#jupyter_notebook #agentic_ai #agents #course #huggingface #langchain #llamaindex #smolagents
The Hugging Face Agents Course is a free, interactive course that teaches you how to build and deploy AI agents. It's divided into four units, starting with the basics of agents and ending with a final project where you create and test your own agent. You'll learn about frameworks like `smolagents`, `LangGraph`, and `LlamaIndex`, and how to use large language models (LLMs) in your agents. The course benefits you by providing hands-on experience and practical skills in AI agent development, helping you become proficient in creating and deploying AI agents.
https://github.com/huggingface/agents-course
The Hugging Face Agents Course is a free, interactive course that teaches you how to build and deploy AI agents. It's divided into four units, starting with the basics of agents and ending with a final project where you create and test your own agent. You'll learn about frameworks like `smolagents`, `LangGraph`, and `LlamaIndex`, and how to use large language models (LLMs) in your agents. The course benefits you by providing hands-on experience and practical skills in AI agent development, helping you become proficient in creating and deploying AI agents.
https://github.com/huggingface/agents-course
GitHub
GitHub - huggingface/agents-course: This repository contains the Hugging Face Agents Course.
This repository contains the Hugging Face Agents Course. - GitHub - huggingface/agents-course: This repository contains the Hugging Face Agents Course.
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#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
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
GitHub
GitHub - expo/expo: An open-source framework for making universal native apps with React. Expo runs on Android, iOS, and the web.
An open-source framework for making universal native apps with React. Expo runs on Android, iOS, and the web. - expo/expo
#python #api #bracket #brackets #docker #docusaurus #fastapi #json #mantine #nextjs #postgresql #python #react #reactjs #selfhosted #sports #tournament_bracket #tournament_manager #tournaments #web #yarn
Bracket is a tool for organizing tournaments. It supports different formats like single elimination, round-robin, and Swiss. You can create teams, add players, and manage multiple clubs with several tournaments. The system allows you to drag-and-drop matches to different courts or reschedule them. It also provides customizable dashboard pages for public viewing. This makes it easier to manage and engage with tournaments, offering more flexibility and control for organizers and participants.
https://github.com/evroon/bracket
Bracket is a tool for organizing tournaments. It supports different formats like single elimination, round-robin, and Swiss. You can create teams, add players, and manage multiple clubs with several tournaments. The system allows you to drag-and-drop matches to different courts or reschedule them. It also provides customizable dashboard pages for public viewing. This makes it easier to manage and engage with tournaments, offering more flexibility and control for organizers and participants.
https://github.com/evroon/bracket
GitHub
GitHub - evroon/bracket: Selfhosted tournament system
Selfhosted tournament system. Contribute to evroon/bracket development by creating an account on GitHub.
#typescript #chatgpt #claude #copilot #cursor #developer_tools #editor #llm #open_source #openai #visual_studio_code #vscode #vscode_extension
Void is a free, open-source code editor that works like Cursor but gives you more control over your data and lets you use any AI model you want, including ones you run yourself. It’s built on top of VS Code, so you can keep your favorite settings and themes. Void offers features like AI-powered code completion, quick edits, and chat with different AI models, and you can even see and change the prompts the AI uses. This means you can code faster, work privately, and use the latest AI tools without being locked into one provider or worrying about your data being sent elsewhere[1][2][4].
https://github.com/voideditor/void
Void is a free, open-source code editor that works like Cursor but gives you more control over your data and lets you use any AI model you want, including ones you run yourself. It’s built on top of VS Code, so you can keep your favorite settings and themes. Void offers features like AI-powered code completion, quick edits, and chat with different AI models, and you can even see and change the prompts the AI uses. This means you can code faster, work privately, and use the latest AI tools without being locked into one provider or worrying about your data being sent elsewhere[1][2][4].
https://github.com/voideditor/void
GitHub
GitHub - voideditor/void
Contribute to voideditor/void development by creating an account on GitHub.
#go #backend #backend_as_a_service #chat_server #game_backend #game_framework #game_server #multiplayer #nakama #realtime #realtime_games #social #unity_engine #unreal_engine
Nakama is an open-source, scalable server for building social and real-time multiplayer games and apps. It offers features like user accounts, social connections, chat, multiplayer matchmaking, leaderboards, tournaments, and in-app purchase validation. You can extend it with custom code in Lua, JavaScript, or Go. Nakama supports multiple platforms and protocols, making it easy to integrate with popular game engines. It includes a web console for managing player data and game metrics. You can run Nakama locally with Docker or deploy it on any cloud provider. This helps you quickly build and scale games with ready-made backend services, saving time and effort.
https://github.com/heroiclabs/nakama
Nakama is an open-source, scalable server for building social and real-time multiplayer games and apps. It offers features like user accounts, social connections, chat, multiplayer matchmaking, leaderboards, tournaments, and in-app purchase validation. You can extend it with custom code in Lua, JavaScript, or Go. Nakama supports multiple platforms and protocols, making it easy to integrate with popular game engines. It includes a web console for managing player data and game metrics. You can run Nakama locally with Docker or deploy it on any cloud provider. This helps you quickly build and scale games with ready-made backend services, saving time and effort.
https://github.com/heroiclabs/nakama
GitHub
GitHub - heroiclabs/nakama: Distributed server for social and realtime games and apps.
Distributed server for social and realtime games and apps. - heroiclabs/nakama
#typescript #bigquery #cassandra #cockroachdb #database #electron #firebird #linux_app #mac_app #mariadb #mssql #mysql #postgresql #sql #sql_server #sqlite #windows_app
Beekeeper Studio is a free, open-source SQL editor and database manager that works on Windows, Mac, and Linux. It supports many databases like MySQL, PostgreSQL, and SQLite. The app offers features like auto-complete SQL queries, syntax highlighting, and a tabbed interface for multitasking. You can sort and filter data, save queries, and even export data in formats like CSV or JSON. It's designed to be easy to use and enjoyable, making database management simpler for everyone. You can download it for free and upgrade to premium features if needed.
https://github.com/beekeeper-studio/beekeeper-studio
Beekeeper Studio is a free, open-source SQL editor and database manager that works on Windows, Mac, and Linux. It supports many databases like MySQL, PostgreSQL, and SQLite. The app offers features like auto-complete SQL queries, syntax highlighting, and a tabbed interface for multitasking. You can sort and filter data, save queries, and even export data in formats like CSV or JSON. It's designed to be easy to use and enjoyable, making database management simpler for everyone. You can download it for free and upgrade to premium features if needed.
https://github.com/beekeeper-studio/beekeeper-studio
GitHub
GitHub - beekeeper-studio/beekeeper-studio: Modern and easy to use SQL client for MySQL, Postgres, SQLite, SQL Server, and more.…
Modern and easy to use SQL client for MySQL, Postgres, SQLite, SQL Server, and more. Linux, MacOS, and Windows. - beekeeper-studio/beekeeper-studio
#kotlin #android #awt #compose #declarative_ui #desktop #gui #ios #javascript #kotlin #multiplatform #reactive #swing #ui #wasm #web #webassembly
Compose Multiplatform is a Kotlin-based framework by JetBrains that lets you build user interfaces for multiple platforms—iOS, Android, desktop (Windows, macOS, Linux), and web—using mostly shared code. It is based on Jetpack Compose for Android, so you can use similar APIs across platforms, speeding up development and ensuring consistent UI design. iOS support is in beta, web is in alpha, and desktop and Android are stable. You can also access native features like camera or maps easily. This helps you save time, reduce bugs, and create apps that work well everywhere with less effort.
https://github.com/JetBrains/compose-multiplatform
Compose Multiplatform is a Kotlin-based framework by JetBrains that lets you build user interfaces for multiple platforms—iOS, Android, desktop (Windows, macOS, Linux), and web—using mostly shared code. It is based on Jetpack Compose for Android, so you can use similar APIs across platforms, speeding up development and ensuring consistent UI design. iOS support is in beta, web is in alpha, and desktop and Android are stable. You can also access native features like camera or maps easily. This helps you save time, reduce bugs, and create apps that work well everywhere with less effort.
https://github.com/JetBrains/compose-multiplatform
GitHub
GitHub - JetBrains/compose-multiplatform: Compose Multiplatform, a modern UI framework for Kotlin that makes building performant…
Compose Multiplatform, a modern UI framework for Kotlin that makes building performant and beautiful user interfaces easy and enjoyable. - JetBrains/compose-multiplatform
#go
The **docker2exe** tool helps convert Docker images into executable files that can be shared easily. This means you can send a program to friends without them needing to set up Docker themselves. The tool requires Docker, GoLang, and gzip to work. When someone runs the executable, it checks if the needed Docker image is on their system. If not, it can automatically download or load the image from a built-in file, making it easy to run the program on different computers. This simplifies sharing and running applications across different environments.
https://github.com/rzane/docker2exe
The **docker2exe** tool helps convert Docker images into executable files that can be shared easily. This means you can send a program to friends without them needing to set up Docker themselves. The tool requires Docker, GoLang, and gzip to work. When someone runs the executable, it checks if the needed Docker image is on their system. If not, it can automatically download or load the image from a built-in file, making it easy to run the program on different computers. This simplifies sharing and running applications across different environments.
https://github.com/rzane/docker2exe
GitHub
GitHub - rzane/docker2exe: Convert a Docker image to an executable
Convert a Docker image to an executable. Contribute to rzane/docker2exe development by creating an account on GitHub.
#python #apple_silicon #audio_processing #mlx #multimodal #speech_recognition #speech_synthesis #speech_to_text #text_to_speech #transformers
MLX-Audio is a powerful tool for converting text into speech and speech into new audio. It works well on Apple Silicon devices, like M-series chips, making it fast and efficient. You can choose from different languages and voices, and even adjust how fast the speech is. It also includes a web interface where you can see audio in 3D and play your own files. This tool is helpful for making audiobooks, interactive media, and personal projects because it's easy to use and provides high-quality audio quickly.
https://github.com/Blaizzy/mlx-audio
MLX-Audio is a powerful tool for converting text into speech and speech into new audio. It works well on Apple Silicon devices, like M-series chips, making it fast and efficient. You can choose from different languages and voices, and even adjust how fast the speech is. It also includes a web interface where you can see audio in 3D and play your own files. This tool is helpful for making audiobooks, interactive media, and personal projects because it's easy to use and provides high-quality audio quickly.
https://github.com/Blaizzy/mlx-audio
GitHub
GitHub - Blaizzy/mlx-audio: A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library built on Apple's MLX…
A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library built on Apple's MLX framework, providing efficient speech analysis on Apple Silicon. - Blaizzy/mlx-audio
#javascript
Open MCT is a tool developed by NASA for visualizing data on computers and mobile devices. It helps analyze and manage data from spacecraft and other systems. The tool is open source, meaning anyone can use and modify it. This makes it useful for many different types of projects that involve collecting and analyzing data. Users can extend Open MCT with plugins to fit their specific needs, making it a flexible and powerful tool for data analysis and management.
https://github.com/nasa/openmct
Open MCT is a tool developed by NASA for visualizing data on computers and mobile devices. It helps analyze and manage data from spacecraft and other systems. The tool is open source, meaning anyone can use and modify it. This makes it useful for many different types of projects that involve collecting and analyzing data. Users can extend Open MCT with plugins to fit their specific needs, making it a flexible and powerful tool for data analysis and management.
https://github.com/nasa/openmct
GitHub
GitHub - nasa/openmct: A web based mission control framework.
A web based mission control framework. . Contribute to nasa/openmct development by creating an account on GitHub.
#python #asr #deeplearning #generative_ai #large_language_models #machine_translation #multimodal #neural_networks #speaker_diariazation #speaker_recognition #speech_synthesis #speech_translation #tts
NVIDIA NeMo is a powerful, easy-to-use platform for building, customizing, and deploying generative AI models like large language models (LLMs), vision language models, and speech AI. It lets you quickly train and fine-tune models using pre-built code and checkpoints, supports the latest model architectures, and works on cloud, data center, or edge environments. NeMo 2.0 is even more flexible and scalable, with Python-based configuration and modular design, making it simple to experiment and scale up. The main benefit is that you can create advanced AI applications faster, with less effort, and at lower cost, while getting high performance and easy deployment options[1][2][3].
https://github.com/NVIDIA/NeMo
NVIDIA NeMo is a powerful, easy-to-use platform for building, customizing, and deploying generative AI models like large language models (LLMs), vision language models, and speech AI. It lets you quickly train and fine-tune models using pre-built code and checkpoints, supports the latest model architectures, and works on cloud, data center, or edge environments. NeMo 2.0 is even more flexible and scalable, with Python-based configuration and modular design, making it simple to experiment and scale up. The main benefit is that you can create advanced AI applications faster, with less effort, and at lower cost, while getting high performance and easy deployment options[1][2][3].
https://github.com/NVIDIA/NeMo
GitHub
GitHub - NVIDIA-NeMo/NeMo: A scalable generative AI framework built for researchers and developers working on Large Language Models…
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech) - NVIDIA-NeMo/NeMo
#rust #gpui #macos #shadcn #ui #windows
GPUI Component offers over 40 easy-to-use, customizable UI elements for building modern desktop apps that look like macOS and Windows, with support for multiple themes and flexible layouts. It includes high-performance tables and lists for handling large data smoothly, plus native Markdown and simple HTML rendering. You can add WebView support and use any SVG icons you want. Although still in development, it’s designed to help you create beautiful, fast, and adaptable desktop applications with less effort, making your app development more efficient and visually appealing. This benefits you by speeding up UI creation and improving user experience.
https://github.com/longbridge/gpui-component
GPUI Component offers over 40 easy-to-use, customizable UI elements for building modern desktop apps that look like macOS and Windows, with support for multiple themes and flexible layouts. It includes high-performance tables and lists for handling large data smoothly, plus native Markdown and simple HTML rendering. You can add WebView support and use any SVG icons you want. Although still in development, it’s designed to help you create beautiful, fast, and adaptable desktop applications with less effort, making your app development more efficient and visually appealing. This benefits you by speeding up UI creation and improving user experience.
https://github.com/longbridge/gpui-component
GitHub
GitHub - longbridge/gpui-component: Rust GUI components for building fantastic cross-platform desktop application by using GPUI.
Rust GUI components for building fantastic cross-platform desktop application by using GPUI. - longbridge/gpui-component
#python #diffusion_models #dit #image_to_video #image_to_video_generation #text_to_video #text_to_video_generation
LTX-Video is a powerful AI model that creates high-quality, realistic videos in real time, running faster than you can watch them. It can generate videos from text descriptions, images, or existing videos, and supports advanced features like keyframe animation and video extension. You can use it online or run it locally with easy setup. It offers great control over video details, smooth motion, and works well even on consumer hardware. This helps you quickly create custom videos for storytelling, social media, or prototyping, saving time and boosting creativity with detailed, lifelike results[2][4][5].
https://github.com/Lightricks/LTX-Video
LTX-Video is a powerful AI model that creates high-quality, realistic videos in real time, running faster than you can watch them. It can generate videos from text descriptions, images, or existing videos, and supports advanced features like keyframe animation and video extension. You can use it online or run it locally with easy setup. It offers great control over video details, smooth motion, and works well even on consumer hardware. This helps you quickly create custom videos for storytelling, social media, or prototyping, saving time and boosting creativity with detailed, lifelike results[2][4][5].
https://github.com/Lightricks/LTX-Video
GitHub
GitHub - Lightricks/LTX-Video: Official repository for LTX-Video
Official repository for LTX-Video. Contribute to Lightricks/LTX-Video development by creating an account on GitHub.
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#python #comfyui #diffusion_models #dit #image_to_video #image_to_video_generation #text_to_image #text_to_image_generation
ComfyUI-LTXVideo is a tool that helps create high-quality videos from images using AI. It offers features like key frame control, improved video quality, and faster generation speeds. This means you can make smooth videos with fewer errors and more control over how they look. It also supports commercial use, so you can use the videos for business projects. The tool is designed to work well with consumer-grade GPUs, making it accessible to more users. Overall, it helps you create professional-looking videos quickly and easily.
https://github.com/Lightricks/ComfyUI-LTXVideo
ComfyUI-LTXVideo is a tool that helps create high-quality videos from images using AI. It offers features like key frame control, improved video quality, and faster generation speeds. This means you can make smooth videos with fewer errors and more control over how they look. It also supports commercial use, so you can use the videos for business projects. The tool is designed to work well with consumer-grade GPUs, making it accessible to more users. Overall, it helps you create professional-looking videos quickly and easily.
https://github.com/Lightricks/ComfyUI-LTXVideo
GitHub
GitHub - Lightricks/ComfyUI-LTXVideo: LTX-Video Support for ComfyUI
LTX-Video Support for ComfyUI. Contribute to Lightricks/ComfyUI-LTXVideo development by creating an account on GitHub.
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#typescript #component_library #element_plus #element_ui #vue #vue_components #vuejs
Element Plus is a UI library for Vue 3, built with TypeScript and the Composition API. It offers a variety of customizable components and a cool design language, making it easy for developers and designers to create user interfaces. The library is open-source and actively maintained, with tools like a migration tool to help transition from Element UI. This makes it a great choice for building modern web applications with a consistent look and feel.
https://github.com/element-plus/element-plus
Element Plus is a UI library for Vue 3, built with TypeScript and the Composition API. It offers a variety of customizable components and a cool design language, making it easy for developers and designers to create user interfaces. The library is open-source and actively maintained, with tools like a migration tool to help transition from Element UI. This makes it a great choice for building modern web applications with a consistent look and feel.
https://github.com/element-plus/element-plus
GitHub
GitHub - element-plus/element-plus: 🎉 A Vue.js 3 UI Library made by Element team
🎉 A Vue.js 3 UI Library made by Element team. Contribute to element-plus/element-plus development by creating an account on GitHub.
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#csharp #architecture #aspnetcore #clean_architecture #cqrs #ddd #dotnet #dotnetcore #event_driven_architecture #event_sourcing #kubernetes #masstransit #messaging #microservice #microservices #oauth2 #opentelemetry #software_architecture #software_design #software_engineering #vertical_slice_architecture
Migrating from a monolithic architecture to a cloud-native microservices architecture offers several benefits. It improves scalability, allowing different parts of the application to grow independently. This approach also enhances reliability by isolating faults, so if one service fails, others continue to work. Additionally, microservices enable faster deployment and updates, as each service can be developed and deployed separately. This flexibility allows teams to use the best technology for each service, making development more efficient and agile[2][3][5].
https://github.com/meysamhadeli/monolith-to-cloud-architecture
Migrating from a monolithic architecture to a cloud-native microservices architecture offers several benefits. It improves scalability, allowing different parts of the application to grow independently. This approach also enhances reliability by isolating faults, so if one service fails, others continue to work. Additionally, microservices enable faster deployment and updates, as each service can be developed and deployed separately. This flexibility allows teams to use the best technology for each service, making development more efficient and agile[2][3][5].
https://github.com/meysamhadeli/monolith-to-cloud-architecture
GitHub
GitHub - meysamhadeli/booking-microservices: A practical microservices with the latest technologies and architectures like Vertical…
A practical microservices with the latest technologies and architectures like Vertical Slice Architecture, Event Sourcing, CQRS, DDD, gRpc, MongoDB, RabbitMq, Masstransit, and Aspire in .Net 9. - ...
#cplusplus #gamedev #gamedev_library #gamedevelopment #library #performance #performance_analysis #profiler #profiling #profiling_library
Tracy Profiler is a powerful tool that helps you understand how your applications are performing. It can track CPU, GPU, memory usage, and more in real-time with very precise timing. This means you can see exactly where your program is spending time, which helps you make it faster and more efficient. Tracy supports many programming languages and can even capture screenshots of your application's frames. By using Tracy, you can identify and fix performance issues, making your applications run smoother and better.
https://github.com/wolfpld/tracy
Tracy Profiler is a powerful tool that helps you understand how your applications are performing. It can track CPU, GPU, memory usage, and more in real-time with very precise timing. This means you can see exactly where your program is spending time, which helps you make it faster and more efficient. Tracy supports many programming languages and can even capture screenshots of your application's frames. By using Tracy, you can identify and fix performance issues, making your applications run smoother and better.
https://github.com/wolfpld/tracy
GitHub
GitHub - wolfpld/tracy: Frame profiler
Frame profiler. Contribute to wolfpld/tracy development by creating an account on GitHub.
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#jupyter_notebook #a2a #agentic_ai #dapr #dapr_pub_sub #dapr_service_invocation #dapr_sidecar #dapr_workflow #docker #kafka #kubernetes #langmem #mcp #openai #openai_agents_sdk #openai_api #postgresql_database #rabbitmq #rancher_desktop #redis #serverless_containers
The Dapr Agentic Cloud Ascent (DACA) design pattern helps you build powerful, scalable AI systems that can handle millions of AI agents working together without crashing. It uses Dapr technology with Kubernetes to efficiently manage many AI agents as lightweight virtual actors, ensuring fast response, reliability, and easy scaling. You can start small using free or low-cost cloud tools and grow to planet-scale systems. The OpenAI Agents SDK is recommended for beginners because it is simple, flexible, and gives you good control to develop AI agents quickly. This approach saves costs, avoids vendor lock-in, and supports resilient, event-driven AI workflows, making it ideal for developers aiming to create advanced, cloud-native AI applications[1][2][3][4].
https://github.com/panaversity/learn-agentic-ai
The Dapr Agentic Cloud Ascent (DACA) design pattern helps you build powerful, scalable AI systems that can handle millions of AI agents working together without crashing. It uses Dapr technology with Kubernetes to efficiently manage many AI agents as lightweight virtual actors, ensuring fast response, reliability, and easy scaling. You can start small using free or low-cost cloud tools and grow to planet-scale systems. The OpenAI Agents SDK is recommended for beginners because it is simple, flexible, and gives you good control to develop AI agents quickly. This approach saves costs, avoids vendor lock-in, and supports resilient, event-driven AI workflows, making it ideal for developers aiming to create advanced, cloud-native AI applications[1][2][3][4].
https://github.com/panaversity/learn-agentic-ai
GitHub
GitHub - panaversity/learn-agentic-ai: Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native…
Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kuberne...
#python
FieldStation42 is a project that lets you experience old TV like it was in the past. It uses a Raspberry Pi to simulate multiple TV channels with shows and commercials. You can set up different channels, schedule shows, and even add seasonal content. The system supports multiple channels playing at the same time and can automatically insert commercials. This project is great for people who miss the old TV experience and want to relive it with a nostalgic feel. It requires some technical setup but offers a fun way to enjoy retro TV.
https://github.com/shane-mason/FieldStation42
FieldStation42 is a project that lets you experience old TV like it was in the past. It uses a Raspberry Pi to simulate multiple TV channels with shows and commercials. You can set up different channels, schedule shows, and even add seasonal content. The system supports multiple channels playing at the same time and can automatically insert commercials. This project is great for people who miss the old TV experience and want to relive it with a nostalgic feel. It requires some technical setup but offers a fun way to enjoy retro TV.
https://github.com/shane-mason/FieldStation42
GitHub
GitHub - shane-mason/FieldStation42: Broadcast & Cable TV simulator
Broadcast & Cable TV simulator. Contribute to shane-mason/FieldStation42 development by creating an account on GitHub.
#python #d_fine #detr #object_detection
D-FINE is a fast and accurate real-time object detection model that improves how bounding boxes are predicted by refining detailed probability distributions for each box edge, making localization more precise. It uses two main techniques: Fine-grained Distribution Refinement (FDR), which iteratively improves box predictions by focusing on uncertainties, and Global Optimal Localization Self-Distillation (GO-LSD), which helps earlier layers learn from later, more accurate predictions. This approach boosts detection accuracy without extra training or inference costs, making it efficient and effective for detecting objects even in complex scenes. You benefit by getting better, faster object detection with less computational effort.
https://github.com/Peterande/D-FINE
D-FINE is a fast and accurate real-time object detection model that improves how bounding boxes are predicted by refining detailed probability distributions for each box edge, making localization more precise. It uses two main techniques: Fine-grained Distribution Refinement (FDR), which iteratively improves box predictions by focusing on uncertainties, and Global Optimal Localization Self-Distillation (GO-LSD), which helps earlier layers learn from later, more accurate predictions. This approach boosts detection accuracy without extra training or inference costs, making it efficient and effective for detecting objects even in complex scenes. You benefit by getting better, faster object detection with less computational effort.
https://github.com/Peterande/D-FINE
GitHub
GitHub - Peterande/D-FINE: D-FINE: Redefine Regression Task of DETRs as Fine-grained Distribution Refinement [ICLR 2025 Spotlight]
D-FINE: Redefine Regression Task of DETRs as Fine-grained Distribution Refinement [ICLR 2025 Spotlight] - Peterande/D-FINE
#cplusplus
A group of fans has successfully decompiled the classic game **LEGO Island**. This means they have reverse-engineered the game's code to make it editable and playable again. The decompilation is complete for version 1.1 of the game, allowing users to compile and play it from scratch. This project benefits users by making the game available on modern systems and potentially allowing it to be ported to other platforms. Users can now modify and improve the game, ensuring its charm and fun are preserved for new generations.
https://github.com/isledecomp/isle
A group of fans has successfully decompiled the classic game **LEGO Island**. This means they have reverse-engineered the game's code to make it editable and playable again. The decompilation is complete for version 1.1 of the game, allowing users to compile and play it from scratch. This project benefits users by making the game available on modern systems and potentially allowing it to be ported to other platforms. Users can now modify and improve the game, ensuring its charm and fun are preserved for new generations.
https://github.com/isledecomp/isle
GitHub
GitHub - isledecomp/isle: A decompilation of LEGO Island (1997)
A decompilation of LEGO Island (1997). Contribute to isledecomp/isle development by creating an account on GitHub.
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