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Kangas CLI
If you are running from inside a notebook, or even in a Python environment, you can start the Kangas server by simply calling:
dg.show()
However, you may also start Kangas from the command-line:
kangas server
kangas server filename.datagrid
Examples:
kangas server https://github.com/dsblank/examples/raw/main/mnist-60000-after-5-epochs.datagrid.zip
kangas server https://github.com/caleb-kaiser/kangas_examples/raw/master/coco-500.datagrid
kangas server https://github.com/WillKoehrsen/Hands-On-Machine-Learning/raw/master/handson-ml-master/datasets/housing/housing.csv
See Development for full description of server flags.
Kangas can import from, and export to specific targets. Currently Kangas supports:
- huggingface
- comet
Additional integrations are welcome!
Import can import datasets (including images and annotations).
kangas import [-h] [--comet] [--huggingface] [--debug] [--options KEY=VALUE [KEY=VALUE ...]] PATH NAME
Positional arguments:
PATH The source-specific path: workspace/project
NAME The name of the DataGrid to create
Optional arguments:
-h, --help show this help message and exit
--comet Use comet as the source
--huggingface Use huggingface as the source
--debug Show debugging information
--options KEY=VALUE [KEY=VALUE ...]
Pass the following KEY=VALUE pairs;
for --huggingface: --options split=train streaming=True seed=42
samples=100 private=True push=False
labels=objects:category bbox=objects:bbox:xyxy
ids=objects:bbox_id
Examples:
Import a dataset from huggingface, and map the annotations from the "objects" field (real example):
kangas import --huggingface detection-datasets/fashionpedia_4_categories fashionpedia.datagrid \
--options split=val samples=10 labels=objects:category bbox=objects:bbox:xyxy ids=objects:bbox_id
Format options for bbox are: xyxy
and xywh
.
Import a dataset from Comet. This will construct a DataGrid with a column name "Image". Includes annotations (real example):
kangas import --comet dsblank/coco-500 coco-500.datagrid
Export can send datasets (including images and annotations).
kangas export [-h] [--comet] [--debug] [--huggingface] [--options KEY=VALUE [KEY=VALUE ...]] [PATH] NAME
Positional arguments:
PATH The target-specific path: workspace/project/exp, workspace/project, project, or nothing
NAME The name of the DataGrid to upload to host
Optional arguments:
-h, --help show this help message and exit
--comet Use comet as the target
--debug Show debugging information
--huggingface Use huggingface as the target
--options KEY=VALUE [KEY=VALUE ...]
Pass the following KEY=VALUE pairs; for --comet: --options output_dir=DIR; for --huggingface --options limit=N
Examples:
For exporting to huggingface:
kangas export --huggingface my-org/my-new-dataset samples.datagrid --options limit=1000
For exporting to Comet:
kangas export --comet my-workspace/my-project samples.datagrid --output_dir=/tmp
To upgrade annotations from Kangas 1 to Kangas 2, use:
kangas upgrade filename.datagrid
# or:
kangas upgrade *.datagrid
Kangas DataGrid is completely open source; sponsored by Comet ML
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Home
- User Guides
- Installation - installing kangas
- Reading data - importing data
- Constructing DataGrids - building from scratch
- Exploring data - exploration and analysis
- Examples - scripts and notebooks
- Kangas Command-Line Interface
- Kangas Python API
- Integrations - with Hugging Face and Comet
- User Interface
- FAQ - Frequently Asked Questions
- Under the Hood
- Security - issues related to security
- Development - setting up a development environment
- Roadmap - plans and known issues
- User Guides