What is the most accurate Image Recognition API out there?

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The most accurate Image Recognition APIs out there are as follows:
1. Cloud Vision API
Google’s Cloud Vision API is about as close to a plug-and-play image recognition API as you can get. It is pre-configured to tackle the most common image recognition tasks, like object recognition or detecting explicit content. The Cloud Vision API is also able to take advantage of Google’s extensive data and machine-learning libraries. That makes it ideal for detecting landmarks and identifying objects in images, which are some of the most common uses for the Cloud Vision API. It also can access image information in a variety of ways. It can return image descriptions, entity identification, and matching images. It can also be used to identify the predominant colour from an image. The Cloud Vision API’s most exciting feature is its OCR recognition. The API can detect printed and handwritten text from an image, PDF, or TIFF file. You can use it to generate documentation straight from graphics and hand-written notes. This alone makes it worthy of investigation.
2. Amazon Rekognition
Amazon’s Rekognition API is another nearly plug-and-play API. It also handles the common image recognition tasks like object recognition and explicit content detection. It has some other features which make it useful for video processing, however. The Celebrity Recognition feature also makes it useful for apps or websites which display pop culture content. The Capture Movement feature is one of the first standout features of Recogniktion. The Capture Movement feature tracks an object’s movement through a frame. Although largely useful for video processing, it is worth having in your API toolkit. The Detect Text in Image feature is also worthy of mention and likely to be more useful for static image processing. The Rekognition API analyses images for text, assessing everything from license plate numbers to street names to product names. Rekognition has several payment levels. It does offer a free tier, which makes it noteworthy. Rekognition users can analyse up to 1,000 minutes of video; 5,000 images; and store up to 1,000 faces each month, for the first year. Amazon Rekognition’s pricing also varies by region. If you are going to use more than their free service, you can request a quote via the pricing page.
3. IBM Watson Visual Recognition
IBM’s Watson Visual Recognition API combines an image recognition API with the power of machine learning. Users can build, train, and test custom machine learning models, either in or outside of Watson Studio. It comes with several pre-trained object detection models. These include the General Model, which provides a classification for thousands of predefined objects. The Explicit Model detects inappropriate content. The Food Model recognizes food objects in images. The Text Model recognizes text, like Amazon Rekognition.
4. Microsoft Image Processing API
Microsoft Azure Cloud offers several tools as part of their Cognitive Services. It is nearly a one-stop-shop for any kind of Computer Vision processing you might need. Microsoft Azure Cloud’s Computer Vision API offers several the same image recognition tools as the other APIs on our list. It also offers some innovative other features that make it worthy of inclusion on our list of best image recognition APIs. Image properties definition can assess the dominant hue of an image, and whether it is black-and-white. Image Content Description and Categorization describe an image as a complete sentence as well as categorizing that content. Microsoft Azure Cloud’s image recognition API is priced according to the region as well as by the number of transactions.
5. Clarifai
Clarifai is another image recognition API that takes advantage of machine learning. Clarifai features 14 pre-built models of computer vision for analysing visual data. It is also simple to use. Simply upload your media and Clarifai returns predictions based on the model you are running. Clarifai has several noteworthy features. Its fashion identification system is one of the most in-depth out there, being able to identify thousands of fashion items and accessories using the Fashion computer model. It also features an extensive food algorithm, being able to analyse over 1,000 food items down to the ingredient level. Clarifai is also capable of most of the basic computer vision functions mentioned on our list. It can detect explicit content, identify celebrities, and recognize faces. Clarifai can also determine the dominant colour of an image.
6. Imagga
Companies using visual recognition and processing APIs often deal in huge volumes of visual media. Imagga API is an automated image tagging and categorization API to help you deal with that quantity of media. Imagga is categorized as a Digital Asset Management API. It features an asset library, allowing for asset categorization and metadata management. Finding assets in the library is simple thanks to a Search/Filter function. It also allows for reporting and analytics. It is comparable to other digital asset management APIs like Box, Airtable, or Canto Digital Asset Management. Imagga’s the new digital asset management API on the block, though, making it more affordable than several the other options out there.
7. Filestack Processing API
If you are processing large amounts of photos, Filestack Processing API is a good tool to have in your toolkit. Filestack Processing API can be used to store files, compress files, and file conversion. It can also automatically integrate with file-sharing platforms like Google Drive, Dropbox, and Facebook. It can also perform many of the other tasks that the other image processing APIs mentioned on our list, like detecting inappropriate content and character recognition. Filestack Processing has a few other distinctive features that are worth noting. It can be used to tag videos and detect copyrighted images. It can also be used to size or resize images, crop, resize, compress, or rotate images.
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