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AppEngine Flexible Environment for TensorFlow Photo Analysis

To use this demonstration, the TensorFlow Object Detection API should be used. For more details here.

To use this example you will need these minimum elements of TensorFlow Object Detection API:

Object model, quick option to automatize the deploy:

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

*validate dependency with protoc tool

protoc ./models/research/object_detection/protos/string_int_label_map.proto --python_out=.
cp -R models/research/object_detection/ object_detection/
rm -rf model

You can use the preferred model: faster_rcnn_inception_resnet_v2_atrous_coco_2017_11_08 or as another like faster_rcnn_inception_v2_coco_2017_11_08

Deploy the project

Note: You should have the Google Cloud SDK. More information about App Engine Flexible environment, Python here

Local: python main.py

Production Environment: gcloud app deploy

*(-v version) if you want to deploy it to a specific version.

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