Hi Mark,
Yes, you are right the weight file is currently missing. I had hoped to submit the neural network model and code to the Wolfram Neural Network Repository. However, the actual numerical weight values come from another developer's TensorFlow implementation. Unfortunately that developer hasn't attached clear licensing conditions to the project. I had written to the developer asking for express permission to use those weight values (with proper credit of course), but I haven't heard back. So reluctantly I felt obliged to refrain from distributing the neural network file which contains those weights.
Sorry about this.
Meanwhile options seem to be to either:
1)
Actually train against a dataset. The easy part is downloading a suitable dataset. Slightly more work would be to implement the target decoder, ie the logic that maps the target bounding boxes back into the desired neural net outputs. Additionally I have heard that hard negative mining may be needed to train this net, but I am a bit vague on the details.
2)
Use someone else's weights that has a liberal license attached. There is a CAFFE implementation:
https://github.com/weiliu89/caffe/tree/ssd
which could be used and has a liberal license. I haven't much experience with CAFFE so I haven't gone down that route. Basically what is required is the ability to dig the weights out of the CAFFE file and save them into a format that Mathematica can read. I have found that JSON works well for fairly small files, but HDF works better for larger neural nets, hence I generally prefer HDF.
In either case the ModelConverters/SSDConverter.m file is helpful as that builds the network structure. It just needs the numerical weights from an HDF file.
Sorry there's not an easier fix. I'll have a look at going down option 2), but I am quite busy at the moment, so it may not be for a few weeks.
Kind regards,
Julian.
