In this tutorial, you will learn how to use Landmark Detection API in 5 minutes using Python. Eden AI provides an easy and developer-friendly API that allows you to detect landmarks in images.
Landmark Detection API is a service that uses Computer Vision and Machine Learning algorithms to analyze the visual content of an image and detect known landmarks such as buildings, monuments, and natural features.
This API can be integrated into various applications such as image search, image tagging, augmented reality, and image recognition systems.
The first step is to install Python's requests package, that will allow you to call Eden AI API.
Next, you'll need to install Python's JSON package in order to read and print the result of the API request.
To perform Landmark Detection, you'll need to create an account on Eden AI for free. Then, you will be able to get your API key directly from the homepage with free credits offered by Eden AI.
Now that you have imported packages on Python and got your API key, you will be able to detect landmarks in images. With Eden AI, you can choose from a wide range of engines you want for Landmark Detection. You can access the list of Landmark Detection providers available on Eden AI directly on our documentation.
Here is the Python script you need to write in your notebook:
For example, we called two different Landmark Detection engines. Eden AI API will then return in its JSON response results of those providers.
Once the request is done, you will be able to get the result with this print:
Here is an example of a Landmark Detection API response:
As you can see, using Landmark Detection with Eden AI API is quick and easy.
We offer a unified API for all providers: simple and standard to use, with a quick switch between providers and an access to the specific features of each provider.
The JSON output format is the same for all suppliers thanks to Eden AI's standardisation work. The response elements are also standardised thanks to Eden AI's powerful matching algorithms.
With Eden AI you have the possibility to integrate a third-party platform: we can quickly develop connectors. To go further and customize your Landmark Detection request with specific parameters, check out our documentation.