Search Results for "context"

StoryMem is a narrative-focused memory accumulation system that lets users build, store, and reference past conversational context or story elements with an AI, effectively enabling the AI to maintain and recall personalized story memories or character arcs over time. Instead of treating each interaction as stateless, it tracks user-defined memory nodes, tags, and story threads so that future interactions can draw on established narrative context like character traits, past events, or ongoing plotlines. ...

...Instead of applying a static center crop, the system intelligently tracks people or key objects to preserve visual focus and composition. When cropping would degrade the scene, it can switch to alternative layouts such as letterboxing to maintain context. The tool integrates FFmpeg for encoding and rendering, ensuring efficient processing and compatibility with standard video workflows. It supports multiple output aspect ratios and quality settings, allowing customization for different platforms. Designed as a lightweight script, it runs locally and provides a cost-free alternative to commercial video reframing tools.

AV1 AVIF is the official specification and reference design for the AV1 Image File Format (AVIF), defining how AV1-encoded bitstreams are packaged into the HEIF container format (based on ISOBMFF) to produce AVIF files. The project outlines the syntax and semantics required for AVIF compliance, including support for multiple image profiles, color depths, chroma subsampling modes, HDR/WCG, alpha channels, animation/image sequences, and various color-space/bit-depth combinations — making AVIF...

...Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. The repo provides training recipes and models for standard datasets, as well as ablations that show how many non-local blocks to insert and at which stages. Efficient implementations keep memory and compute manageable so the blocks can be added without rewriting the entire backbone. The result is a practical, drop-in mechanism for upgrading purely local video models into context-aware networks with strong benchmark performance.

aws-lambda-ffmpeg is a project that enables running FFmpeg within AWS Lambda environments, allowing serverless media processing workflows. It packages FFmpeg binaries and provides examples of how to execute video and audio processing tasks in a serverless context. The system allows users to perform operations such as transcoding, resizing, and format conversion without managing dedicated servers. It leverages cloud storage services like S3 for input and output handling, enabling scalable processing pipelines. The project demonstrates how to overcome Lambda limitations such as execution time and storage constraints. ...

An OS/hardware vendor independent GPU accelerated image and video processing library written in C. Interface allows easy combination and manipulation of customizable filters. Works with an active OpenGL context.