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dymaxionlabs

This is the Python package for accessing the Dymaxion Labs Platform.

Features

The Dymaxion Labs Platform allows you:

  • Download and upload satellite and drone images.
  • Train machine learning models for object detection, segmentation, change detection, and more.
  • Work your data using a REST API and Python.

This is a publicly installable package. However, if you want access to our full Platform, you will need to create a Dymaxion Labs account.

Install

Install the latest client package via pip:

pip install dymaxionlabs

Authentication

Sing up at https://app.dymaxionlabs.com/signup if you don't have a user yet, otherwise log in.

When entering the first time, you will be asked to create a new Project. After nameing your project you will enter the main dashboard. Take note of your Project Id.

Now enter the API Key section, create a new API key and copy the generated key.

You need to set both keys as environment variables, like this:

export DYM_API_KEY=...
export DYM_PROJECT_ID=...

You can also do this from Python:

import os

os.environ["DYM_API_KEY"] = "insert-api-key"
os.environ["DYM_PROJECT_ID"] = "insert-project-id"

From now on, you have full access to the Dymaxion Labs API from Python.

Examples

To use your models for predicting, you have to know their UUID.

You can obtain this by visiting the models page: https://app.dymaxionlabs.com/home/models. Click on the Edit button of your model, then on Show UUID menu option. Copy this and pass it as parameter to the Estimator constructor.

You can predict objects in local images. For example, if you have img.jpg:

import time
from dymaxionlabs.models import Estimator

model = Estimator('b4676699-27c8-4193-a24c-cffaf88cce92')

job = model.predict_files(local_files=['./img.jpg'])

# Wait for results
while not job.status():
    print("Waiting for results...")
    time.sleep(60)

# Download results to ./results directory (will be created if not exists)
job.download_results("./results")

or use previously uploaded files (remote)

import time
from dymaxionlabs.models import Estimator, Project

project = Project()
files = project.files()
first_file = files[0]

model = Estimator('b4676699-27c8-4193-a24c-cffaf88cce92')

job = model.predict_files(remote_files=[first_file.name])

# Wait for results
while not job.status():
    print("Waiting for seconds results...")
    time.sleep(60)

# Download results to ./results directory (will be created if not exists)
job.download_results("./results")

Contents

.. toctree::
   :maxdepth: 2

   License <license>
   Authors <authors>
   Changelog <changelog>
   Module Reference <api/modules>


Indices and tables

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