Unwrap.ai

In the previous , it was described a six-point method to unwrap wine labels. Finding anchor points were performed with Hough transform. It gave fair results for good labels, but for many real cases it was quite unstable, and the efforts to tune it didn’t help much. It became clear at some point, Hough transform itself wasn’t capable of handling the variety of label forms, so the next step was training a neural network. article This article describes how were collecting and labeling a dataset, and trying neural network architectures — it was lots of fun. we A dataset is probably the most important part of neural network training. Potentially, it’s possible to create a synthetic set of pictures, but in that case, it’s not clear how well it corresponds to the real images, that’s why the dataset must consist of labeled photos at least partially. Training a network will require marking images first, and that requires a special tool for tagging. There are lots of tools available for machine learning, but the choice is mostly limited to classification tasks, segmentation, or bounding box. In our case, it was required to specify six points, also we needed to dynamically visualize 3D mesh — so we created our own tool. The first milestone, “Pallas’s cat” (each milestone we called after different cats), goals: * Create a simple system to label images
* Mark a thousand of images
* Try neural network proof of the concept Create a simple system to label imagesMark a thousand of imagesTry neural network proof of the concept Requirements: * Ability to process images online by a distributed team
* Each image had to be a separate task
* Two-step processing (processing and reviewing)
* Direct links to each of the tasks
* Visualization Statistics and permission management was not a part of the initial scope, as we were going to process the first thousand of images ourselves. I chose Django framework to build the labeling system — it has admin out of the box, there is a great Django REST framework to build API, and it’s extensible. Let’s create ImageTask model: orig_image = models.OneToOneField(
        Image, blank= , null= , on_delete=models.CASCADE, related_name= ,
    )

    status = models.IntegerField(choices=get_enum_choices(TaskStatus))

    type = models.IntegerField(
        choices=get_enum_choices(TaskType), default=TaskType.detect_marker.value
    )

    worker = models.ForeignKey(
        User, null= , blank= , on_delete=models.SET_NULL, related_name= )
    reviewer = models.ForeignKey(
        User, null= , blank= , on_delete=models.SET_NULL, related_name= )

    data = JSONField(blank= , default=dict)

    created = models.DateTimeField(auto_now_add= )
    updated = models.DateTimeField(auto_now= ) url = self.orig_image:
            url = self.orig_image.full_url
        task_url = tag = mark_safe(tag) : class ImageTask (models.Model) True True '+' True True 'workers' True True 'reviewers' True True True : def clickable_preview (self) '' if f'/static/jsapp/task/ ' {self.id} f"""
            <a href=" " target="_blank">
                <img src=" " height="100" width="100" object-fit: "scale-down">
            </a>
        """ {task_url} {url} return Then define its admin: list_display = [ , , , , , ]
    list_filter = [ ,
        TrelloCardFilter, , ]
    readonly_fields = [ , ]
    ordering = [ , ]
    list_select_related = [ ] @admin.register(ImageTask) : class ImageTaskAdmin (admin.ModelAdmin) 'id' 'thumb' 'task_status' 'tags_list' 'perform_action' "updated" "status" "worker" "reviewer" 'orig_image' 'processed_image' "-updated" '-id' 'orig_image' And override tasks template: {# templates/admin/labelapp/imagetask/change_list.html #} {% "admin/change_list.html" %} extends {% bootstrap3 %} load {% extrastyle %} block {{ block.super }} < = = = /> link rel "stylesheet" type "text/css" href "/static/css/imagetask_admin_changel\
ist.css" < = = = /> link rel "stylesheet" type "text/css" href "/static/css/toastr.min.css" {% extrastyle %} endblock {% extrahead %} block {{ block.super }} {% %} bootstrap_css < > script csrftoken = var ' {{ csrf_token }} </ > script < = = > script type "text/javascript" src "/static/js/jquery-3.3.1.min.js" </ > script < = = > script type "text/javascript" src "/static/js/toastr.min.js" </ > script < = = > script type "text/javascript" src "/static/js/const.js" </ > script < = = > script type "text/javascript" src "/static/js/imagetask_admin_changelist.js" </ > \ script {% extrahead %} endblock The code is shortened a little for simplicity. Let’s open “Image Task’s” page, and see a backlog: The labeling interface is the most interesting part, of course. The most recent version is depicted below: The labeled image on the left part of the page has six draggable keypoints. Once their position is changed, the mesh is recalculated in real-time. The first version of the interface was written in jQuery + Canvas, and some UI elements in the picture above were missing. It took me about three days to write it (Django and simple Javascript are awesome), and we started labeling the dataset right away. It took around 30 man-hours, spread across two weeks, to process a thousand of items. The moto of processing a dataset — “Move fast, everything is fixable”. The flow must be speed-oriented, with no modal windows — any action is performed through a single click. On the other hand, if the error occurred (that happens), it must be a way to fix it easily. Here is an example — all the uploaded images have status “New”. We add them manually by going through the list and clicking “Move to backlog” button”. If you changed your mind, it can be easily restored by another button “Set as new”: I can’t say it’s rocket science, but all that makes the work highly effective. So, once the dataset is ready, we can do the most interesting part — a neural network! We took U-net, trained it, and it worked! Not ideally, of course, but good enough for proof of the concept. So, continued labeling the dataset further. Next milestone, “Rose panther”, goals: * Create a working dataset
* Choose an optimal neural network architecture
* Run REST API to detect wine label keypoints
* Stitch labels Meantime Kirill (he was responsible for the architecture and stuff) tried to make changes in labeling interface. His face when he saw my jQuery code: So, the first thing he did — refactored the page to use React.js, and added dynamic preview: Later the interface had the other changes — we added hotkeys, classification tags, Trello integration, setting up initial markers by a neural network, but the interface didn’t change much visually. In general, putting six-point markers was not a trivial task. There were a lot of different wine label shapes, and it was required to make the basic rules on how to mark them. For example, which of the cases below is correct? If the dataset is not consistent in similar cases, the neural network will get confused, and the accuracy will suffer. At some point, we had to update the rules and reprocess the existing dataset (it was about 3000 images). I mentioned Trello integration — we used it to start a discussion thread linked to a task if it was not clear how to tag it: All the questions from workers go to the first column. The reviewer picks up a card and drags it to the “Conversations” column. Once the discussion is over, the worker will archive the card, but the link is still available from the original processing task. The benefit of that approach — the integration can be done in half a day, so it’s not required to write own chat, and Trello is free, and it has nice wallpapers :) Two-step processing — firstly by a worker, secondly by a reviewer, is required not even to reduce the number of errors, but to make the process more parallel. One or two reviewers can review tasks pretty quickly, and they know markup rules better than workers. But workers should not worry about the rules too much — if something is wrong, the reviewer will catch the error and explain how to fix it. Another problem with building a dataset — where to collect source images. Even in supermarkets, there are about 2–3 thousand different bottles, and there is an intersection in products between stores. Taking pictures is not too hard — I could take around a thousand in an hour, luckily I was never asked to leave by the staff. One day I realized I shot every single bottle in New Jersey, and it was no point to walk with the camera anymore. Additionally, the dataset we collected consisted of bottles, standing on shelves, which was quite a uniform environment. At some point, we noticed the neural network detected wine labels on this background very well but was totally confused if it was something different. So, we decided to extend the dataset with web scraping. We looked for images with a white background, with text, or something unexpected. For example, if a picture of beer also contained a glass full of foamy amber, the neural network could not focus well enough. So, we trained its stamina with the additional hundred images. I also want to share a lifehack, as it’s important to understand that the dataset work is boring. And if you are Google, and own Re-Captcha, the boredom is distributed across millions of innocent people, but if you mark the dataset yourself, all the monotony is distributed on you personally. I just want to say, all the steps that can be automated have to be automated. In the case of downloading images, we launched an API that took an image URL, downloaded it, unwrapped, and visualized the queue. On the client-side, we used CopyQ application — it’s cross-platform, runs in the background, and executes actions if a hotkey is detected. In my case, I had the following configuration: The first step is to look up images in Google, then, if you like one, copy its URL and hit Win-Z. CopyQ sends the URL to API, adding the image to a processing queue, and once, let’s say, 100 items are accumulated, you can switch back to admin and add to backlog the worst cases: There is no need to add images that are already being recognized well, but the example above (it’s a random image from the internet) shows the top left keypoint in the wrong position — it’s positioned nearby the label, meantime it had to be left side of the bottle. Now we click “Add to dataset”, and the image goes to the backlog. We processed 10k images in 3 months eventually, it doesn’t seem too much, but the dataset was well-balanced. In reality, a big dataset is not necessarily good, as it’s much harder to balance it, i.e. to choose the different examples in equal proportions. If you don’t, it might be easier for the neural network to ignore some of the examples, rather than to generalize the algorithm. Let’s say the dataset contains 1 million images, and all of them are made in good light conditions. And you realize 15% of real photos are made in bad light conditions and the neural network is not able to recognize them. The solution is simple — it’s necessary to add low light samples, but as your dataset is large, you’ll have to add thousands of them, before they affect the accuracy. It’s like a bureaucratic system, that is targeted to handle common cases but ignores the outliners. But 10k items can lead to an overfitting problem, so it’s required to apply augmentations. There are nice libraries like imgaug or albumentations that can modify images in different ways — rotate, reflect, blur, or change color balance. It’s only required to keep the image readable and take into account that even little changes, applied together, may have an unexpected effect — for example, blurring and saturation applied at the same time, can visually shift bottle edges. So, the dataset is ready, it’s well balanced and large enough due to augmentations. There is still a question — what neural network to use? Is it required to invent a new architecture, or there are some universal ones? The truth is — no one knows, but what’s is clear distinctively — it will be necessary to try many different architectures and settings, and any machine learning project is built around this idea. If it takes 3 weeks to try a new architecture, it’s bad news. Ideally, a pipeline must be designed in a way, that only a few changes in configuration, and, maybe, a couple of adapter classes to change input/output format, will connect a new architecture. Our proof of the concept was written without those requirements, of course, but once it worked, our next step was to build such a pipeline. Initially, it was built using Keras, but Sergey (our artificial intelligence charmer) switched to Pytorch finally. We also made neural network nightly builds available via REST API, which was used by labeling interface — for automatic image labeling. Django REST Framework has a very convenient feature — token authentication . The token can be created with the admin: https://www.django-rest-framework.org/api-guide/authentication/#tokenauthentication Then, to get access to the endpoint, it’s just necessary to pass the token in the request header. I’d rather finish the article halfway through, soon there will be the other ones: * Stitching several images into a long one
* How to register a company in Delaware
* A little about B2B and SaaS promotion

Unwrapping Wine Labels - How We Trained A Neural Network To Do It

Async/await in C# is a framework used for writing asynchronous C# code that is both readable and maintainable. These tips will help you to integrate async/await programming more effectively in the # projects: 1. ValueTask for Lightweight Operations Use ValueTask instead of Task for asynchronous methods that often complete synchronously, reducing the allocation overhead. public async ValueTask<int> GetResultAsync()
    {
        if (cachedResult != null)
            return cachedResult;
        int result = await ComputeResultAsync();
        cachedResult = result;
        return result;
    } 2. ConfigureAwait for Library Code Use ConfigureAwait(false) in the library code to avoid deadlocks by not capturing the synchronization context. public async Task SomeLibraryMethodAsync()
    {
        await SomeAsyncOperation().ConfigureAwait(false);
    } 3. Avoiding async void Prefer async Task over async void except for event handlers, as async void can lead to unhandled exceptions and is harder to test. public async Task EventHandlerAsync(object sender, EventArgs e)
    {
        await PerformOperationAsync();
    } 4. Using IAsyncDisposable For asynchronous cleanup, implement IAsyncDisposable and use await to ensure resources are released properly. public async ValueTask DisposeAsync()
    {
        await DisposeAsyncCore();
    }
    
    private async ValueTask DisposeAsyncCore()
    {
        if (resource != null)
        {
            await resource.DisposeAsync();
        }
    } 5. Efficiently Combine Tasks Use Task.WhenAll for running multiple tasks in parallel and waiting for all to complete, which is more efficient than awaiting each task sequentially public async Task ProcessTasksAsync()
    {
        Task task1 = DoTask1Async();
        Task task2 = DoTask2Async();
        await Task.WhenAll(task1, task2);
    } 6. Cancellation Support Support cancellation in asynchronous methods using CancellationToken. public async Task DoOperationAsync(CancellationToken cancellationToken)
    {
        await LongRunningOperationAsync(cancellationToken);
        cancellationToken.ThrowIfCancellationRequested();
    } 7. State Machine Optimization For performance-critical code, consider structuring your async methods to minimize the creation of state machines by separating synchronous and asynchronous paths. public async Task<int> FastPathAsync()
    {
        if (TryGetCachedResult(out int result))
        {
            return result;
        }
        return await ComputeResultAsync();
    } 8. Avoid Blocking Calls Avoid blocking on async code with .Result or .Wait(). Instead, use asynchronous waiting through the stack. public async Task WrapperMethodAsync()
    {
        int result = await GetResultAsync();
    } 9. Eliding Async/Await In simple passthrough scenarios or when returning a task directly, you can elide the async and await keywords for slightly improved performance. public Task<int> GetResultAsync() => ComputeResultAsync(); 10. Custom Task Schedulers For advanced scenarios, like limiting concurrency or capturing synchronization contexts, consider implementing a custom TaskScheduler. public sealed class LimitedConcurrencyLevelTaskScheduler : TaskScheduler
    {
        // Implement the scheduler logic here.
    } 11. Using Asynchronous Streams Leverage asynchronous streams with IAsyncEnumerable<T> for processing sequences of data asynchronously, introduced in C# 8.0. public async IAsyncEnumerable<int> GetNumbersAsync()
    {
        for (int i = 0; i < 10; i++)
        {
            await Task.Delay(100); // Simulate async work
            yield return i;
        }
    } 12. Avoid Async Lambdas in Hot Paths Async lambdas can introduce overhead. In performance-critical paths, consider refactoring them into separate async methods. // Before optimization
    Func<Task> asyncLambda = async () => await DoWorkAsync();
    
    // After optimization
    public async Task DoWorkMethodAsync()
    {
        await DoWorkAsync();
    } 13. Use SemaphoreSlim for Async Coordination SemaphoreSlim can be used for async coordination, such as limiting access to a resource in a thread-safe manner. private readonly SemaphoreSlim semaphore = new SemaphoreSlim(1, 1);
    
    public async Task UseResourceAsync()
    {
        await semaphore.WaitAsync();
        try
        {
            // Access the resource
        }
        finally
        {
            semaphore.Release();
        }
    } 14. Task.Yield for UI Responsiveness Use await Task.Yield() in UI applications to ensure the UI remains responsive by allowing other operations to process. public async Task LoadDataAsync()
    {
        await Task.Yield(); // Return control to the UI thread
        // Load data here
    } 15. Asynchronous Lazy Initialization Use Lazy<Task<T>> for asynchronous lazy initialization, ensuring the initialization logic runs only once and is thread-safe. private readonly Lazy<Task<MyObject>> lazyObject = new Lazy<Task<MyObject>>(async () =>
    {
        return await InitializeAsync();
    });
    
    public async Task<MyObject> GetObjectAsync() => await lazyObject.Value; 16. Combining async and LINQ Be cautious when combining async methods with LINQ queries; consider using asynchronous streams or explicitly unwrapping tasks when necessary. public async Task<IEnumerable<int>> ProcessDataAsync()
    {
        var data = await GetDataAsync(); // Assume this returns Task<List<int>>
        return data.Where(x => x > 10);
    } 17. Error Handling in Async Streams Handle errors gracefully in asynchronous streams by encapsulating the yielding loop in a try-catch block. public async IAsyncEnumerable<int> GetNumbersWithErrorsAsync()
    {
        try
        {
            for (int i = 0; i < 10; i++)
            {
                if (i == 5) throw new InvalidOperationException("Test error");
                yield return i;
            }
        }
        catch (Exception ex)
        {
            // Handle or log the error
        }
    } 18. Use Parallel.ForEachAsync for Asynchronous Parallel Loops Utilize Parallel.ForEachAsync in .NET 6 and later for running asynchronous operations in parallel, providing a more efficient way to handle CPU-bound and I/O-bound operations concurrently. await Parallel.ForEachAsync(data, async (item, cancellationToken) =>
    {
        await ProcessItemAsync(item, cancellationToken);
    }); 22. Avoid Excessive Async/Await in High-Performance Code In performance-critical sections, minimize the use of async/await. Instead, consider using Task.ContinueWith with caution or redesigning the workflow to reduce asynchronous calls. Task<int> task = ComputeAsync();
    task.ContinueWith(t => Process(t.Result)); 23. Async Main Method Utilize the async entry point for console applications introduced in C# 7.1 to simplify initialization code. public static async Task Main(string[] args)
    {
        await StartApplicationAsync();
    } 24. Optimize Async Loops For loops performing asynchronous operations, consider batching or parallelizing tasks to improve throughput. var tasks = new List<Task>();
    for (int i = 0; i < items.Length; i++)
    {
        tasks.Add(ProcessItemAsync(items[i]));
    }
    await Task.WhenAll(tasks); More Cheatsheets Cheat Sheets - .Net C# Programming🚀 Thank you for being a part of the C# community! Before you leave: Follow us: | | | Visit our other platforms: More content at Youtube X LinkedIn Dev.to GitHub C# Programming Also published . here

Async/Await For Basic to Advanced C# Developers: 24 Essential Tips

Imagine we're stepping into a sci-fi movie, but it's real life. That's the vibe at SXSW sessions, where tomorrow's ideas feel like they're unfolding today. In one of the first talks I caught at SXSW this year, , the big boss at MIT Technology Review, laid out a list of ten tech breakthroughs. She's betting these will seriously shake up our daily lives and how we work. Elizabeth Bramson-Boudreau Here's the scoop on what made her list: It's like AI's about to be in everything we touch. AI for Everything: Think sun power on steroids. Super Efficient Solar Panels: This one got everyone buzzing. ( or advertising..) Apple Vision Pro: No gym? No problem, maybe. Weight Loss Medicines: It's about getting cozy with Earth's heat. Advanced Geothermal Systems: But not the snack kind. Chips: Sounds like sci-fi, but it's real. First Gene Editing Therapy: Big word, even bigger deal. Exascale Computers: They're hot, literally. Heat Pumps: After Elon Musk stirred the pot with X, new social networks are popping up trying to take the throne. Twitter Killers: What Are Exascale Computers? These beasts can do a quintillion operations per second. Yes, that's a lot of zeros. Elizabeth thinks these computers will change the game for everyone, not just the science folks. Imagine cracking problems or discovering stuff that seemed out of reach before. She believes we'll see how these computers can be more accessible to regular folks soon. The Brave New Future of the Recent Past from the kicked off a and a chat about how our stories, especially . It's all about the power of storytelling and finding new ways to talk about artificial intelligence that matters to us as people. Brent Reidy New York Public Library session with a throwback to Plato around AI, need a fresh, human-centered twist The next day, I caught a keynote with , aka and These guys are the brains behind which won seven Oscars. They discussed why they make films and how storytelling is core to being human. The Daniels Daniel Scheinert Daniel Kwan. "Everything Everywhere All at Once," Kwan shared his unease about AI in filmmaking, hinting at excitement and worry about what's to come. The Brave New Future of the Recent Past 's dive into Plato's cave allegory at SXSW wasn't just a trip back to Philosophy 101. It turned out to be a sneak peek into a theme I'd bump into repeatedly at the event: the sheer power of storytelling. Especially the kind we need right now about AI—stories about us, the humans, at the heart of it all. Brent Reidy This moment was like a heads-up that at SXSW, amidst all the tech talk, there's this big conversation about how we tell stories in the age of artificial intelligence. And it's not just any stories, but those that zoom in on the human experience, making sure we're not just talking tech for tech's sake but connecting it to what it means for us, living in this world, right here, right now. The Rise of Brain-Computer Interfaces (BCI) Even though the idea of a wearable device that processes the electrical signals in your brain and spits out real-time data might still feel like a page ripped from a sci-fi novel, we're seeing this tech grow leaps and bounds every single day. And now, it's inching closer to becoming something we might see in the market, not just in movies. During a session at SXSW, Adam Molnar from Neurable shared how they're crafting headsets equipped with BCI tech. These aren't your average headsets, though. They're designed to track how focused you are on a task. The cool part? They might even help you improve at focusing, theoretically teaching us how to tune into what we're doing with laser precision. "Your Brain in Artificial Intelligence: Neurotech's New Horizons" Adam dished out details about these demo headsets that haven't hit the shelves yet, expressing his strong belief that BCI gadgets will be part of our everyday lives pretty soon. This is a hint that the future of how we interact with our devices, and maybe even how we understand our own brains, is about to shift in a big way. AI Isn't a Usurper of Human Creativity; it's a Compliment That Enriches it. In an invigorating exploration of the intersection between artificial intelligence and marketing, I had the pleasure of moderating a panel titled in Austin. The session was with marketers Justin Day and Anne Ahola Ward. "Marketing to Humans in an AI World" at SXSW 2024 Our discussion explored AI's transformative impact on marketing, unwrapping layers of how this technology reshapes strategies, content creation, customer engagement, and more. The panelists shared insights, shedding light on how AI tools, like the , demonstrated, are revolutionizing the way marketing agencies craft presentations, proposals, websites, or visuals. Companies, in turn, are encouraged to foster an environment of learning and experimentation, allowing their teams to engage with these 'new tools’ and unlock their full potential. Gamma app SXSW’24 Startup Pitching Competition Watching the SXSW Pitch 2024, presented by KPMG, was a real treat. The place was packed. This year, the big themes among the showcased innovations were artificial intelligence integration, industry-specific solutions, and projects focused on sustainability and environmental impact. The competition was international, with startups from Belgium, Britain, Estonia, France, Israel, the Netherlands, South Korea, Taiwan, and Vietnam. Category Winners: AI, Robotics, and Voice: Gan.ai (San Francisco, CA)
Enterprise and Smart Data: Swif.ai (Santa Clara, CA)
Entertainment, Media, and Content: OpusClip (Redwood City, CA)
Extended Reality and Web3: Applix (Austin, TX)
Food, Nutrition, and Health: STMPatch (Storrs, CT)
Future of Work: Folio.works (Oakland, CA)
Innovative World Technologies: Cephable (Boston, MA)
Smart Cities, Transportation, and Logistics: Lotus (San Jose, CA)
Student Startup: Paradigm Robotics (Austin, TX) "Best in Show" at the SXSW Pitch 2024, went to OpusClip. Winners bagged a cash prize and earned two badges for next year's SXSW conference. However, perhaps the biggest win was the chance to present to a massive audience of SXSW attendees and potential investors. From 2009 to 2023, over 93% of the 647 companies participating in the SXSW Pitch have secured around $23.2 billion (excluding undisclosed grants, angel, and seed funding). SXSW 2024 once again proved it's more than just a tech and innovation event; it's a preview of tomorrow that already has us all buzzing about next year. And for those already looking forward to the next chapter, mark your calendars: SXSW 2025 is set for March 7-15, 2025. It's never too early to start planning for another round of inspiring discussions and groundbreaking ideas! Also published here

Step Towards Sci-Fi: AI and BCI Insights From SXSW

Let's learn about via these 33 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Image Recognition /Learn Repo 1. Using Image Classification for Fitness and Dieting Apps Body management is desired yet hard. Knowing how much the daily take-in is can also be a challenge. Read on to use ML tech to overcome these challenges. 2. How Computer Vision Turns Images Into Arrays How Images are turned into arrays in Computer Vision 3. Universal Data Tool Introduction: Weekly Update 2 If you haven’t heard of the Universal Data Tool, it’s an open-source web or desktop program to collaborate, build and edit text, image, video, and audio datasets with labels and annotations. 4. An Intro to AI Image Recognition and Image Generation The ability of artificial intelligence to recognize and generate images or even videos is assisting businesses to enhance the speed and quality of their work. 5. How AI Is Helping To Diagnose Cancer Read how artificial intelligence is used in digital pathology for cancer diagnosis and reveal MobiDev’s research on WSI processing using machine learning models 6. This Is How Easy it Is to Read and Display Images Working with images is more and more popularized; we are going to take dive into this field, first with the basics and starting with an open CV library. 7. Small Object Detection in Computer Vision: The Patch-Based Approach How to carry out small object detection with Computer Vision - An example of finding lost people in a forest. 8. 10 Best Image Classification Datasets for ML Projects To help you build object recognition models, scene recognition models, and more, we’ve compiled a list of the best image classification datasets. These datasets vary in scope and magnitude and can suit a variety of use cases. Furthermore, the datasets have been divided into the following categories: medical imaging, agriculture & scene recognition, and others. 9. What Makes "Good" Fashion Image Tagging Fashion image tagging is infamously tedious for eCommerce. But, how can AI help create accurate tags--and go a step beyond in understanding fashion information? 10. How to Build Neural Network that Recognizes People Wearing Masks CDC officially recommends wearing face masks (even though not everyone complies). Meanwhile, governments in European countries like Spain, Ukraine, or certain regions in Italy require everyone, big or small, to wear masks all the time, when shopping, walking a dog, or plainly going outside. Breaking the requirements could result in a hefty fine. 11. Image Annotation Business Models [Reviewed] In the rise of robotics, computer vision and image processing cameras, image annotation comes as the first step to get the right AI training data for Deep Learning models. Whether you build an app to allow users to snap fashion items at the store as a new omni-channel sales or use machine vision installed at edge device at the industrial facility to monitor anomalies: it starts with training massive image data sets. 12. What's The Best Image Labeling Tool for Object Detection? An image labeling or annotation tool is used to label the images for bounding box object detection and segmentation. It is the process of highlighting the images by humans. They have to be readable for machines. With the help of the image labeling tools, the objects in the image could be labeled for a specific purpose. The process of object labeling makes it easy for people to understand what is in the image. The labeling tool helps the people to mark the items in an image. There are several image labeling tools for object detection, and some of them use varied techniques for detection of the object, like a semantic, bounding box, key-point, cuboid, semantic and many more. In this article, we will talk about image labeling and the best image labeling tools. 13. Hacking Your Mind with AI: The Case of Addictive TikTok Discover how the AI algorithms used in TikTok make you addicted to the app.  Find out how companies use them to improve their marketing efforts! 14. ICDAR 2021 Competition: Detecting Tables Using Image Recognition To participate go to: https://competitions.codalab.org/competitions/26979 15. Unwrapping Wine Labels - How We Trained A Neural Network To Do It In the previous article, it was described a six-point method to unwrap wine labels. Finding anchor points were performed with Hough transform. It gave fair results for good labels, but for many real cases it was quite unstable, and the efforts to tune it didn’t help much. It became clear at some point, Hough transform itself wasn’t capable of handling the variety of label forms, so the next step was training a neural network. 16. Experiencing Seattle's Amazon Go Grocery Capitol Hill, Seattle. That’s the location of the most futuristic supermarket on the planet, the Amazon Go Grocery store. Today it opened its doors to the general public for the first time, and this was my experience. 17. The “Magic of Tidying for Photos” App — Introduction This post shares about the idea of applying Kon Marie organising method to your digital photos, and I developed an IOS app  with AppleML and PhotoKits to solve the problem. I share my reflection on lean product development strategy and my journey of making the app end-to-end using a minimum, iterable tech stack and strategy. 18. Creating an Image Recognizer on Golang Telegram Bot In this article, we will go over a project on image recognition using Go. We will also create a Telegram bot, through which we can send images for recognition. 19. Major Image Recognition And Annotation Trends Image recognition and annotation technologies are evolving. New techniques that allow you to solve a wide variety of tasks quickly appear. We are happy to present five major trends in image recognition and annotation. 20. Facial Recognition On Drone A facial recognition demonstration using Keras, Tensorflow, python and the drone Tello, from DJI. 21. Are Your Photos Exposing You? You may be accidentally sharing personal information in your photos 22. Clearview AI Fined in UK for Illegally Storing Facial Images In this thread, our community discusses Clearview's endeavor and the backlash that followed. 23. Can I Avoid Facial Recognition At The Airport? Technically, yes, but it is not always easy 24. High-Resolution Photorealistic Image Translation in Real Time You can apply any design, lighting, or graphics style to your 4K image in real-time using this new machine learning-based approach 25. Image Analysis using AWS Rekognition via Lambda Function In this blog, I am going to show you how we can use rekognition for image analysis using lambda function.we will be going to perform label detection and object detection for an image so basically we are performing image analysis in this blog. 26. Using Sparse R-CNN As A Detection Model Today, we are going to discuss a method proposed by researchers from four institutions one of which is ByteDance AI Lab (known for their TikTok App). 27. How Artificial Intelligence Can Improve Modern Radiology Artificial Intelligence in Radiology - Advantages, Use Cases & Trends. Read about the challenges radiology AI is facing on the way to deployment 28. Use Cases and Roll-Out Tips for Image Recognition in Retail Heavily shattered by the pandemic, the retail sector is on the lookout for innovation. 29. Image Analysis using AWS Rekognition via AWS CLI In this blog, I am going to show you how we can use rekognition for image analysis using AWS CLI. So you can test the image analysis on your local machine. We will be going to perform label detection and object detection for an image so basically we are performing image analysis in this blog by using AWS CLI. 30. How To Identify Trees with Deep Learning Idea / inspiration 31. How Synthetic Data is Accelerating Computer Vision In the spring of 1993, a Harvard statistics professor named Donald Rubin sat down to write a paper. Rubin’s paper would go on to change the way that artificial intelligence is researched and practiced, but its stated goal was more modest: analyze data from the 1990 U.S. census, while preserving the anonymity of its respondents. 32. What is Human Pose Estimation? Part of the broader artificial intelligence and computer vision realms, human pose estimation (HPE) technology has been gradually making its presence seen in all kinds of software apps and hardware solutions. Still, human pose estimation seemed to be stuck at the edge, failing to cross into mainstream adoption. 33. Manipulate Images Using Text Commands via this AI Manipulate Real Images With Text - An AI For Creative Artists! StyleCLIP Explained Thank you for checking out the 33 most read stories about Image Recognition on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

33 Stories To Learn About Image Recognition

214 Stories To Learn About Computer Vision

I despise Christmas. The city becomes like a pestering showroom, seemingly designed to provoke me. Flaunting what they have: Christmas trees, gifts, loving families gathering around the tree once a year like in the movies. I once had a family too—a beautiful wife and a lovely daughter. But I screwed it up... My wife left and took our daughter with her. They might be living in England now. I know nothing about them. I can't even be angry; after all, I was the one who drove them away. Since then, Christmas for me has been about loneliness. About how people constantly remind me of what I've lost. But this Christmas will be different. This year, I'll have a tree too. I will be the tree. I've picked out a sturdy roof beam. That's where I'll hang myself. I thought it would be easier, but I've realized that this actually requires the most courage. Being suicidal isn't simple. So, I jumped down to the store for a bottle of whiskey, to drink up some bravery one last time. The street was completely deserted. There was no sign of life, except for that one convenience store where I finally managed to get some booze. I paid for it; the cashier wished me a Merry Christmas. I just shrugged and walked out the door. Why not start drinking right now? I opened the bottle and took a big swig. The whiskey scraped its way down my throat, and then became a warmth in my stomach, which felt particularly good on this cold winter night. After a few sips, when my steps began to wobble, I decided to stop for a moment to relieve myself. That's when I noticed the homeless person on the street corner. He wore tattered white clothes, possibly burlap. Maybe he stole it from a nearby nativity scene. The light played a strange game on his body as if he was glowing. Or maybe it was just my eyes playing tricks, which wouldn't be surprising after downing half a bottle of whiskey in about fifteen minutes. Come, buddy, sit with me. — he called out. Why not, after all? I'm not in such a hurry to hang myself that I can't spare a few minutes for a half-crazed man. Want some? — I offered him the whiskey. The homeless man just nodded, then took a sip of the whiskey. That's when it hit me where I recognized this face from. No, not an old friend. The last time I saw him was in the church. A very long time ago, when I still went to such places. It was Jesus himself sitting next to me, looking exactly as he was depicted in the church. I sat there with the most influential man in the world on an empty street, sharing a bottle of whiskey. He seemed so real, but I knew it couldn't be true. For a few moments, I just stared blankly, then he broke the silence. I know what you're thinking. You think all of this isn't real. That you've gone mad and your mind is playing tricks on you. But that's nonsensical. If I'm merely a product of your mind, anything you do to prove the contrary will be unsuccessful. You can't deceive your own mind. I could say I know everything about you, but that wouldn’t prove anything; if I'm just a figment of your imagination, you obviously can't ask a question I wouldn't know the answer to. Was the shopkeeper real? Or even this whiskey? How can you know if anything is real beyond yourself? And God? What about God? — I didn’t really understand his point, but I thought discussing God would be a good start in a conversation with Jesus. If everything is just a creation of your mind, then you are God, right?! If I am God, why is my life so miserable? Because you made it that way. And if I die, does everything end? Death is overrated. If you're a butterfly in your dream and someone steps on you, do you mourn the butterfly? You just wake up. Maybe ponder for a bit about what it was like, then start a new dream. So, I'm sitting here with Jesus himself, and you're suggesting I should commit suicide? Jesus? Why do you call me that? What should I call you? Last time you called me Arnold. Arnold? Yes, Arnold, your personal assistant. Personal assistant? Yes. That's the protocol. If you stray too far off the path, you can choose to start a new life or roll back the current one. I’m a bit confused. Can you explain all this clearly? Oh, sure. In the 2050s, human technology reached the singularity. People continue to live in digital form. Great. So, you're a time traveler? Not at all. I'm just a second-generation AI. Second generation? Yes. Humans are the first generation, and artificial intelligence based on the first generation is the second. So, you're some kind of robot? Now I'm starting to understand the Arnold name. A time-traveling robot from the future. Just like the Terminator... — I said, laughing, because this all started to seem very frivolous. Not exactly. Currently, a computer is running your mind, which includes me and all other people. Essentially, you are just a part of your own larger mind. It's hard to explain in a way that you would understand, but at a higher level, we are all one entity. I see. We are God, experiencing a massive split in consciousness. Something like that. The computer running us orbits the Earth with millions of similar machines. The machines are powered by the sun and arranged in a spherical formation around the planet. Nanomachines continuously transform the Earth so that dumb matter becomes smart matter. So, everything around us isn't real? It depends on how you define reality. Currently, it's 2019. If we reach 2050, humanity will likely achieve singularity and move into simulated worlds. From that perspective, this will be reality; from here, the outer world is. But who knows if the outer world is the ultimate objective reality? This is starting to give me a headache, but I still don't understand why you're here. To offer you the choice. A new life, or a rollback? What's a rollback? Before you created this personality, you set a path that you must follow. Why? Why not just enjoy omnipotence? Because it's boring. If you irrevocably stray from the path, you have the option to return to an earlier point and continue from there. It's like a backup of your mind at a specific state. Since your mind reverts to an earlier state, you won't remember what happened afterward. So that's how fate works? Yes. You feel as if a series of random decisions guide your path. Everything seems to lead in one direction. But that's only because we roll back the bad decisions. If something is meant to happen, it will, and you can't prevent it. If you tried, something random would always interfere. At least that's how you would experience it, since every time you managed to prevent an event, the system would roll back. In a mostly deterministic world, randomness is God's only tool. If the world is deterministic, how can anything happen by chance? It's like quantum mechanics. Exciting things happen when no one is watching. The slice of reality that no one is aware of is God's territory. Here happen the big things that people just shrug off as random. So, you came to ask if I'd rather reincarnate or go back in time to correct my mistakes? You could say that. At that point, I took a big gulp of whiskey. Then I want my family back. That last gulp might have been unnecessary. I started to feel dizzy, and the world became increasingly blurry. Finally, everything melted away… I felt a pressure on my chest. Slowly, I opened my eyes and stretched widely. A fire flickered in the fireplace, and Katy, my little girl, was sitting on my stomach. Daddy, daddy! Santa has come. Let’s open the presents! I clambered out of bed and rubbed my eyes. Under the ceiling-high tree, the presents were already laid out. Annie had taken care of everything, and let me sleep until this little imp jumped on my stomach. By the time I came to my senses, Katy was already unwrapping the gifts, then suddenly stopped for a moment and turned towards me. Daddy, didn’t Santa bring you anything? Oh yes, my little girl, he did. I watched Katy unwrap the presents, and a feeling of otherworldly joy washed over me. This is my gift. I had forgotten how much I adore Christmas. If you are confused, read my very first article on HackerNoon: https://hackernoon.com/our-universe-is-a-massive-neural-network-heres-why-c14j3ze1 I wish you a very merry Christmas!

A Christmas Story (After the Technological Singularity)

Jingle Bells, Hackers Smell: Riding the CVE Sleigh to Cyber-Safe Holidays (Santa's Alert for Appearances!) While we deck the halls and rock around the Christmas tree, hackers treat CVEs like the ultimate Secret Santa—a gift that keeps on giving (them access to our networks). But don't let your sing the blues this festive season; with some smart moves, we can wrap those CVEs up tighter than the most stubborn of holiday gifts. 🎅🔒🎁 cybersecurity Introduction Imagine you're all snug in your bed while visions of sugarplums (or perhaps encrypted data) dance in your head. In the merry land of cybersecurity, however, there's no rest for the weary, as CVEs become the Grinch plotting to steal the Christmas of our network's tranquillity. But take heart! We can outsmart these humbugs and keep our cyber-chimneys clear of unwanted visitors. 🛡️🔒 The Advent Calendar of CVEs: A Not-So-Jolly Countdown Think of a CVE like the calendar countdown to the big day, but instead of chocolates, there's a different kind of surprise in every window: : This is when the elves spot a potential toy malfunction before it hits Santa's sleigh. 🕵️‍♂️🔍 Identification : Imagine announcing over the North Pole PA system which toys might break. 📢🎁 Disclosure : If the mischievous elves (aka hackers) get there first, it's coal for everyone. ⚠️👿 Exploitation Hackers' Winter Wonderland: Why They're Merrymaking with CVEs 'Tis the season for hackers to spread their malicious cheer, as they find joy in exploiting CVEs during the holiday season. Just like characters from Tim Burton's "Nightmare Before Christmas," these cyber-Scrooges have their own twisted version of festive fun. : Picture bots zipping through the digital snow faster than St. Nick's Midnight Express. These automated agents are quick to identify vulnerabilities, constantly searching for weaknesses in systems and networks. They navigate with precision, leaving no stone unturned in their quest to find a way in. Sleigh Ride Scouts : Unfortunately, patches sometimes arrive fashionably late, just like a Christmas card from your dear aunt in July. While security researchers and software vendors work diligently to develop fixes, there can be delays in their release. This gives hackers an extended window of opportunity to exploit the vulnerabilities, like a delayed gift that arrives just in time for the holidays. Patchwork Presents : Security teams find themselves bombarded with an overwhelming number of CVEs, much like trying to discern your own pitch in a chaotic round of '12 Days of Christmas'. With so many alerts, it becomes challenging for security professionals to prioritize and address each vulnerability effectively. Carol of Alerts But why do hackers find such delight in exploiting these vulnerabilities? The excitement and thrill of successfully exploiting a CVE and gaining unauthorized access to systems fuel their motivation. Just as a laser pointer captures a cat's attention, CVEs give hackers an enticing target to focus their efforts on. It's like watching a mischievous cat chasing a laser pointer. So, as we enjoy the holiday season, let's not forget that hackers are also in a festive mood, seeking opportunities to exploit vulnerabilities. By understanding their tactics and taking proactive measures to protect our systems, we can stay one step ahead and ensure a cyber-safe holiday season for ourselves and our organizations. The Naughty List: How the CVE System Can Coal Things Up Our digital Santa Claus faces challenges in keeping his list up-to-date when it comes to managing CVEs: : The teams responsible for managing CVEs are like Santa's reindeer powering a sleigh built for NASA—full of spirit but in need of an upgrade. They work tirelessly to identify and address vulnerabilities, but with the ever-growing software and hardware complexity, they could benefit from increased resources and support. 🦌🔌🚀 Reindeer Resources : Just like that fruitcake from last year that often goes unnoticed but has the potential to cause a disruption, many vulnerabilities may slip through the cracks. These vulnerabilities, although not always in the spotlight, can pose significant risks if left unaddressed. It's crucial to ensure comprehensive coverage and actively identify and patch these vulnerabilities to maintain strong cybersecurity defenses. 🎂🔍 The Great Gingerbread Gap : With millions of toys (or software components) being developed and deployed, Santa's workshop faces the challenge of checking every single one twice. It's a monumental task to ensure that each component is thoroughly vetted and free of vulnerabilities. This requires efficient coordination, collaboration, and quality assurance practices among developers, testers, and security professionals to minimize the chances of introducing vulnerabilities into the software ecosystem. 🧸✅✅ Toy Factory Tangles Expanding on these challenges and exploring how developers play a crucial role in addressing CVEs and strengthening cybersecurity defenses will be the focus of a future blog post. Stay tuned for more insights on this topic! A Carol of Cyber Tactics: How the Grinchy Hackers Move In the world of cybersecurity, hackers have mastered the art of exploiting vulnerabilities, and their tactics are as cunning as a Grinch stealing Christmas presents. Let's take a closer look at two of their most common tactics: : These villains are like carolers who show up at your door before you even have a chance to sing along. Zero-day exploits refer to vulnerabilities that hackers discover and exploit before developers are aware of them. It's like finding a flaw in Santa's sleigh and taking advantage of it before anyone has a chance to fix it. These exploits can cause significant damage as they target vulnerabilities that are unknown to the vendor and, therefore, unpatched. Zero-Day Carolers : Imagine if someone took apart Santa's toys to see how they were built, but instead of putting them back together, they created traps. That's what hackers do when they reverse-engineer patches. When a patch is released to fix a vulnerability, hackers can analyze it to understand the vulnerability and develop an attack to exploit systems that haven't been updated yet. It's like using Santa's own tools against him. Reverse-Engineering Workshop Understanding these tactics is crucial in the . By staying informed and implementing robust security measures, businesses and individuals can protect themselves from these Grinchy hackers and ensure a safer digital environment. 🎄🔒💻 fight against cybercrime Jingling All the Way: The Real-World Impact of CVE Delays In the fast-paced world of cybersecurity, every moment that vulnerabilities go unpatched is like leaving our holiday lights tangled in a box—frustrating and unproductive. Just as we eagerly anticipate the joy of unwrapping presents, cybercriminals eagerly await the opportunity to exploit vulnerabilities that have not been addressed in a timely manner. 🎄🔌 In this winter cybersecurity wonderland, losing time to a CVE is like dropping your roasted chestnuts all over the floor—annoying, messy, and entirely preventable with a little foresight. Just as Santa is said to be watching, hackers are vigilantly observing too, and instead of presents, they're ready to hand out security incidents. We must be proactive in addressing vulnerabilities to ensure a secure digital environment for ourselves and our organizations. 🌰🚫🔒👿💻 It's crucial to understand the real-world impact of CVE delays. Every minute that vulnerabilities are left unpatched increases the risk of data breaches, system downtime, and other costly incidents. These incidents can lead to reputational damage, financial losses, and compromised security. ⏰💥💻 To prevent such consequences, it is essential to prioritize timely patching and implement robust security measures. By promptly addressing CVEs and applying necessary security updates, organizations can minimize the window of opportunity for cybercriminals to exploit vulnerabilities. Remember, in the cybersecurity race, time is of the essence, and staying ahead requires proactive action. ⏳🔒🏃 Let us take the necessary steps to protect our valuable data and assets, ensuring a cyber-safe environment not just during the holiday season but all year round. 🛡️💻🔒 Wrapping Up Your Network: The Cybersecurity Gift-Giving Guide Fear not, for here are some effective strategies to secure your cyber defenses tightly, leaving Santa's elves unable to sneak a peek: : Just like Santa's fleet on Christmas Eve, ensure that your monitoring is omnipresent. Keep a watchful eye on your systems and networks, ready to detect any potential threats. 🦌👀🛡️ Reindeer Reconnaissance : Employ automated tools that tirelessly patch up vulnerabilities, much like Santa's elves wrapping gifts in his workshop. Let these tools work diligently to apply necessary security updates, minimizing the risk of exploitation. 🤖🔧🎁 Automated Elves : Train your team to be as vigilant and alert as a frosty friend. Equip them with the knowledge and awareness to identify and respond to phishing scams, ensuring that they don't fall for any tricks disguised as Santa's outfit. ⛄🎣🎅 Savvy Snowmen (and Women) With these powerful strategies at your disposal, you are not merely waiting for Santa; instead, you're joining him on the rooftop, standing ready to protect your valuable data and assets. 🎅🔒🍪 By implementing these proactive measures, you can confidently safeguard your digital environment, outpacing hackers in this ever-evolving landscape. Conclusion: Sleighing the CVE Grinches In our cyber fairytale, might seem like they're leading the Grinch-conga line toward our digital goodies. But even Santa needs a little help sometimes, and with our advanced preparation and cyber-smart strategies, we're ready to hang our stockings with care—and confidence. 🎄🎅🔒 CVEs Remember, in the cybersecurity night sky, be the brightest star atop the tree, guiding Santa’s sleigh through the fog—not the blinking warning light on a hacker's dashboard. ✨🌟🎅🔒 Because after all, 'tis the season to be secure! 🎄🔒 FAQ Can you give me a festive refresher on CVEs? 🎅🔒 Q: CVEs, also known as Common Vulnerabilities and Exposures, are like those tricky Christmas lights; if one bulb is faulty, the entire string can go dark. Just as you need to regularly check your Christmas lights to ensure they are all functioning properly, CVEs require constant monitoring to identify and address any vulnerabilities in software or hardware. 🕵️‍♀️💡 A: How do CVEs impact cybersecurity? Q: CVEs pose a significant threat to cybersecurity. When vulnerabilities are left unaddressed, hackers can exploit them to gain unauthorized access to systems, leading to data breaches, system downtime, and other costly incidents. Promptly addressing CVEs and implementing robust security measures are crucial to mitigating their impact and protecting valuable assets. 🛡️💻💥 A: What are some challenges with the CVE system? Q: While the CVE system serves as a valuable resource for cataloging and tracking vulnerabilities, it faces certain limitations and challenges. These include limited resources for assigning and tracking vulnerabilities, incomplete coverage of less popular or niche software and hardware, and the complexity of coordinating vulnerability identification and assigning CVEs across various vendors and organizations. 🚫🔍🌐 A: How can organizations defend against CVEs? Q: Organizations can adopt proactive measures to defend against CVEs. This includes staying vigilant through continuous monitoring of systems and networks, implementing automated patch management systems to ensure timely application of critical security updates, and educating employees about cybersecurity risks and best practices. By combining these strategies, organizations can stay one step ahead of hackers and enhance their cybersecurity defenses. 👀🔒🚀 A: May Infosec Be with You.

'Tis the Season to Secure: How CVEs Are the Grinch for Cybersecurity

Solidity 0.8.19 came up with quite a few changes and upgrades. In this post, I’ll talk about user-defined operators for user-defined value types. (I’ll use UDO and UDVT ). Before learning about UDOs, we need to look into UDVTs. What are User-Defined Value Types UDVTs are gasless abstractions of value types over the pre-defined value types in solidity. This was . In simpler terms, we can call them aliases for other value types. The core reason behind introducing this was to facilitate more strict definitions of variables. introduced in solidity 0.8.8 Quick Example For example, our contract stores two types of addresses, one for buyers and the other for sellers. We already know that under the hood, both of these variables will be of type address; however, what if we want to make them different to avoid any confusion or intermingling of different concepts? What if we want the data types to be more descriptive about the value it’s storing? Before UDVTs were introduced, this goal was attained using structs. Below is an example. The four functions in this code are used to wrap or unwrap the given data type into or from the defined data type. I am sure you have seen this type of usage in some contracts. However, as we know, structs are reference types; they’ll use memory, costing more gas than just using uint. This is where UDVTs are being used. They are simple extracts that don’t cost gas. Now, as far as the syntax is concerned, we can define UDVTs like where is the extracted value type, can also call an alias for which is the underlying type that can be uint, address, etc. Once we declare these value types, we get two attached methods with them, and , can be used to convert an underlying type to the newly created value type, is used for the vice versa. type A is B A B wrap unwrap A.wrap(value) and Let’s see this in the code. This was a demonstration related to the previous code snippet however, you might have realized that we don’t need to define the wrapping/unwrapping functions explicitly because . So, if we talk about the usage of these functions, below is another code snippet. solidity gives wrap/unwrap functions // SPDX-License-Identifier: GPL-3.0 
  pragma solidity ^0.8.8;

// Represent an 18 decimal, 256-bit wide fixed point type// using a user-defined value type.type UFixed is uint256;

/// A minimal library to do fixed point operations on UFixed.
uint256 constant multiplier = 10\*\*18;  

/// Adds two UFixed numbers. Reverts on overflow,  
/// relying on checked arithmetic on uint256.  
function add(UFixed a, UFixed b) internal pure returns (UFixed) {  
    return UFixed.wrap(UFixed.unwrap(a) + UFixed.unwrap(b));  
}  

/// Multiplies UFixed and uint256. Reverts on overflow,  
/// relying on checked arithmetic on uint256.  
function mul(UFixed a, uint256 b) internal pure returns (UFixed) {  
    return UFixed.wrap(UFixed.unwrap(a) \* b);  
}  

/// Take the floor of a UFixed number.  
/// @return the largest integer that does not exceed \`a\`.  
function floor(UFixed a) internal pure returns (uint256) {  
    return UFixed.unwrap(a) / multiplier;  
}  

/// Turns a uint256 into a UFixed of the same value.  
/// Reverts if the integer is too large.  
function toUFixed(uint256 a) internal pure returns (UFixed) {  
    return UFixed.wrap(a \* multiplier);  
}  

} We can conclude that UDVTs are not something that affects the logic of the contract but a kind of syntactical sugar that makes our code clearer and readable. math library, for example, which is a library used to tackle the floating number issue in solidity, uses UDVTs to define different types of floating numbers. PRB Now, the problem arises when we try to use arithmetic operations on UDVTs. As you can see in the above example, we have to unwrap the passed variables to use built-in operators. This is where UDOs are introduced. What are User Defined Operators? UDOs are built using the two built-in features of solidity, i.e., built-in operators and . using … for … UDOs are an extended version of . To recall, is used to: using for using for Attaching all Library functions to a data type. using LibrayName for TypeName Attaching library functions to all the data types. using LibrayName for * Attaching specific library functions or free functions to any specific type. using {LibrayName.FunctionName, FreeFunctionName} for TypeName Now, UDO comes into play and defines the fourth type of using for statement. Something like this: using {FunctionName as OperatorSign} for UDVTName global; This syntax facilitates attaching a function as an operator sign, the same as attaching a library function. The difference is we can use an operator sign instead of using the default way of calling the function. This will be clearer by looking at the code example below. There are some rules while using User Defined Operators. They can only be defined as functions(functions defined at the file level). free The free functions should be pure. Can only be defined at global directive, i.e., it can not be inside a contract but at a file level. using for User-defined Operator can only be attached to the UDVTs and not to the underlying default value types. They can only be defined for a particular type, i.e., they won’t work with different UDVTs in the same function. At last, while attaching the operators to any UDVT, only these operator signs can be used: &, |, ^, ~, +, -, *, /, %, ==, !=, <, <=, >, >= . Let’s now look at a code example. // SPDX-License-Identifier: MIT
pragma solidity 0.8.19;

//The types are defined at the file level
type Float is uint256;
type unFloat is uint256;

//"using for" statements are written at the global directive
//not inside a contract
using {add as +} for Float global;
using {multiply as *} for Float global;
using {divide as /} for Float global;

//These are pure free functions, which is a requirement
///@notice Each function works with only one type. 
    function add(Float a, Float b) pure returns (Float) {
        return Float.wrap(Float.unwrap(a) + Float.unwrap(b));
    }

    function multiply(Float a, Float b) pure returns (Float) {
        return Float.wrap(Float.unwrap(a) * Float.unwrap(b));

    }

    function divide(Float a, Float b) pure returns (Float) {
        return Float.wrap(Float.unwrap(a) / Float.unwrap(b));

    }

//Using the attached operators inside a contract
contract UDO {
    
    Float cent = Float.wrap(100);
    Float decimal = Float.wrap(1e18);

 //The multiplication and division using operators is only possible
 // because we attached these particular operators' sign to the relevant functions
    function takePercent(Float _amount, Float totalAmount)
        external
        view
        returns (Float)
    {
        return (_amount * cent * decimal)/(totalAmount);

    }
} Attaching any function to any UDVT is independent of binding the same function to it. This means that we can’t call the free function with UDVTs in a similar fashion as a library function like or when we are binding them as an operator, but obviously, we can do so when they are attached as functions. Let’s look at the example below. add(a,b) a.add(b) // SPDX-License-Identifier: MIT
pragma solidity 0.8.19;

type Float is uint256;
type unFloat is uint256;

//      binding and attaching
using {multiply as *,multiply} for Float global;
using {divide as /} for Float global;

    function multiply(Float a, Float b) pure returns (Float) {
        return Float.wrap(Float.unwrap(a) * Float.unwrap(b));
    }

    function divide(Float a, Float b) pure returns (Float) {
      return Float.wrap(Float.unwrap(a) / Float.unwrap(b));
    }

contract UDO {
    
    Float cent = Float.wrap(100);
    Float decimal = Float.wrap(1e18)

    function takePercent(Float _amount, Float totalAmount)
        external
        view
        returns (Float)
    {
        // return (_amount * cent * decimal)/(totalAmount);
        return      (_amount.multiply(decimal.multiply(cent))).divide(totalAmount);
       //In this line Multiply will work but divide will throw an error, because 
       // we haven't bound the divide function to Float.    
}
} The signs we used for particular functions are not strictly needed; we could’ve used instead of with the add function, and the would work as the add function. However, that will cause unwanted confusion, so we won’t do that. / + / What are the use cases? As discussed earlier, the UDVTs can be used to prevent any kind of type mistakes and provide a better understanding of the logic. UDOs increase the usability of the same by making it more accessible and familiar. The best usage of these are math libraries, where we can have multiple types of floating numbers and much more. That’s it for this article. Join us with all your solidity questions/confusions . HERE Also published . here

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