ASH1998 / playing-with-tensorflow-object-detection

This is a play code for me to get acquainted with tensorflow object detection api

playing-with-tensorflow-object-detection

This is a play code for me to get acquainted with tensorflow object detection api

These are some sample images trained :

Useful links :

There are a lot of dependencies and installation procedure check out this link : Models of tensorflow api clone this link and go to object_detection directory and paste the code

Installation

Dependencies

Tensorflow Object Detection API depends on the following libraries:

• Protobuf 2.6
• Pillow 1.0
• lxml
• tf Slim (which is included in the "tensorflow/models" checkout)
• Jupyter notebook
• Matplotlib
• Tensorflow

For detailed steps to install Tensorflow, follow the Tensorflow installation instructions. A typically user can install Tensorflow using one of the following commands:

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

The remaining libraries can be installed on Ubuntu 16.04 using via apt-get:

sudo apt-get install protobuf-compiler python-pil python-lxml
sudo pip install jupyter
sudo pip install matplotlib

Alternatively, users can install dependencies using pip:

sudo pip install pillow
sudo pip install lxml
sudo pip install jupyter
sudo pip install matplotlib

Protobuf Compilation

The Tensorflow Object Detection API uses Protobufs to configure model and training parameters. Before the framework can be used, the Protobuf libraries must be compiled. This should be done by running the following command from the tensorflow/models directory:

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

Add Libraries to PYTHONPATH

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

# From tensorflow/models/
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.

Testing the Installation

You can test that you have correctly installed the Tensorflow Object Detection
API by running the following command:

python object_detection/builders/model_builder_test.py

Custom Images

And to make sure the test images i used or for you to use custom images go to object_detection directory and test_images subdirectory and rename the images and change in program at " In[8] " at TEST_IMAGE_PATHS in range according to image number

Enjoy!!

Disclaimer

This program is owned with tensorflow. I just created some simple images file to study more about its workflow.!!