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Survey: Feedback and Improvements

Please feel free to add any comments by replying to this thread.


  • 17 Comments sorted by Votes Date Added
  • Api corresponding to distributed processing to multiple sticks is necessary, not cyclic processing.

  • Support for Tensorflow mobilenet SSD. The blog posts at are quite good - additional topics by the same authors would be helpful.

  • I hope to see support for Mask R-CNN very soon.

  • @GoldenWings Thanks for the input. Any other suggestions or features you guys would want to see?

  • Would like to see support for squeezenet and Tensorflow mobilenet SSD object detection.

  • I would in general like to see more support for different tensorflow ops. This would enable greater freedom in design of networks which would be really cool. :) Also more tutorials for maybe custom Networks. :)

  • Tutorials on getting new networks not already in the ncappzoo working on the sticks. Like DSOD - Densely Supervised Object Detectors. MobileNets-SSD is slow to train on Caffe. (and will remain until they start supporting an efficient Depthwise Separable Layer, in Caffe-SSD)

  • @trevor you should be able to use this link for training SSD with efficient DWS convolution with CUDNN9:

  • Please support Keras. I have everything setup with Keras in Ubuntu. I do not see particular reason to add Caffe in my system other than Movidius stick. Untill then example graph files that can be deployed in RPi would be appreciated.

  • How to use and your own classifications, mnvcompile and use it on the stick.

  • edited July 31 Vote Up0Vote Down
    1. Yolo support in all flavors ( not just tiny .. I prefer correct classification above fast&wrong )
      I would like to try Yolo v2 and v3...
    2. tested and forgiving installation script ( It's not fun to install NCSDK2 under Ubuntu studio/Mate 16.04/18.04 )
    3. Update all samples from appzoo to run under version 2
    4. Movidius "under the hood", low level api ?

    Release date for Movidius X ??? ( this year !? )

  • It would be great if the stick will support Pytorch in the future

  • 1) NCS kit in general is messy and loaded with Python dependencies. Straight C/C++ solutions would be best and a little python maybe for conversion / support.
    2) just fails in so many ways on a vanilla clean install Ubuntu 16.04 - like it was never really tested.
    3) find a way to enable a broader support community by open sourcing more tools (e.g. myriad compilers) and selecting a few outside partners to support smaller hobbyist / maker types.
    4) get a partner program going - important to all of the above items

  • 1 request is MobileNet SSD for TensorFlow.

    It would also be nice for better Raspberry Pi / TinkerBoard support during installation and compilation.

  • Internal processing FP32 compatible

    • Correspondence to FusedBatchNormV2
    • Correspondence to Caffe-Segnet
    • Correspondence to caffe-jacinto
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