A Real Time Object Detection application on iOS using Tensorflow and pre-trained COCO dataset models. Video frames are captured and inference is done locally using the provided mobilenet models. Both Swift and Objective-C projects.
An Object Detection application on iOS using Tensorflow and pre-trained COCO dataset models. Video frames are captured and inference is done locally using one of the 3 provided models: ssd_mobilenet_v1_coco, ssd_modelnet_v2_coco, or ssd_inception_v2_coco. Both Swift and Objective-C projects.
brew install automake libtool
git clone https://github.com/tensorflow/tensorflow
cd
into the tensorflow repo and at a minimum checkout the v1.5.0
tag. The v1.5.0 release has the Makefile support for the following ANDROID_TYPES
environment variable. I have tested up to v1.12.0
git checkout origin/r1.11
if you run into this issue: thread-local storage is not supported for the current target, you may need to edit the two files affected. The following one-liners worked for me:
gsed '/ifeq[^,]*,I386)/!b;n;n;n;n;n;s/thread_local//' < ./tensorflow/contrib/makefile/Makefile > foo; mv foo ./tensorflow/contrib/makefile/Makefile
gsed 's/thread_local int per_thread_max_parallism/__thread int per_thread_max_parallism/' < tensorflow/core/util/work_sharder.cc > foo; mv foo ./tensorflow/core/util/work_sharder.cc
You can get gsed
using homebrew: brew install gnu-sed
export ANDROID_TYPES="-D__ANDROID_TYPES_FULL__"
tensorflow/contrib/makefile/build_all_ios.sh
Go get a coffee. This can take a while. On my macBook it took almost 2 hours.
TENSORFLOW_ROOT=/Users/username/Development/tensorflow