Eric Hofesmann, Aman Kumar Jha, Preet Gill, Vihang Agarwal
Entertaining and Training your dog while you are away.
Using state-of-the-art computer vision algorithms, this dog localization and activity recognition system can determine what your dog is doing from a home surveillance camera.
| Mean | Standard Deviation | Random Chance |
|---|---|---|
| 68.41 | 6.10 | 50.00 |
Across 5 splits given in tfrecords_pawpal/split.npy in the dataset download link below
Python 3.5
OpenCV
Tensorflow 1.0.0
Cython
Darkflow for Yolo
M-PACT Activity Recognition Platform
Detailed installation instructions below.
Follow instructions below to install darkflow and PawPal
git clone https://github.com/thtrieu/darkflow
virtualenv -p python3.5 env
source env/bin/activate
pip install tensorflow==1.0.0
pip install Cython
pip install opencv-python
cd darkflow
sudo apt-get install python3 python-dev python3-dev \
build-essential libssl-dev libffi-dev \
libxml2-dev libxslt1-dev zlib1g-dev \
python-pip
pip install -e .
flow (ignore any errors)
cd ..
git clone https://github.com/ehofesmann/PawPal/
cd PawPal
Download the weights for C3D Download link
Download yolo.weights Download link
mv ~/Downloads/checkpoint-532.npy ./c3d/
mv ~/Downloads/yolo.weights ../darkflow/bin/
Update the /path/to/darkflow in detect_video.py
python detect_video.py --vidpath example/example1.mp4
python detect_video.py --vidpath example/example1.mp4
Dog biting vs non biting tfrecords dataset Download link
Install M-PACT and copy PawPal/c3d/c3d_frozen into the models directory of M-PACT