Vize AI REST API v1 - Source Code

Artificial Intelligence Algorithms, Customization, Images, Recognition

The Vize API recognizes images with artificial intelligence. It classifies images, assists with image upload, and trains new models for identification. The Vize AI API allows applications to recognize customized objects in images. Use the API to create, manage, and deploy custom recognition models. The API can be useful for Real Estate, E-Commerce, IoT, and other industry applications with specific image recognition needs. Developers can test a sample image recognition in Python, PHP, Node.js, Java, Objective-C, .NET, and Ruby.

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Sample Source Code (15)

The following is a list of sample source code snippets that matched your search term. Source code snippets are chunks of source code that were found out on the Web that you can cut and paste into your own source code. Whereas most of the sample source code we've curated for our directory is for consuming APIs, we occasionally find something interesting on the API provider side of things. If you know of some sample source code that would be of interest to the ProgrammableWeb community, we'd like to know about it. Be sure to check our guidelines for making contributions to ProgrammableWeb.

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	Title	Description
	Ximilar Smart Image Recognition Curl Sample Code	The Ximilar Smart Image Recognition Curl Sample Code demonstrates how to integrate image recognition to identify and classify images. Additional services include generic tagging, photo and product similarity, and dominant colors.
	Ximilar Smart Photo and Product Similarity Curl Sample Code	The Ximilar Smart Photo and Product Similarity Curl Sample Code demonstrate how to perform a search to find the similarity between products.
	Ximilar Smart Dominant Colors Curl Sample Code	The Ximilar Smart Dominant Colors Curl Sample Code demonstrates how to extract the dominant colors from an image. It aims to be useful for generic and product photos.
	Ximilar Python Sample Code	The Ximilar Python Sample Code demonstrates how to access the API to implement image recognition. Tests available to make calls for displaying tasks, labels, and images.
	Vize Start Training Python Sample Code	The Vize Start Training Python Sample Code demonstrates how to start training the artificial intelligence application with the URL https://api.vize.ai/v1/training/start/, the authorization API token, and the task ID data. Successful responses will show model training, depending on the number of images in training dataset.
	Vize Training Image Python Sample Code	The Vize Training Image Python Sample Code demonstrates how to train images to be recognized by machine learning. To receive a response, developers first access the URL https://api.vize.ai/v1/training-image/, authorize via token, and open the path file. Both successful and error responses are possible with if and else statements.
	Vize Label Python Sample Code	The Vize Label Python Sample Code demonstrates how to access label features for image recognition apps, when developers visit the URL https://api.vize.ai/v1/label/ They can authorize via token to use the task ID for receiving responses to their requests.
	Vize Task Python Sample Code	The Vize Task Python Sample Code presents how to access tasks in image recognition applications. Developers can import requests when they access the URL https://api.vize.ai/v1/task/, authorize with a token, and use the appropriate headers as requests.
	Vize Image Recognition Ruby Sample Code	The Vize Image Recognition Ruby Sample Code demonstrates how to recognize images when developers use the address http://unirest.io/ruby open-source library. After authorizing with a token, they can accept text or plain content type in return to the image request.
	Vize Image Recognition .NET Sample Code	The Vize Image Recognition .NET Sample Code demonstrates how to recognize images by using the HTTP http://unirest.io/net open-source library. Developers can accept images in return when they authorize with token and request content type.
	Vize Image Recognition Objective-C Sample Code	The Vize Image Recognition Objective-C Sample Code presents how to recognize images by initially requesting to the HTTP address http://unirest.io/objective-c Developers can authorize with token, set the URL to classify images, and have the images recognized in return with their respective header response.
	Vize Image Recognition Java Sample Code	The Vize Image Recognition Java Sample Code presents how to recognize an image when developers access the HTTP address http://unirest.io/java open-source library They can have data in return when they authorize with token, request content type, and accept text or plain result.
	Vize Image Recognition Node.js Sample Code	The Vize Image Recognition Node.js Sample Code presents how to recognize an image when developers use the HTTP http://unirest.io/nodejs open-source library They will install npm and unirest followed by authorizing with token, request and accept content type and attach image and task.
	Vize Image Recognition PHP Sample Code	The Vize Image Recognition PHP Sample Code presents how to recognize an image by handling the cURL https://api.vize.ai/v1/classify/ Developers can access data in return when they request post fields, return transfer, and HTTP header.
	Vize Image Recognition Python Sample Code	The Vize Image Recognition Python Sample Code demonstrates how to identify an image by accessing the URL https://api.vize.ai/v1/classify/ Developers can authorize with API token, access image file, and find data task ID.

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