View extension framework

[gheinrich]

This implements a visualization framework along the lines of:

Depends on #731

A rawData view extension is added and selected by default to show the network output in the same way as in the original generic type of networks.

[lukeyeager]

I tested the gradient workflow and it's working well for me. But isn't it supposed to draw a red arrow in the direction of the gradient when you test an image? I thought I saw a screenshot from you that did that. Maybe I'll find out what I'm doing wrong when I dig into the code review ...

[lukeyeager]

Seems like we should also show the gradient datasets if we're showing the models

[gheinrich]

That's the rawData visualization - it's just showing the raw data. To see the little arrows you need to select the gradient visualization (which isn't in this PR - it's in e8001f8 if you're curious to try). The screenshot was on the PR description for #735 - sorry it's confusing!)

[lukeyeager]

Whoops, my bad. I got confused.

[lukeyeager]

Our new URLs seem a little weird:

# classification (old)
/datasets/images/classification/new
/models/images/classification/new
# generic (old)
/datasets/images/generic/new
/models/images/generic/new
# gradients (new)
/datasets/generic/new/image-gradients
/models/images/generic/new?extension_id=image-gradients

Why the inconsistency? I like the move to /[datasets|models]/generic/new, why doesn't that work for models? And why does one specify the extension in the query string but the other doesn't?

[gheinrich]

I like the move to /[datasets|models]/generic/new, why doesn't that work for models?

The generic datasets now support any 3D data (barring bugs). I initially wanted to add generic models too to handle any 3D data but realized that it would be a huge change. We'd have to change a lot of the training and inference paths. So I thought as a first step we could use the existing image/generic models with both the image/generic datasets and the generic datasets.

And why does one specify the extension in the query string but the other doesn't?

No strong reason actually - I didn't know how to make the inference_id parameter optional when using URLs in the form of /models/images/generic/new/<extension_id>.

[lukeyeager]

Ok, I figured you had a good reason for not creating /models/generic/. I agree we don't need to do all that work now, but I look forward to being able to do it eventually and to convert all datasets to /datasets/generic and all models to /models/generic, or whatever we end up calling them.

I didn't know how to make the inference_id parameter optional when using URLs in the form of /models/images/generic/new/<extension_id>.

This oughta work:
http://stackoverflow.com/questions/14032066/flask-optional-url-parameters

[gheinrich]

And why does one specify the extension in the query string but the other doesn't?

I have updated the "Generic datasets" commit to fix this. For image gradients, routes now look like:

# gradients (new)
/datasets/generic/new/image-gradients
/models/images/generic/new/image-gradients

If the extension ID is unspecified in the model creation URL, then this defaults to the "other" kind of datasets.