Android maintained its position as the leading mobile operating system worldwide in the third quarter of 2025 with a market share of about ***** percent. Android's closest rival, Apple's iOS, had a market share of approximately ***** percent during the same period. The leading mobile operating systems Both unveiled in 2007, Google’s Android and Apple’s iOS have evolved through incremental updates introducing new features and capabilities. The latest version of iOS, iOS 18, was released in September 2024, while the most recent Android iteration, Android 15, was made available in September 2023. A key difference between the two systems concerns hardware - iOS is only available on Apple devices, whereas Android ships with devices from a range of manufacturers such as Samsung, Google and OnePlus. In addition, Apple has had far greater success in bringing its users up to date. As of February 2024, ** percent of iOS users had iOS 17 installed, while in the same month only ** percent of Android users ran the latest version. The rise of the smartphone From around 2010, the touchscreen smartphone revolution had a major impact on sales of basic feature phones, as the sales of smartphones increased from *** million units in 2008 to **** billion units in 2023. In 2020, smartphone sales decreased to **** billion units due to the coronavirus (COVID-19) pandemic. Apple, Samsung, and lately also Xiaomi, were the big winners in this shift towards smartphones, with BlackBerry and Nokia among those unable to capitalize.

This dataset encompasses mobile smartphone application (app) usage, collected from over 150,000 triple-opt-in first-party US Daily Active Users (DAU). Use it for measurement, attribution or surveying to understand the why. iOS and Android operating system coverage.

Tie app usage to web and location events using anonymized PanelistID for omnichannel consumer journey understanding.

This dataset encompasses mobile web clickstream behavior on any browser, collected from over 150,000 triple-opt-in first-party US Daily Active Users (DAU). Use it for measurement, attribution or path to purchase and consumer journey understanding. Full URL deliverable available including searches.

Comprehensive YouTube channel statistics for OGLPLAYS Android iOS Gameplays, featuring 346,000 subscribers and 65,113,547 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Gaming category and is based in US. Track 10,701 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

STL10 - Segmentation

Please consider sponsoring this repo so that we can continue to develop high-quality datasets for the AI and ML research. To become a sponsor: GitHub Sponsors Buy me a coffee You can also sponsor us by downloading our free application, Etiqueta, to your devices: Etiqueta on iOS or Apple Chip Macs Etiqueta on Android This repo contains segmented images for the labeled part of the STL-10 Dataset.
If you are looking for STL10-Labeled variant of the dataset… See the full description on the dataset page: https://huggingface.co/datasets/semihyagli/STL10-Segmented.

Top Flutter Packages Dataset

Flutter is an open source framework by Google for building beautiful, natively compiled, multi-platform applications from a single codebase. It is gaining quite a bit of popularity because of ability to code in a single language and have it running on Android/iOS and web as well. This dataset contains a snapshot of Top 5000+ flutter/dart packages hosted on Flutter package repository The dataset was scraped in August-2024. We aim to use this dataset to… See the full description on the dataset page: https://huggingface.co/datasets/deepklarity/top-flutter-packages.

This dataset encompasses mobile app usage, web clickstream and location visitation behavior, collected from over 150,000 triple-opt-in first-party US Daily Active Users (DAU). The only omnichannel meter at scale representing iOS and Android platforms.

Social media companies are starting to offer users the option to subscribe to their platforms in exchange for monthly fees. Until recently, social media has been predominantly free to use, with tech companies relying on advertising as their main revenue generator. However, advertising revenues have been dropping following the COVID-induced boom. As of July 2023, Meta Verified is the most costly of the subscription services, setting users back almost 15 U.S. dollars per month on iOS or Android. Twitter Blue costs between eight and 11 U.S. dollars per month and ensures users will receive the blue check mark, and have the ability to edit tweets and have NFT profile pictures. Snapchat+, drawing in four million users as of the second quarter of 2023, boasts a Story re-watch function, custom app icons, and a Snapchat+ badge.

User Interface (Navigation) Corpus

  Overview

This dataset serves as a collection of various images of, videos and metadata of mobile (both iOS and Android) and web user interfaces as well as tags and text extractions associated to them. Dataset also includes user interface navigation annotations and videos related to them. One of the possible use cases of this dataset is training a UI navigation agent.

  Dataset Structure

The resources of this dataset are packed… See the full description on the dataset page: https://huggingface.co/datasets/teleren/ui-navigation-corpus.

Comprehensive YouTube channel statistics for Gameplay Android iOS, featuring 2,270,000 subscribers and 1,207,193,557 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Gaming category and is based in US. Track 10,636 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

🇦🇹 오스트리아 English With the ‘Join in!’ app for iPhone, Android and Windows Phone, citizens can report shortcomings or grievances, such as potholes, to their community in a non-bureaucratic and quick manner. For Vienna, the maps of the city of Vienna are offered via the city map interface with a wealth of value-added functions and unprecedented accuracy. The notes are handed over from the app to the Viennese city administration. ### Availability * Apple iOS from version 4.1 * Google Android version 2.1 and higher and * Microsoft Windows Phone from version 7.0

Comprehensive YouTube channel statistics for StarShort APP - GET APP NOW ON IOS & ANDROID , featuring 327,000 subscribers and 4,574,459 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Entertainment category and is based in US. Track 526 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

trajectories.zip contains all trajectories evaluated in our paper, including

WebArena GPT-4 CoT baseline agent extracted from WebArena official release

Android Auto-UI base/large CogAgent Human demonstrations from Android-in-the-Wild

iOS CogAgent basline CogAgent + Self-training CogAgent + Filtered BC

ios-offline-trajectories.zip contains CogAgent's trajectories on iOS emulator, which is then used to refine the CogAgent model through Filtered BC… See the full description on the dataset page: https://huggingface.co/datasets/Agent-Eval-Refine/Agent-Trajectories.

GUI Grounding Benchmark: ScreenSpot Description The ScreenSpot dataset serves as an evaluation benchmark for GUI grounding tasks, designed to facilitate the development and testing of models capable of understanding graphical user interfaces (GUIs) across a variety of platforms. This dataset includes over 1,200 instructions paired with GUI elements from iOS, Android, macOS, Windows, and Web environments. Each entry is meticulously annotated to distinguish between text and icon/widget elements… See the full description on the dataset page: https://huggingface.co/datasets/benwiesel/ScreenSpot.

Comprehensive YouTube channel statistics for Gameplay - Android /ios Gaming Channel, featuring 963,000 subscribers and 360,905,484 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Gaming category and is based in US. Track 4,952 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Dataset Card for ScreenSpot

GUI Grounding Benchmark: ScreenSpot. Created researchers at Nanjing University and Shanghai AI Laboratory for evaluating large multimodal models (LMMs) on GUI grounding tasks on screens given a text-based instruction.

  Dataset Details





  Dataset Description

ScreenSpot is an evaluation benchmark for GUI grounding, comprising over 1200 instructions from iOS, Android, macOS, Windows and Web environments, along with annotated element types… See the full description on the dataset page: https://huggingface.co/datasets/lett9468/test2.

ANTI_FORENSIC_DATASET

  Overview

The ANTI_FORENSIC_DATASET is a comprehensive collection of anti-forensic tools and techniques designed for red team operations in controlled sandbox environments. This dataset provides detailed information on methods to evade forensic analysis across multiple platforms, including Windows, macOS, Android, and iOS. It is intended for security researchers, penetration testers, and cybersecurity professionals to test and evaluate anti-forensic… See the full description on the dataset page: https://huggingface.co/datasets/darkknight25/ANTI_forensic_dataset.jsonl.

Introducing the English Product Image Dataset - a diverse and comprehensive collection of images meticulously curated to propel the advancement of text recognition and optical character recognition (OCR) models designed specifically for the English language.

Dataset Contain & Diversity

Containing a total of 2000 images, this English OCR dataset offers diverse distribution across different types of front images of Products. In this dataset, you'll find a variety of text that includes product names, taglines, logos, company names, addresses, product content, etc. Images in this dataset showcase distinct fonts, writing formats, colors, designs, and layouts.

To ensure the diversity of the dataset and to build a robust text recognition model we allow limited (less than five) unique images from a single resource. Stringent measures have been taken to exclude any personally identifiable information (PII) and to ensure that in each image a minimum of 80% of space contains visible English text.

Images have been captured under varying lighting conditions – both day and night – along with different capture angles and backgrounds, to build a balanced OCR dataset. The collection features images in portrait and landscape modes.

All these images were captured by native English people to ensure the text quality, avoid toxic content and PII text. We used the latest iOS and Android mobile devices above 5MP cameras to click all these images to maintain the image quality. In this training dataset images are available in both JPEG and HEIC formats.

Metadata

Along with the image data, you will also receive detailed structured metadata in CSV format. For each image, it includes metadata like image orientation, county, language, and device information. Each image is properly renamed corresponding to the metadata.

The metadata serves as a valuable tool for understanding and characterizing the data, facilitating informed decision-making in the development of English text recognition models.

Update & Custom Collection

We're committed to expanding this dataset by continuously adding more images with the assistance of our native English crowd community.

If you require a custom product image OCR dataset tailored to your guidelines or specific device distribution, feel free to contact us. We're equipped to curate specialized data to meet your unique needs.

Furthermore, we can annotate or label the images with bounding box or transcribe the text in the image to align with your specific project requirements using our crowd community.

License

This Image dataset, created by FutureBeeAI, is now available for commercial use.

Conclusion:

Leverage the power of this product image OCR dataset to elevate the training and performance of text recognition, text detection, and optical character recognition models within the realm of the English language. Your journey to enhanced language understanding and processing starts here.