#dart #android #browser #cookie_manager #flutter #flutter_package #flutter_plugin #flutter_webview #inappbrowser #inappwebview #inline_webview #ios #mobile #plugin #web_storage #webview #webview_control #webview_instances #webview_library #webview_options #wkwebview

https://github.com/pichillilorenzo/flutter_inappwebview

#javascript #console #debugger #developer_tools #eruda #mobile

https://github.com/liriliri/eruda

#typescript #carousel #carousel_component #carousel_plugin #dependency_free #javascript #mobile #mobile_web #react #slider #slider_plugin #slideshow #svelte #touch #touch_evens #vanilla #vue

https://github.com/davidjerleke/embla-carousel

#python #augmix #convnext #distributed_training #dual_path_networks #efficientnet #image_classification #imagenet #maxvit #mixnet #mobile_deep_learning #mobilenet_v2 #mobilenetv3 #nfnets #normalization_free_training #pretrained_models #pretrained_weights #pytorch #randaugment #resnet #vision_transformer_models

PyTorch Image Models (`timm`) is a comprehensive library that includes a wide range of state-of-the-art image models, layers, utilities, optimizers, and training scripts. Here are the key benefits `timm` offers over 300 pre-trained models from various families like Vision Transformers, ResNets, EfficientNets, and more, allowing you to choose the best model for your task.
- **Pre-trained Weights** You can easily extract features at different levels of the network using `features_only=True` and `out_indices`, making it versatile for various applications.
- **Optimizers and Schedulers** It provides several augmentation techniques like AutoAugment, RandAugment, and regularization methods like DropPath and DropBlock to enhance model performance.
- **Reference Training Scripts**: Included are high-performance training, validation, and inference scripts that support multiple GPUs and mixed-precision training.

Overall, `timm` simplifies the process of working with deep learning models for image tasks by providing a unified interface and extensive tools for training and evaluation.

https://github.com/huggingface/pytorch-image-models

#cplusplus #android #audio_processing #c_plus_plus #calculator #computer_vision #deep_learning #framework #graph_based #graph_framework #inference #machine_learning #mediapipe #mobile_development #perception #pipeline_framework #stream_processing #video_processing

MediaPipe is a tool that helps you add smart machine learning features to your apps and devices. It works on mobile, web, desktop, and other devices. You can use pre-made solutions for tasks like vision, text, and audio processing, or customize the models to fit your needs. MediaPipe also offers tools like Model Maker and Studio to help you create and test your solutions easily. This makes it easier to delight your customers with innovative features without needing deep machine learning expertise.

https://github.com/google-ai-edge/mediapipe

#javascript #carousel #gallery #mobile #slider #swipe #swiper #touch #touch_events

Swiper is a free and modern mobile touch slider designed for mobile websites, web apps, and native/hybrid apps. It offers several key features Only imports the modules you use, keeping your app's bundle small.
- **Mobile-friendly** Allows customization of pagination, navigation, and effects like parallax and 3D transitions.
- **Flexible Layout** Delays loading images until they are visible, improving performance.
- **Virtual Slides** Enhances user experience with various navigation options.

Using Swiper benefits you by providing a smooth, hardware-accelerated transition experience, making your mobile applications more engaging and efficient. You can get started quickly with its extensive documentation and demos available.

https://github.com/nolimits4web/swiper

#csharp #android #desktop #dotnet #hacktoberfest #ios #maccatalyst #maui #microsoft #mobile #multi_platform #user_interface #winui #winui3

.NET MAUI is a tool that lets you create apps for many different devices like Android, iOS, iPadOS, macOS, and Windows using just one set of code. This means you can write your app once and it will work on all these platforms. It uses C# and XAML, making it easier and faster to develop apps. With .NET MAUI, you can use Visual Studio tools and emulators to speed up your development process. This saves time and effort because you don't need to write separate codes for each device type.

https://github.com/dotnet/maui

#javascript #api #backend #backend_api #frontend #mobile_development

The FreeAPI.app project is a free and open-source API hub that helps developers learn and work with APIs in any programming language. It offers a wide range of APIs across different industries, making it easy to integrate them into your applications. Here are the key benefits** You can use all the APIs without any cost, allowing you to experiment and build projects freely.
- **Diverse APIs** Clear documentation, code samples, and SDKs make it simple to integrate these APIs into your projects.
- **Community Support** You can run the API hub locally or deploy it to a server, giving you flexibility in your development environment.

This project is great for developers because it removes barriers to entry, offers extensive learning resources, and supports both beginners and advanced developers in building their portfolios.

https://github.com/hiteshchoudhary/apihub

#dart #android #app_framework #cross_platform #dart #dart_platform #desktop #flutter #flutter_package #fuchsia #ios #linux_desktop #macos #material_design #mobile #mobile_development #skia #web #web_framework #windows

Flutter is a tool from Google that helps you create beautiful and fast apps for mobile, web, and desktop using just one codebase. It's free, open source, and works with existing code. Flutter allows you to make changes and see them instantly without restarting your app, making development faster. It also gives you full control over the design and includes many pre-made widgets to help you build apps quickly. With Flutter, you can target multiple platforms like iOS, Android, Windows, macOS, and Linux, making it very versatile and productive for developers.

https://github.com/flutter/flutter

#rust #desktop_app #high_performance #mobile_app #native_app #rust #web_frontend #webview

Tauri is a tool for developers to build fast and small desktop applications that work on Windows, macOS, Linux, and even mobile devices like iOS and Android. You can use any front-end framework that works with HTML, JS, and CSS to create the user interface, while the backend is built with Rust. Tauri offers many features like app bundling, self-updating, system tray icons, and native notifications. It's easy to get started by installing the prerequisites and using the `create-tauri-app` tool. This makes it simpler and faster for developers to create cross-platform applications without a lot of extra work.

https://github.com/tauri-apps/tauri

#typescript #components #mobile #ui_kit #ui_library #vant #vue #vue3

Vant is a lightweight and customizable UI library for building mobile web apps with Vue. It offers over 80 high-quality components, each averaging only 1KB in size, and has no third-party dependencies. Vant supports both Vue 2 and Vue 3, as well as Nuxt 2 and Nuxt 3, and includes features like tree shaking, custom themes, dark mode, and accessibility. It also has extensive documentation, demos, and support for multiple languages. This makes it easy to build fast and efficient mobile web applications with a lot of useful features.

https://github.com/youzan/vant

#java #android #auth #cloud_messaging #firebase #geolocation #google #google_cloud_messaging #java #kotlin #kotlin_android #maps #microg #mobile #push_notifications

microG Services is a free and open-source framework that lets apps designed for Google Play Services work on devices where Play Services is not available. This means you can use many popular apps even if your device doesn't support Google Play Services. To get started, you can find downloads and instructions in the wiki. The project is also open to translations, and it's licensed under the Apache License, which allows free use and modification. This benefits users by giving them more app options on devices that otherwise wouldn't support them.

https://github.com/microg/GmsCore

#c_lang #convolutional_neural_network #convolutional_neural_networks #cpu #inference #inference_optimization #matrix_multiplication #mobile_inference #multithreading #neural_network #neural_networks #simd

XNNPACK is a powerful tool that helps make neural networks run faster on various devices like smartphones, computers, and Raspberry Pi boards. It supports many different types of processors and operating systems, making it very versatile. XNNPACK doesn't work directly with users but instead helps other machine learning frameworks like TensorFlow Lite, PyTorch, and ONNX Runtime to perform better. This means your apps and programs that use these frameworks can run neural networks more quickly and efficiently, which is beneficial because it saves time and improves performance.

https://github.com/google/XNNPACK

#c_lang #ai #app #bci #c #flutter #friend #mobile #necklace #nextjs #omi #personas #python #smartglasses #summary #transcription #wearable

Omi is a wearable AI device that helps you by capturing conversations, summarizing them, and creating action items. It connects to your mobile device and provides automatic transcriptions of meetings and chats. This can save you time and help you remember important details. Omi is also open-source, which means developers can create their own apps for it. However, there are concerns about how it handles user data. Overall, Omi can be useful for boosting productivity and keeping track of conversations.

https://github.com/BasedHardware/omi

#typescript #android #app_framework #expo #framework #frontend #ios #javascript #mobile #native #native_apps #react #react_native #typescript #universal #web #web_framework

Expo is a tool that helps you make apps for Android, iOS, and the web using React and JavaScript. It simplifies the development process by handling complex tasks, allowing you to focus on features. Expo offers fast setup, easy access to native features like the camera, and painless updates without needing store approvals. You can write one codebase and deploy it across multiple platforms, saving time and effort. Expo also has a strong community and flexible workflows, making it easier to find help and customize your app as needed.

https://github.com/expo/expo

#cplusplus #android #app_framework #cross_platform #ios #mobile #mobile_development #react #react_native

React Native lets you build mobile apps for both iOS and Android using just one set of code, which saves a lot of time and effort compared to making separate apps for each platform. You use familiar JavaScript and React skills, and your app looks and feels like a native app on each device. Changes to your code show up quickly, so you can test and improve your app fast. This means you can get your app to users sooner, with less work and cost, and you can easily update or add new features as needed[1][3][5].

https://github.com/facebook/react-native

#dart #android #cross_platform #expense_tracker #flutter #grocery_list #ios #kitchenowl #mobile_app #recipe_manager #self_hosted

KitchenOwl is a helpful app for managing your grocery shopping and recipes. It allows you to create and share shopping lists with others, which is great for families. You can also store and share recipes, plan meals, and track how much you spend. The app is open-source and free, meaning you can use it without paying and even help improve it. It works on many devices, including phones and computers, and can be used offline too. This makes shopping easier and helps you stay organized.

https://github.com/TomBursch/kitchenowl

#python #alibabacloud #android #android_emulator #aws #azure #cloud #docker #docker_android #emulator #gcp #genymotion #jenkins #kubernetes #mobile_app #mobile_web #novnc #saltstack #selenium #selenium_grid #terraform

You can use Docker-Android to run Android emulators inside Docker containers, which helps you develop and test Android apps easily without needing physical devices. It offers many device profiles like Samsung Galaxy and Nexus models, supports viewing the emulator via VNC, sharing logs through a web interface, and controlling the emulator remotely with adb. It works on Ubuntu and can integrate with cloud services like Genymotion. This setup speeds up development, testing, and automation, making your workflow more consistent and efficient while saving resources. You can also persist data and run unit or UI tests with popular frameworks like Appium and Espresso. This helps you build and test Android apps faster and more reliably.

https://github.com/budtmo/docker-android

#python #artificial_intelligence #cloud_ml #computer_systems #courseware #deep_learning #edge_machine_learning #embedded_ml #machine_learning #machine_learning_systems #mobile_ml #textbook #tinyml

You can learn how to build real-world AI systems from start to finish with an open-source textbook originally from Harvard University. It teaches you not just how to train AI models but how to design scalable systems, manage data pipelines, deploy models in production, monitor them continuously, and optimize for devices like phones or IoT gadgets. This helps you become an engineer who can create efficient, reliable, and sustainable AI systems that work well in practice. The book offers hands-on labs, community support, and free online access, making it easier to gain practical skills in machine learning systems engineering.

https://github.com/harvard-edge/cs249r_book

#cplusplus #arm #baidu #deep_learning #embedded #fpga #mali #mdl #mobile #mobile_deep_learning #neural_network

Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance.

https://github.com/PaddlePaddle/Paddle-Lite