Image analysis with Object Detection API to try in 1 hour

version: python 3.7.7 OS: macOS Catalina 10.15.3 tensorflow: 2.2.0-rc1

Environment

Use python3 series.

For the python version, use pyenv etc. and install the latest version. (See other articles for pyenv.)

Install and upgrade pip.

sudo easy_install pip

sudo easy_install --upgrade six

sudo pip install --upgrade pip

Install the required libraries.

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

Install TensorFlow.

pip install tensorflow

//version confirmation
python -c 'import tensorflow as tf; print(tf.__version__)'
2.2.0-rc1

Install protobuf.

brew install protobuf

Clone the model of TensorFlow. (Create a tensorflow directory.)

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

Execution of detection api

Perform on Jupyter notebook.

cd ~/tensorflow/models/research/object_detection/
Jupyter notebook

スクリーンショット 2020-03-20 20.47.13.png

The directory will be displayed on your browser. Click ʻobject_detection_tutorial.ipynb` to open the notebook.

Select Run All from the notebook Cell.

スクリーンショット 2020-03-20 20.48.02.png

Elements such as people are detected.

ダウンロード (2).png

PATH_TO_TEST_IMAGES_DIR = pathlib.Path('models/research/object_detection/test_images')

The image to be analyzed is saved in the above directory. Please change the file and analyze your favorite image.

ダウンロード (1).png

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