Quickstart
A jump-start guide to using Deep Lake.
How to Get Started with Activeloop Deep Lake in Under 5 Minutes
Version control, query, and train models while streaming your deep-learning datasets from a cloud of your choice.
Installing Deep Lake
Deep Lake can be installed through pip. By default, Deep Lake does not install dependencies for audio, video, google-cloud, and other features. Details on all installation options are available here.
$ pip3 install deeplake
Fetching Your First Deep Lake Dataset
Let's load the Visdrone dataset, a rich dataset with many object detections per image. Datasets hosted on Activeloop Platform are typically identified by host organization name followed by the dataset name: activeloop/visdrone-det-train
.
import deeplake
dataset_path = 'hub://activeloop/visdrone-det-train'
ds = deeplake.load(dataset_path) # Returns a Deep Lake Dataset but does not download data locally
Reading Samples From a Deep Lake Dataset
Data is not immediately read into memory because Deep Lake operates lazily. You can fetch data by calling the .numpy()
or .data()
methods:
# Indexing
image = ds.images[0].numpy() # Fetch the first image and return a numpy array
labels = ds.labels[0].data() # Fetch the labels in the first image
boxes = ds.boxes[0].numpy() # Fetch the bounding boxes in the first image
# Slicing
img_list = ds.labels[0:100].numpy(aslist=True) # Fetch 100 labels and store
# them as a list of numpy arrays
Other metadata such as the mapping between numerical labels and their text counterparts can be accessed using:
labels_list = ds.labels.info['class_names']
Visualizing a Deep Lake Dataset
Deep Lake enables users to visualize and interpret large datasets. The tensor layout for a dataset can be inspected using:
ds.summary()
The dataset can be visualized in Activeloop Platform, or using an iframe in a Jupyter notebook:
ds.visualize()
Create your own Datasets
You can perform all of the steps above and more with your own datasets! Please check out the links below to learn more:
Getting StartedCreating DatasetsCongratulations, you've got Deep Lake working on your local machine🤓
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