To help you decide which image recognition API is right for you, here’s a short synopsis of the features of the APIs we’ve covered in this article. Each one has its own unique capabilities as well, though. A number of them perform many of the same basic image recognition functions. Image Recognition APIs: Final ThoughtsĪs you can see, there are a lot of different image recognition APIs to choose from.
If you’re going to use more than their free service, you can request a quote via the pricing page.įilestack Processing API is 96% percent sure this is a cactus, and we have to agree. Rekognition users can analyze up to 1,000 minutes of video 5,000 images and store up to 1,000 faces each month, for the first year.Īmazon Rekognition’s pricing also varies by region.
It does offer a free tier, which makes it noteworthy. Rekognition has a number of payment levels.
The Rekognition API analyzes images for text, assessing everything from license plate numbers to street names to product names. The Detect Text In Image feature is also worthy of mention and likely to be more useful for static image processing. Although largely useful for video processing, it’s worth having in your API toolkit. The Capture Movement feature tracks an object’s movement through a frame. The Capture Movement feature is one of the first standout features of Recogniktion. The Celebrity Recognition feature also makes it useful for apps or websites which display pop culture content. It has some other features which make it useful for video processing, however. It also handles the common image recognition tasks like object recognition and explicit content detection. Amazon RekognitionĪmazon’s Rekognition API is another nearly plug-and-play API. Google Cloud Vision API correctly identifies a cassette tape, listing most probable web entities. Prepare to pay if you’re going to be using it extensively. The only real downside to Google’s CloudVision API is that it’s a bit expensive. This alone makes it worthy of investigation. You can use it to generate documentation straight from graphics and hand-written notes. The API can detect printed and handwritten text from an image, PDF, or TIFF file. The CloudVision API’s most exciting feature is its OCR recognition. It can also be used to identify the predominant color from an image. It can return image descriptions, entity identification, and matching images.
It also can access image information in a variety of ways. That makes it ideal for detecting landmarks and identifying objects in images, which are some of the most common uses for the CloudVision API. The CloudVision API is also able to take advantage of Google’s extensive data and machine-learning libraries. It’s pre-configured to tackle the most common image recognition tasks, like object recognition or detecting explicit content. Google’s CloudVision API is about as close to a plug-and-play image recognition API as you can get. They’re still worth a look if you’re developing a different kind of computer vision tool. Some of the image processing APIs can be used for other computer vision applications. GrubHub developers express a need for image recognition APIs for everything from detecting explicit content to finding similar images.įor the scope of this article, we’ll be focusing on image processing APIs as there are a lot out there.
The simple task of posting images of food to an app is surprisingly fraught. Certain tasks, like detecting similar images or landmark identification, are even next to impossible without advanced AI tools.įor example, consider GrubHub’s use of image recognition APIs for automating images being added to their platform.
Working with a large volume of images ceases to be productive, or even possible, without some sort of image recognition in place. Computer vision can cover everything from facial recognition to semantic segmentation, which differentiates between objects in an image. Image recognition APIs are part of a larger ecosystem of computer vision. These are just a few of the nearly-infinite applications of image processing APIs, which fall under the umbrella term computer vision.īelow we delve into some of the best image recognition APIs out there, covering a wide range of different applications and features. These image processing algorithms could be used for everything from narrating images for the visually impaired to avoiding car accidents to automated image tagging. In 2016, Mark Zuckerberg laid out details at Facebook’s annual developer’s conference about their quest to launch AI that is better at recognizing images than people are.