A jump-start guide to using Deep Lake.
$ pip3 install deeplake
dataset_path = 'hub://activeloop/visdrone-det-train'
ds = deeplake.load(dataset_path) # Returns a Deep Lake Dataset but does not download data locally
image = ds.images.numpy() # Fetch the first image and return a numpy array
labels = ds.labels.data() # Fetch the labels in the first image
boxes = ds.boxes.numpy() # Fetch the bounding boxes in the first image
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']
Deep Lake enables users to visualize and interpret large datasets. The tensor layout for a dataset can be inspected using:
You can perform all of the steps above and more with your own datasets! Please check out the links below to learn more:
Congratulations, you've got Deep Lake working on your local machine