In this tutorial, you will learn how to use Video Object Detection in 5 minutes using Python. Eden AI provides an easy and developer-friendly API that allows you to detect objects in videos.
What is Video Object Detection?
Video Object Detection or Label Detection API uses advanced Computer Vision algorithms to analyze videos and automatically assign labels or tags to various visual elements present in the video, including scenes, activities or concepts. The API extracts meaningful information from the video, which can be exploited for numerous applications such as automatic video categorization, video summary creation, caption generation, and so forth.
Get Started with Video Object Detection API using Python
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.
How to use Video Object Detection API with Python
You are now ready to process your video file into Eden AI Video Object Detection API.
1. Get a Video Object Detection API Key on Eden AI
To perform Video Object Detection in videos, 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.
2. Let’s Detect Objects in your Video File
Now that you have imported packages on Python and got your API key, you will be able to detect objects in videos. With Eden AI, you can choose from a wide range of engines you want for Video Object Detection. You can access the list of Video Object Detection providers available on Eden AI directly on our documentation.
Here is the Python script you need to write on your notebook:
For example, we called two different Video Object Detection engines. Eden AI API will then return in its JSON response results of those providers.
Eden AI Video Object Detection API is an asynchronous API. It means that you will get in response an ID:
Then you will need to perform a GET request to check the status of the API request (success, processing, failed):
You will first get this response:
Once the request is done (status : finished), you will be able to get the result with this print:
Here is an example of a result for Video Object Detection task:
Benefits of using Video Object Detection API with Eden AI
As you can see, using Video Object Detection with Eden AI API is quick and easy.
Save time and cost
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.
Easy to integrate
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.
Customization
With Eden AI you have the possibility to integrate a third-party platform: we can quickly develop connectors. To go further and customize your Video Object Detection request with specific parameters, check out our documentation.
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