Imagga Named As One of the IDC 2016 Worldwide Image Analytics Innovators

Imagga is recognized as one of the 3 pioneering players in the worldwide image analytics market. IDC’s 2016 Innovators report acknowledges companies that offer an inventive technology and/or groundbreaking new business model.

Imagga stands out with the possibility to offer custom image recognition training using custom-provided data for training sets, according to the prestigious report. Thanks to the flexible training model, customers are offered unprecedented opportunity to make sense of their image content and use the insights for analytics, understanding customers or better monetization strategies. Depending on the complexity of the training model, it takes form a day to couple of days for the actual training. Customers are given visual tools to evaluate the results and decide if fine-tinning is needed for greater performance.

According to Carrie Solinger, senior research analyst at Cognitive Systems and Content Analytics “Application of natural language processing and machine learning technologies have advanced image analytics’ cost effectiveness and accuracy, exponentially”. Services as Imagga enable business to harness the power of machine learning and do what once was done manually with great expense of manpower, or was impossible due to time restrictions. Real time (or near real time) image analytics opens up totally new horizon for companies to optimize their business decisions with direct effect on productivity and business results.

You can download this report from IDC here.

free image recognition with imagga

Batch Image Processing From Local Folder Using Imagga API

Batch Upload of Photos for Image Recognition

This blog post is part of series on How-Tos for those of you who are not quite experienced and need a bit of help to set up and use properly our powerful image recognition APIs.

In this one we will help you to batch process (using our Tagging or Color extraction API) a whole folder of photos, that reside on your local computer. To make that possible we’ve written a short script in the programming language Python:

Feel free to reuse or modify it. Here’s a short explanation what it does. The script requires the Python package, which you can install using this guide.

It uses requests’ HTTPBasicAuth to initialize a Basic authentication used in Imagga’s API from a given API_KEY and API_SECRET which you have to manually set in the first lines of the script.

There are three main functions in the script - upload_image, tag_image, extract_colors.

    • upload_image(image_path) - uploads your file to our API using the content endpoint, the argument image_path is the path to the file in your local file system. The function returns the content id associated with the image.
  • tag_image(image, content_id=False, verbose=False, language='en') - the function tags a given image using Imagga’s Tagging API. You can provide an image url or a content id (from upload_image) to the ‘image’ argument but you will also have to set content_id=True. By setting the verbose argument to True, the returned tags will also contain their origin (whether it is coming from machine learning recognition or from additional analysis). The last parameter is ‘language’ if you want your output tags to be translated in one of Imagga’s supported 50 (+1) languages. You can find the supported languages from here -
  • extract_colors(image, content_id=False) - using this function you can extract colors from your image using our Color Extraction API. Just like the tag_image function, you can provide an image URL or a content id (by also setting content_id argument to True).

Script usage:

Note: You need to install the Python package requests in order to use the script. You can find installation notes here.

You have to manually set the API_KEY and API_SECRET variables found in the first lines of the script by replacing YOUR_API_KEY and YOUR_API_SECRET with your API key and secret.

Usage (in your terminal or CMD):

python <input_folder> <output_folder> --language=<language> --verbose=<verbose> --merged-output=<merged_output> --include-colors=<include_colors>

The script has two required - <input_folder>, <output_folder> and four optional arguments - <language>, <verbose>, <merged_output>, <include_colors>.

  • <input_folder> - required, the input folder containing the images you would like to tag.
  • <output_folder> - required, the output folder where the tagging JSON response will be saved.
  • <language> - optional, default: en, the output tags will be translated in the given language (a list of supported languages can be found here:
  • <verbose> - optional, default: False, if True the output tags will contain an origin key (whether it is coming from machine learning recognition or from additional analysis)
  • <include_colors> - optional, default: False, if True the output will also contain color extraction results for each image.
  • <merged_output> - optional, default: False, if True the output will be merged in a JSON single file, otherwise - separate JSON files for each image.

Imagga Partners with Aylien

aylien magga partnership

We are super excited to announce our partnership with AYLIEN - a natural language processing platform, that will make possible to add text analytics capabilities to our image recognition and analytics APIs. We believe this partnership will help users of both services better understand their multimedia content and do way more with it.

AYLIEN Text API is a package consisting of eight different Natural Language Processing, Information Retrieval and Machine Learning APIs that help developers extract meaning and insight from text documents. It can be applied in Ad-Targeting, Media Monitoring and Social Listening projects.

Imagga’s Image Recognition API utilizes machine learning, image recognition and deep learning algorithms to identify over 6,000 distinct objects and concepts and return relevant keywords that best describe what’s in the images.

Currently Imagga’s image analysis endpoint is being added to ALYIEN’s Natural Language Processing API, giving developers the ability to analyze text and images in one API.

test image tagging

Having access to two powerful technologies in a single API creates endless opportunities for businesses that need to deal with large volumes of user generated content. Users rarely input or share just text or images, so being able to analyze and understand both at once, gives amazing new opportunity for any business to distribute and monetize content.

Together with AYLIEN we’ve been testing how our technologies can compliment each other for some time and the results were very exciting. Text and images are different but complement well each other in many cases and applications.

You can try the new hybrid image and text analysis service here. There’s nice demo to play with before you are finally sold (you can see the results for some sample images, but also can upload your own)

Demystifying Image SaaS Solutions (Infographic)

In most cases when people hear we do image processing & analysis, they exclaim “Oh, I see, face detection! That’s cool!” Well, that’s not all we can do, definitely not the most sexiest of the currently available image technologies but by far the most popular. This is why we decided to do an overview of various image understanding technologies, what integration options are available, and what business models are currently used in the Image Software-as-a-Service world. What better way to convey such message than with an image

ImageSaaS demystifying infographic

Feel free to spread the word and share the infographic! If you decide to share only the image and not the whole blog post, please link back to it somehow.

For your convenience, here are links to some of the key image SaaS players: Blitline, Chute, Cloudinary, Aviary,, Pixolution, Imagga, IQ Engines, Kooba, Lambda Labs, LTU technologies, Idee Inc.

If you know or you are part of some significant image SaaS provider that we’ve missed – please, comment here and we may include it in the next version of the infographic