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We just launched a technical blog that will focus on building projects using Intel Movidius Neural Compute Stick and Neural Compute SDK. You can access the at https://movidius.github.io/blog/
EDIT: We now have several tutorials on running TensorFlow models on NCS
@GoldenWings, we ran into some bugs with respect to exporting TF models for inference, hence the delay. V1.12 has a fix, so I am curating the blog now. You can refer these examples until I have had a chance to polish & publish the blog.
MNIST example: https://github.com/ashwinvijayakumar/ncappzoo/tree/mnist/tensorflow/mnist
Fashion MNIST example: https://github.com/ashwinvijayakumar/ncappzoo/tree/fashion-mnist/tensorflow/fashion-mnist
A super-simple custom network trained on fashion MNIST: https://github.com/ashwinvijayakumar/ncappzoo/tree/single-conv/tensorflow/single-conv
Developer guide explaining the changes needed to export a model for inference: https://movidius.github.io/ncsdk/tf_compile_guidance.html
I study a project on "raspberry pi 3" with "The neural compute stick" in order to identify the quantity dragon fruit on a garden. Could you please give me some material "The neural compute stick".
Can you please put an example of object detection with the ncs?
@monotosh, I'll look into creating a blog on object detection, until then you refer the MobileNet_SSD and tiny YOLO examples on https://GitHub.com/Movidius/ncappzoo
@AshwinVijayakumar Any news about the blog on creating and running custom tensorflow on movidius ?
@AshwinVijayakumar: Is there any chance you can come up with an end-to-end solution from Keras -> movidius? Because I can not get this to work due to a myriad array of parser issues.
@pisymbol, I have been looking into converting Keras models to TF and then to Movidius, but no joy. Until we get Keras support on NCSDK, I am afraid our only option is to rewrite Keras models in TensorFlow (I know, it's super tedious).
@AshwinVijayakumar Can we make a custom image classifier with it ? Any example to do that? I am a newbee
@jaymj , not sure I understand the question. Are you asking if you can fine-tune a specific network with your own dataset? If so, here are some resources:
Caffe GoogLeNet dogs vs cats (same instructions can be used to train different networks with different datasets) - https://movidius.github.io/blog/deploying-custom-caffe-models/
Tensorflow MNIST trained on fashion-mnist dataset - https://github.com/ashwinvijayakumar/ncappzoo/tree/fashion-mnist/tensorflow/fashion-mnist
Custom network using TF - https://github.com/ashwinvijayakumar/ncappzoo/tree/single-conv/tensorflow/single-conv
Recommended workflow for running TF models on NCS - https://github.com/ashwinvijayakumar/ncappzoo/tree/tensorflow-template/tensorflow/mobilenets. You can use export_inference_graph to export different networks and datasets.
As mentioned earlier, we don't yet have a proven method/workflow to run Keras models on NCS.