GC_computer_vision

Intro

Main repo for the Grocery Checkout Team's computer vision project

Setup

The data in this file is used in combination with the TF models file found here: https://github.com/tensorflow/models

1. Replace the protos file found at models\research\object_detection\Protos with the proto file found in this git. (Ignore this step if you have already set up tensorflow)
2. Move the vision_app.py file and model('ssd_resnet50' folder) to models\research\object_detection
3. Install the required packages using pip install -r requirements.txt, consider a virtual environment for this
4. run the vision_app.py file using terminal, a video screen will pop up if setup was done correctly

Creating a venv

to use this project you need a venv outside of this project directory. create one with virutalenv venv activate it with . venv/bin/activate deactivate it with deactivate when you want tp update the requirements.txt for everyone use pip freeze > requirements.txt (must be in the project directory)

Common Matplot Issue

to change matplotlib backend cd ~/.matplotlib touch maplotlibrc emacs matplotlibrc backend: TkAgg

Setup

Consider using a virtual environment for this project using:

virutalenv venv

Activate your venv using:

. venv/bin/activate

1. Install tensorflow

# For CPU
pip install tensorflow
# For GPU
pip install tensorflow-gpu

2. Install additional libraries

pip install --user Cython
pip install --user contextlib2
pip install --user pillow
pip install --user lxml
pip install --user jupyter
pip install --user matplotlib

3. Additionally, install any other required libraries using form the requirements.txt file using:

pip install -r requirements.txt

4. Clone tensorflow/models git: https://github.com/tensorflow/models

git clone https://github.com/tensorflow/models.git

5. Download the latest protobuf compiler from: https://github.com/protocolbuffers/protobuf/releases
6. Unzip the protoc and tensorflow/models-master files, and rename models-master to just models. You should have the following folders:
   • bin
   • include
   • models
7. Protobuf compilation:

# From tensorflow/models/research/
protoc object_detection/protos/*.proto --python_out=.

8. When running locally, the tensorflow/models/research/ and slim directories should be appended to PYTHONPATH. This can be done by running the following from tensorflow/models/research/:

# From tensorflow/models/research/
export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim

Note: This command needs to run from every new terminal you start. If you wish to avoid running this manually, you can add it as a new line to the end of your ~/.bashrc file, replacing pwd with the absolute path of tensorflow/models/research on your system.

9. To test your installation:

# from models/research/
python object_detection/builders/model_builder_test.py