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Object detection neural network for detecting a MacBook Air

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Detect MacBook Air

Use an object detection neural network to detect a Mac in images.

Instructions

Get this code:

git clone --recursive https://github.com/WSU-RAS/detect-laptop
cd detect-laptop

Labeling images

Then, to label them in Sloth (see my Arch PKGBUILD):

./gen_sloth.sh
./annotate.sh # 'f' to label as laptop, space for next, Ctrl+S to save

Convert TensorFlow {tftrain,tfvalid,tftest}.record files:

./sloth2tf.py

Get pre-trained TensorFlow networks

wget http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_coco_2018_01_28.tar.gz
wget http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_0.75_depth_quantized_300x300_coco14_sync_2018_07_18.tar.gz
wget http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_ppn_shared_box_predictor_300x300_coco14_sync_2018_07_03.tar.gz
for i in *.tar.gz; do tar xaf $i; done

Fix bug

To fix a bug, in models/research/object_detection/metrics/coco_tools.py change

results.dataset['categories'] = copy.deepcopy(self.dataset['categories'])

to

results.dataset['categories'] = self.dataset['categories']

Training

Uncomment the model you wish to train in config.sh.

Install dependencies:

sudo pacman -S cython
pip install --user pycocotools

Then run training and monitor the results:

./train.sh
tensorboard --logdir float:object_detection_models.float,quantized:object_detection_models.quantized,ppn:object_detection_models.ppn

Export model

Export the model for TensorFlow Lite:

./export.sh

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  • Python 82.1%
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