This Python sample is available only with our Professional plan.
Training of EB Classification Model
This Python script allows you to train a supervised classification model with recorded event streams.
checkpoints (models at different training stages)
videos on test dataset
A training demo is shown below:
Setup & requirements
To run the script, you need:
path to the output folder
path to the training dataset:
a folder containing 3 sub folders, named
each subfolder should contain one or multiple
h5files and their corresponding
<h5 filename>_bbox.npylabels. The label is by default set to EventBbox format, except that only the column “ts” and “class_id” are actually used, the rest can be set to a constant dummy value.
a dictionary file named
label_map_dictionary.json, which contains all the classification categories.
How to start
To run the script:
python3 train_classification.py /path/to/logging /path/to/dataset
python train_classification.py /path/to/logging /path/to/dataset
To find the full list of options, run:
python3 train_classification.py -h
python train_classification.py -h