The movidius ncs compute capability comes from its myriad 2 vpu vision processing unit.
Intel movidius neural compute stick 3.
The conversion from fp32 to fp16 can cause minor rounding issues to occur in the inference results and this is where the mvnccheck tool can come in handy.
It is compatible with two dnn frameworks such as tensorflow and caffe.
Based on the intel movidius myriad x vpu and supported by the intel distribution of openvino toolkit the intel ncs 2 delivers greater performance boost over the previous generation.
The frameworks standards technique used are.
As you can see from the above graph the higher end mobilenets with depthmultiplier 1 0 and input image size 224x224 with a top5 accuracy of 89 5 runs at 9x the speed fps when an intel movidius neural compute stick is attached to the raspberry pi compared to running it natively on the raspberry pi 3 using the cpu.
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The movidius neural compute stick ncs is produced by intel and can be run without an internet connection.
It can be used in ubuntu 16 04 or raspberry pi 3.
Powered by the intel movidius myriad x vpu the intel neural compute stick 2 accelerates deep learning development for edge devices.
This episode of the iot developer show features two demos that showcase the movidius neural compute stick.
Profiling tuning and compiling a dnn on a development computer with the tools are provided in the intel movidius neural compute sdk.
With the help of intel movidius neural compute usb stick with raspberry pi 3 we are using it for image classification and an object recognizing application.
Since the intel movidius neural compute stick and ncsdk use 16 bit floating point data it must convert the incoming 32 bit floating point data to 16 bit floats.
Check out the intel movidius neural compute app.
Purchase your intel neural compute stick 2 from one of our trusted partners.
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Speed prototyping for your deep neural network application with the new intel neural compute stick 2 ncs 2.
Also check out the getting started videos for your platform.
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