The visual data management platform from Zensors.
Join for free at app.datatap.dev.
The dataTap Python library is the primary interface for using dataTap's rich data management tools. Create datasets, stream annotations, and analyze model performance all with one library.
Full documentation is available at docs.datatap.dev.
- ⚡ Begin training instantly
- 🔥 Works with all major ML frameworks (Pytorch, TensorFlow, etc.)
- 🛰️ Real-time streaming to avoid large dataset downloads
- 🌐 Universal data format for simple data exchange
- 🎨 Combine data from multiples sources into a single dataset easily
- 🧮 Rich ML utilities to compute PR-curves, confusion matrices, and accuracy metrics.
- 💽 Free access to a variety of open datasets.
To begin, select a dataset from the dataTap repository.
Then copy the starter code based on your library preference.
Paste the starter code and start training.
Install the client library.
pip install datatap
Register at app.datatap.dev. Then, go to Settings > Api Keys
to find your personal API key.
export DATATAP_API_KEY="XXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXX"
Start using open datasets instantly.
from datatap import Api
api = Api()
coco = api.get_default_database().get_repository("_/coco")
dataset = coco.get_dataset("latest")
print("COCO: ", dataset)
import itertools
from datatap import Api
api = Api()
dataset = (api
.get_default_database()
.get_repository("_/wider-person")
.get_dataset("latest")
)
training_stream = dataset_version.stream_split("training")
for annotation in itertools.islice(training_stream, 5):
print("Received annotation:", annotation)
Q. How do I resolve a missing API Key?
If you see the error Exception: No API key available. Either provide it or use the [DATATAP_API_KEY] environment variable
, then the dataTap library was not able to find your API key. You can find your API key on app.datatap.dev under settings. You can either set it as an environment variable or as the first argument to the Api
constructor.
Q. Can dataTap be used offline?
Some functionality can be used offline, such as the droplet utilities and metrics. However, repository access and dataset streaming require internet access, even for local databases.
Q. Is dataTap accepting contributions?
dataTap currently uses a separate code review system for managing contributions. The team is looking into switching that system to GitHub to allow public contributions. Until then, we will actively monitor the GitHub issue tracker to help accomodate the community's needs.
Q. How can I get help using dataTap?
You can post a question in the issue tracker. The dataTap team actively monitors the repository, and will try to get back to you as soon as possible.