README.md

AWS DeepRacer Video Visualizations

Repository containing tools to visualize AWS DeepRacer (training) runs. Currently only a visualization based on GradCam is supported.

Setup

Requirements

• Python 3
• Poetry

Installation

First prepare the Python enviroment using poetry install. Available tools can be found in the tools folder. Before running a tool make sure the virtual environment is activated using poetry shell.

Downloading your model

You can obtain your model graph in the form of a .pb file either from S3 or from the DeepRacer console.

• S3 -> Go to the S3 folder in which the training run is stored. Here you can download the model files per checkpoint.
• Console -> Select your training run and choose Download model. Inside the obtained .tar.gz you can find your model.pb file.

Visualization tools

Kinesis Downloader

Can be used to view and store the live feed of a training job. This is the same feed that is shown in the AWS DeepRacer console.

python download_kinesis.py <Kinesis Video Stream Name> -o <output_file.mp4>

GradCam

Overlays a Gradient-weighted Class Activation Mapping (Grad-CAM, Selvaraju et al.) over an input video for a given action. It takes as input the action number of the action in model_metadata.json or the DeepRacer console for which it then computes the activation map using the model stored in model.pb.

python gradcam.py <input_file.mp4> -m <model.pb file path> -a <action index> -o <output_file.mp4>