icevision-dashboards 0.0.4

Provides dashboard components and dashboards to get insight into data.

IceVisionDashboard

IceVisionDashboard is an extension to the IceVision object detection framework. This extension provides different dashboards to investigate datasets, create new datasets and analyse the results of a training.

The libary provides dashboards to inspect datasets, create new datasets, investigate the results of a training and much more.

Examples

from icevision_dashboards.data import BboxRecordDataset
from icevision_dashboards.dashboards import ObjectDetectionDatasetOverview

# load some data from the icedata
data_dir = icedata.fridge.load_data()
class_map = icedata.fridge.class_map()
parser = icedata.fridge.parser(data_dir)
train_records, valid_records = test_parser.parse()

# create a dataset that can be consumed by the dashboards
train_dash_ds = BboxRecordDataset(train_records, class_map)

# create a new dashboard instance and display it with the .show() function
overview_dashboard = ObjectDetectionDatasetOverview(train_dash_ds, width=1500, height=900)
overview_dashboard.show()

The output will look like this:

Contributing

If you want to contribute add the following lines to your pre-commit file to ensure the notebook cell output don't get pushed into the repo.

# ensure the oupt of the notebooks is empty
jupyter nbconvert --ClearOutputPreprocessor.enabled=True --inplace nbs/*.ipynb
git add .