Computer Vision is a field of Artificial Intelligence that enables image recognition, object detection as well as facial detection technologies thanks to task automation using AI and ML tools that mimic human visual system. To make it simple, it imitates the human visual system and translates visual objects into description of the world.
Companies and developers use Eden AI’s unique API to easily integrate AI Vision capabilities in their cloud-based applications, without having to build their own solution.
Eden AI platform include a wide range of Computer Vision APIs providers available for medical imaging, military, industry, transport etc; and provide customization by domain or profession, improving output by limiting the scope of allowable substitutions.
Here are some typical tasks Computer Vision AIs undertake :
There are also very specific tasks in computer vision. Here are some examples :
This technology lets customers extract various information from a resume (type of files allowed: pdf, jpg, jpeg, png) into structured data to automate their process.
Logo detection is an API specifically trained to detect logos that can be used for brand protection or sponsorship monitoring. It enables the detection of logos in different scales, qualities, and colors. Eden AI aggregates Google AIs on its platform, which you can test out with our unique API.
It is a commonly required technology for privacy (mainly used in TV news, witness protection…) that detects faces in images or videos, then blurry them out.
Explicit Content Detection is an AI technology used to detect adult content within a video, such as NSFW (Not Safe For Work) media or violence. Using Explicit Content Detection allows you to spot non-age appropriate content in a given media. Eden AI is aggregating both AWS and Google AIs on its platform, which you can test out with our unique API.
This customized solution allows you to train your own image recognition model with a tag system. This process allows you to choose the algorithm and build the predictive model from scratch. Eventually, it can be used with complex data. If you’re interested in Computer vision & custom model, check out this article to know which AI Custom Model provider to choose.
While comparing APIs, it is crucial to consider different aspects, among others, cost security and privacy. Computer Vision experts at Eden AI tested, compared and used many computer vision APIs of the market. Here are some actors that perform well (in alphabetical order) :
For all the companies who use Computer Vision in their softwares for their customers : cost and performance are real concerns. The CV market is dense and all those providers have their own benefits and weaknesses.
Performances of Computer Vision vary according to the type of data used by each AI engine for their model training : AI engines are usually trained with specific data. This means that some Computer Vision APIs may perform better for images from the medical field while others for images from the automotive field.
Bear in mind that if the user has very specific data, not all provider’s engine will be able to recognize what the user is looking for. If you have customers coming from different fields, you must consider this detail and optimize your choice of provider.
Eden AI offers multiple AI APIs on its platform amongst several technologies : OCR (Optical Character Recognition), Face Detection, Explicit Content Detection, Object Detection, Image Segmentation, Video Recognition, Custom Vision, and many more to come.
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We want our users to have access to multiple image recognition engines and manage them all in one place so they can reach high performance, optimize cost and cover all their needs. There are many reasons for using multiple computer vision APIs :
You need to set up an AI API that is requested if and only if the main AI API does not perform well (or is down). You can use confidence score returned or other methods to check provider accuracy.
After testing phase, you will be able to build a mapping of AI vendors performance that depends on criterias that you chosed. Each data that you need to process will be then send to the best API.
This method allows you to choose the cheapest provider that performs well for your data. Let's imagine that you choose Google Cloud API for customer "A" because they all perform well and this is the cheapest. You will then choose Microsoft Azure for customer "B", more expensive API but Google performances are not satisfying for customer "B". (this is a random example)
This approach is required if you look for extremely high accuracy. The combination leads to higher costs but allows your AI service to be safe and accurate because AI APIs will validate and invalidate each others for each data.
Eden AI is the future of AI usage in companies. Our platform not only allows you to call multiple AI APIs, but also gives you :
You can read Eden AI documentation here.
The Eden AI team can help you with your machine translation integration project. This can be done by :
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