the article is just a general highlighting of the full repo): https://github.com/wroscoe/donkey https://github.com/wroscoe/donkey