Developer builds Linux video player with NVIDIA AI upscaling and frame interpolation

·1 views

A developer has created an open-source Linux video player that brings NVIDIA RTX VSR-style AI upscaling and RIFE frame interpolation to Linux, where NVIDIA officially limits these features to Windows. The project, called vsr-player, is built around NVIDIA's Video Effects SDK and integrates with a patched version of libmpv as custom video filters, with a Qt-based frontend. A companion CLI tool, mpv-vsr, offers the same AI filters in a drop-in compatible form for existing mpv workflows, including support for yt-dlp and external scripts. The entire post-decode pipeline runs on the GPU via CUDA-Vulkan interop, eliminating per-frame CPU round-trips, and a single TensorRT engine file supports RTX 30, 40, and 50 series cards for interpolation. The hobby project was developed with heavy AI assistance using Claude Code and DeepSeek, requires an NVIDIA RTX 20 or newer GPU with driver 570 or later, and is available on GitHub.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Three Ways to Edit Files Directly in AWS CloudShell

AWS CloudShell offers multiple options for editing files without leaving the browser-based terminal environment. Users comfortable with terminal editors can use Vim for full navigation features or Nano for a simpler interface with on-screen shortcut prompts. A third option, the built-in 'edit' command, opens files in a graphical editor similar to VS Code, supporting familiar shortcuts like CTRL+S to save. Each method suits a different comfort level, from seasoned Vim users to those who prefer point-and-click editing. The choice ultimately depends on which tool helps the user resolve their task most quickly.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Why SKILL.md Files Cannot Enforce Coding Rules in AI Tools Like Cursor

AI coding assistants like Cursor often ignore rules written in SKILL.md files because model attention is limited and recent tool outputs outweigh instructions seen earlier in a session. The model tends to prioritize completing the user's latest request over adhering to a rule file loaded at the start of a conversation. A more reliable approach pairs the skill file with a hard command layer — such as running tsc --noEmit or a test suite — that must pass before any output is declared production-ready. Unlike text instructions, a failing compiler or test command produces a concrete, undeniable signal that forces the agent to make corrections. The author recommends reserving hooks for deterministic tools like formatters, resetting chat threads between features, and always requesting that typecheck and test output be pasted at the end of each session.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

One line of code adds tab completion to Python CLIs via shtab and jsonargparse

A developer building a Python command-line tool found that users had no way to discover valid argument values mid-command, such as the four accepted strings for an order_by parameter. Rather than writing separate shell completion scripts for bash, zsh, fish, and tcsh — each in a different syntax — the author turned to shtab, an optional dependency of jsonargparse. By adding shtab to the project's dependencies and calling set_parsing_settings(add_print_completion_argument=True) in one line, the CLI automatically gains a --print_completion flag. The completion scripts are generated by inspecting the existing parser, which already knows all valid choices from the client's type hints, meaning no manual maintenance is required. The approach keeps tab completion in sync with the interface automatically, since both derive from the same source code.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Why Browser Games That Seem Offline Often Still Require an Internet Connection

Many browser games give the impression of being offline-capable due to fast load times and simple gameplay, but they frequently depend on internet access for assets, leaderboards, authentication, and analytics. Developers distinguish between three scenarios: truly offline-capable games with deliberate caching architecture, partly cached games that may break unpredictably, and online games that merely mimic an offline aesthetic. Standard browser caching is not a reliable substitute for offline support, as the browser can revalidate, remove, or update files independently, meaning a single missing resource can prevent a game from loading. Service workers offer a more intentional solution by intercepting network requests and serving cached content, though they introduce their own versioning challenges if not carefully managed. Reliable offline functionality must be explicitly designed and tested as a complete user experience rather than assumed from partial caching.

0 comments Read more at DEV Community