With all the discourse on OpenAI’s ChatGPT and Natural language processing (NLP), I’d like to steer the conversation toward images/video and object recognition. This is another area in artificial intelligence primed for growth with many use cases. Arguably, it’s not as shocking, bending our society at its core, creating college papers with limited input, but Object Recognition can seem “magical.” AI object recognition may turn art into science, as easy as AI reading your palm to tell your future. AI object recognition will bring consumers more data points from which Augmented Reality (AR) overlays digital images within an analog world of tangible objects.
Microsoft’s AI Builder – Platform Independent
Microsoft’s Power Automate AI [model] Builder has the functionality to get us started on the journey of utilizing images, tagging them with objects we recognize, and then training the AI model to recognize objects in our “production” images. Microsoft provides tools to build AI [image] models (library of images with human, tagged objects) quickly and easily. How you leverage these AI models is the foundation of “future” applications. Some applications are already here, but not mass production. The necessary ingredient: taking away the proprietary building of AI models, such as in social media applications.
In many social media applications, users can tag faces in their images for various reasons, mostly who to share their content/images with. In most cases, images can also be tagged with a specific location. Each AI image/object model is proprietary and not shared between social media applications. If there was a standards body, an AI model could be created/maintained outside of the social media applications. Portable AI object recognition models with a wide array of applications that support it’s use, such as social media applications. Later on, we’ll discuss Microsoft’s AI Model builder, externalized from any one application, and because it’s Microsoft, it’s intuitive. đ
An industry standards body could collaborate and define what AI models look like their features, and most importantly, the portability formats. Then the industry, such as social media apps, can elect to adopt features that are and are not supported by their applications.
Use Cases for Detecting Objects in Images
Why doesn’t everyone have an AI model containing tagged objects within images and videos of the user’s design? Why indeed.
1 – Brands / Product Placement from Content Creators
Just about everyone today is a content creator, producing images and videos for their own personal and business social media feeds, Twitter, Instagram, Snap, Meta, YouTube, and TikTok, to name a few. AI models should be portable enough to integrate with social media applications where tags could be used to identify branded apparel, jewelry, appliances, etc. Tags could also contain metadata, allowing content consumers to follow tagged objects to a specified URL. Clicks and the promotion of products and services.
2 – Object Recognition for Face Detection
Has it all been done? Facebook/Meta, OneDrive, iCloud, and other services have already tried or are implementing some form of object detection in the photos you post. Each of these existing services implements object detection at some level:
- Identify the faces in your photos, but need you to tag those faces and some “metadata” will be associated with these photos
- Dynamically grouping/tagging all “Portrait” pictures of a specific individual or events from a specific day and location, like a family vacation.
- Some image types, JPEGs, PNG, GIF, etc., allow you to add metadata to the files on your own, e.g. so you can search for pictures on the OS level of implementation.
3 – Operational Assistance through object recognition using AR
- Constructing “complex” components in an assembly line where Augmented Reality (AR) can overlay the next step in assembly with the existing object to help transition the object to the next step in assembly.
- Assistance putting together IKEA furniture, like the assembly line use case, but for home use.
- Gaming, everything from Mario Kart Live to Light Saber duels against the infamous Darth Vader.
4 – Palm Reading and other Visual Analytics
- Predictive weather patterns
5 – Visual Search through Search Engines and Proprietary Applications with Specific Knowledge Base Alignment
- CoinSnap iPhone App scans both sides of the coin and then goes on to identify the coin, building a user’s collection.
- Microsoft Bing’s Visual Search and Integration with MSFT Edge
- Medical Applications, Leveraging AI, e.g., Image Models – Radiology
Radiology – Reading the Tea Leaves
Radiology builds a model of possible issues throughout the body. Creating images with specific types of fractures can empower the autodetection of any issues with the use of AI. If it was a non-proprietary model, radiologists worldwide could contribute to that AI model. The displacement of radiology jobs may inhibit the open non-proprietary nature of the use case, and the AI model may need to be built independently of open input from all radiologists.
Microsoft’s AI Builder – Detect Objects in Images
Microsoft’s AI model builder can help the user build models in minutes. Object Detection, Custom Model, Detect custom objects in images is the “template” you want to use to build a model to detect objects, e.g. people, cars, anything, rather quickly, and can enable users to add images (i.e. train model) to become a better model over time.
Many other AI Model types exist, such as Text Recognition within images. I suggest exploring the Azure AI Models list to fit your needs.
Current, Available Data Sources for Image Input
- Current Device
- SharePoint
- Azure BLOB
Wish List for Data Sources w/Trigger Notifications
When a new image is uploaded into one of these data sources, a “trigger” can be activated to process the image with the AI Model and apply tags to the images.
- ADT – video cam
- DropBox
- Google Drive
- Kodak (yeah, still around)
- Meta/Facebook
- OneDrive
- Ring -video cam
- Shutterfly
Get Started: Power Automate, Premium Account
Login to Power Automate with your premium account, and select “AI Builder” menu, then the “Models” menu item. The top left part of the screen, select “New AI Model,” From the list of model types, select “Custom Model, Object Detection”Detect Custom Objects in Images.”
It’s a “Premium” feature of Power Automate, so you must have the Premium license. Select “Get Started”,. The first step is to “Select your model’s domain”, there are three choices, so I selected “Common Objects” to give me the broadest opportunity. Then select “Next”.
Next, you need to select all of the objects you want to identify in your images. For demonstration purposes, I added my family’s first names as my objects to train my model to identify in images.
Next, you need to “Add example images for your objects.” Microsoft’s guidance is “You need to add at least 15 images for each object you want to detect.” Current data sources include:
I added the minimum recommended images, 15 per object, two objects, 30 images of my family, and random pics over the last year.
Once uploaded, you need to go through each image, draw a box around the image’s objects you want to tag, and then select the object tag.
