Loader for Roboflow datasets.
Roboflow Python Library
This is a helper library to load your Roboflow datasets into your python scripts and Jupyter notebooks.
This package requires python >=3.6 and a (free) Roboflow account.
pip install roboflow
conda install roboflow
roboflow package works in conjunction with your
Account page, click
Roboflow Keys to get your API key.
You can then use the
roboflow python package to manage downloading
your datasets in various formats.
import roboflow roboflow.auth("<<YOUR API KEY>>") info = roboflow.load("chess-sample", 1, "tfrecord") # dataset is now downloaded and unzipped in your current directory # and info contains the paths you need to load it into your favorite # machine learning libraries
By default the folder is named
The file hierarchy is three folders containing the
data you selected in the Roboflow upload flow (and the format you specified
roboflow.load above). There is also a
README.roboflow.txt describing the preprocessing and augmentation steps and, optionally, a
provided by the person who shared the dataset.
It's important to pre-process your images for inference the same way you
pre-processed your training images. For this, get a pre-processor via the
roboflow.infer method which will return a function you can use to pre-process
import roboflow roboflow.auth("<<YOUR API KEY>>") process = roboflow.preprocessor("chess-sample", 1) images = process.fromFile("example.jpg") # returns a numpy array (of 1 image, unless you used tiling)
This package currently provides two main benefits over downloading and loading your datasets manually.
- If you have previously loaded your dataset, it will automatically use the local copy rather than re-downloading.
- You can dynamically choose the export format at runtime rather than export-time.
We plan to include more features in the future to allow you (for example, to let you easily do inference on your trained models).
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
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