Here are few steps required to get Imagenet based on OpenCV working DB845c
################## on HOST     ###################################
For some reason SNPE looks at /proc/cpuinfo to figure out the soc info, this patch should make it happy for DB845c
http://people.linaro.org/~srinivas.kandagatla/0001-HACK-arm64-cpuinfo-Make-SNPE-happy-on-DB845c.patch
Make sure that you have included this in your kernel before testing.

################# on TARGET DB845c ###############################
Step 1: Build new fastrpc lib on DB845c
$ git clone -b  automake https://git.linaro.org/landing-teams/working/qualcomm/fastrpc.git
$ cd fastrpc
$ ./gitcompile
$ make install

Step 2: download Qualcomm Neural Processing SDK for AI version snpe-1.30.0.480 from
  https://developer.qualcomm.com/software/qualcomm-neural-processing-sdk
and Unzip into /home/linaro folder as /home/linaro/snpe-1.30.0.480/
$ cp 
$ mount /dev/disk/by-partlabel/dsp_a /dsp
$ cp /home/linaro/snpe-1.30.0.480/lib/dsp/* /dsp/cdsp/

Step 3: Start CDSP and userspace cdsprpcd deamon

# start cdsp if its not already started.
$ echo start >/sys/devices/platform/remoteproc-cdsp/remoteproc/remoteproc1/state
#Run qrtr services if they have not already started
$ qrtr-cfg 1 && qrtr-ns && rmtfs -v &
#Mount dsp partition
#export libcdsp path.
$ export ADSP_LIBRARY_PATH=/dsp/cdsp
#Start cdsp deamon
$ cdsprpcd&

Step 4: Install OpenCV on the Target

$ sudo apt-get install libopencv-dev python3-opencv

Step 5: Build SNPE Demo application and run
## To Build ##
$ git clone  https://git.linaro.org/people/srinivas.kandagatla/SNPEMobileNetCv.git 
$ cd SNPEMobileNetCv
$ mkdir build
$ cd build
$ cmake ..
$ make
$ export LD_LIBRARY_PATH=/home/linaro/snpe-1.30.0.480/lib/aarch64-linux-gcc4.9/
$ ./SNPEMobileNetSSDCv

This should show up a live video with MoblieNet SSD detections with boxes