icevision-dashboards 0.0.6

Provides dashboard components and dashboards to get insight into data.

IceVisionDashboard

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 .

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
jupyter nbconvert --ClearOutputPreprocessor.enabled=True --inplace examples/*.ipynb
jupyter nbconvert --ClearOutputPreprocessor.enabled=True --inplace test_data_generation/*.ipynb
nbdev_build_lib
git add .