Search Results for "maps"

...It processes video files alongside GPX or FIT data to render dashboards displaying metrics such as speed, distance, and location directly onto footage. The system supports a wide range of layouts, including maps, gauges, and charts, which can be customized through configuration files. It integrates FFmpeg for rendering and supports multiple resolutions and camera modes such as timelapse and timewarp. The tool can also convert metadata into formats like GPX or CSV for further analysis. It is designed for both post-processing workflows and automated video generation pipelines. ...

This project is no longer active. It has been replaced by mrv2 at: www.sourceforge.net/p/mrv2 A video player, interactive image viewer, and flipbook for use in VFX, 3D computer graphics and professional illustration.

...An example of a processed texture is shown in the following image (parameters used: scaling-factor = 4 and deblur iterations = 4) besides upscaling and debluring the utility also generates normal maps for each texture. This is implemented using the DeepBump by HugoTiny model. Examples of normal maps are shown in the following images.

video-to-ascii is a Python-based command-line tool that converts and plays video files directly in the terminal using ASCII characters as visual representations. It processes each frame of a video, maps pixel brightness and color values to characters, and renders them in real time within terminal constraints. The tool adapts video resolution to match terminal dimensions, ensuring a coherent and readable output despite limited character space. It can optionally include audio playback when additional dependencies such as FFmpeg and PortAudio are installed. ...

...The system builds upon traditional structure-from-motion (SfM) techniques to provide geometric constraints while integrating a convolutional neural network trained for single-image depth estimation. During inference, the model fine-tunes itself to align with the geometric constraints of a specific input video, ensuring stable and realistic depth maps even in less-constrained regions. This approach achieves improved geometric consistency and visual stability compared to prior monocular reconstruction methods. The project can process challenging hand-held video footage, including those with moderate dynamic motion, making it practical for real-world usage.