Search Results for "frame" - Page 4
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Showing 123 open source projects for "frame"
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1
mgnsVideoTranscoder
mgnsVideoTranscoder is a tool that allows to transcode video file
Full documentation is provided in docs\index.html inside archive file. -
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CCTV Frame Timestamp Extractor
CCTV Footage Timestamp Search Tool
Python script to address the problem of manually locating required event timestamps from carved CCTV DVR footages. Full details can be found in the paper published in Eighteenth Annual IFIP WG 11.9 International Conference on Digital Forensics. Link to paper: https://link.springer.com/chapter/10.1007/978-3-031-10078-9_8 The project has been divided into four modules: Framextract.py- Extracts frames from video footages Reconstruct.py- Attempts to repair unplayable video by extracting... -
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VSGAN
VapourSynth Single Image Super-Resolution Generative Adversarial
...The Network will be applied in quadrants of the image to reduce up-front VRAM usage. You can use any RGB video input, including float32 (e.g., RGBS) inputs. Using VapourSynth you can pass a Video directly to VSGAN, without any frame extraction needed. Any edit you make in the VapourSynth script with or without VSGAN can be re-used for any other video. VSGAN is released under the MIT License, ensuring it will stay free, with the ability to be used commercially. -
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Robust Video Matting (RVM)
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX
...Our method is much lighter than previous approaches and can process 4K at 76 FPS and HD at 104 FPS on an Nvidia GTX 1080Ti GPU. Unlike most existing methods that perform video matting frame-by-frame as independent images, our method uses a recurrent architecture to exploit temporal information in videos and achieves significant improvements in temporal coherence and matting quality. Furthermore, we propose a novel training strategy that enforces our network on both matting and segmentation objectives. This significantly improves our model's robustness. ... -
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VidCutter
A modern yet simple multi-platform video cutter and joiner
A modern, simple to use, constantly evolving and hella fast MEDIA CUTTER + JOINER w/ frame-accurate SmartCut technology, chapter support, media stream selection for audio + subtitle channels and blackdetect video filter support to automatically detect scene changes or skip commercials in digital TV recordings. Chapter support allows scene chapter names to be included in final media metadata. NOTE: results will only work in media players that support chapters. -
6
Transformer TTS
Implementation of a Transformer based neural network
...It takes inspiration from architectures like FastSpeech, FastSpeech 2, FastPitch, and Transformer TTS, and extends them with its own aligner and forward models. The system separates alignment learning and acoustic modeling: an autoregressive Transformer is used as an aligner to extract phoneme-to-frame durations, while a non-autoregressive “ForwardTransformer” generates mel-spectrograms conditioned on text and durations. This design addresses common autoregressive issues such as repetition, skipped words, and unstable attention, and results in robust, fast synthesis where all frames are predicted in parallel. The repository ships with tooling to build datasets (especially LJSpeech) and create training data, plus scripts to train both the aligner and the TTS model, monitor training with TensorBoard, and resume or reset training runs. -
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VidCutter
the simplest & fastest video cutter & joiner
A modern, simple to use, constantly evolving and hella fast MEDIA CUTTER + JOINER w/ frame-accurate SmartCut technology + Qt5, libmpv, FFmpeg and MediaInfo powering the backend. -
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Pydub
Manipulate audio with a simple and easy high level interface
...For opening and saving non-wav files, like mp3, you'll need ffmpeg or libav. Any operations that combine multiple AudioSegment objects in any way will first ensure that they have the same number of channels, frame rate, sample rate, bit depth, etc. -
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video-to-ascii
It is a simple python package to play videos in the terminal
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. ... -
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BasicSR
Winning Solution in NTIRE19 Challenges on Video Restoration
...The architecture includes bespoke modules (e.g., Pyramid, Cascading and Deformable alignment and Temporal Spatial Attention fusion) that align information across frames and emphasize important features for restoration, enabling state-of-the-art performance on benchmarks such as the REDS challenge. By fusing spatial and temporal context, EDVR produces significantly improved visual quality in restored videos compared with approaches that treat each frame independently. -
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PaddlePaddle models
Pre-trained and Reproduced Deep Learning Models
Pre-trained and Reproduced Deep Learning Models ("Flying Paddle" official model library, including a variety of academic frontier and industrial scene verification of deep learning models) Flying Paddle's industrial-level model library includes a large number of mainstream models that have been polished by industrial practice for a long time and models that have won championships in international competitions; it provides many scenarios for semantic understanding, image classification,... -
12
Deep Exemplar-based Video Colorization
The source code of CVPR 2019 paper "Deep Exemplar-based Colorization"
...To address this issue, we introduce a recurrent framework that unifies the semantic correspondence and color propagation steps. Both steps allow a provided reference image to guide the colorization of every frame, thus reducing accumulated propagation errors. Video frames are colorized in sequence based on the colorization history, and its coherency is further enforced by the temporal consistency loss. All of these components, learned end-to-end, help produce realistic videos with good temporal stability. Experiments show our result is superior to the state-of-the-art methods both quantitatively and qualitatively. ... -
13
Bulk LUTs Previewer 2.8.4
Generate a preview gallery for your LUTs.
Quickly generate a gallery to preview your (Look Up Tables) luts on selected still frame, or video. 1) Import a still image. (jpg, jpeg, png, bmp) *) (Or select video. (mpg, mpeg, mp4, mov, mts, avi, webm, mkv)) 2) Choose path to your lutsfolder. (cube, 3dl, dat, m3d) 3) Generate. (If video selected, use scroll wheel to preview luts) All preview images that is generated is stored in '.\OUT' folder, and then deleted upon restart of the application -
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LiVES
LiVES is a Video Editing System. It is designed to be simple to use, y
...For the more technically minded, the application is frame and sample accurate, and it can be controlled remotely or scripted for use as a video server. And it supports all of the latest free standards. -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
16
YouTube-8M
Starter code for working with the YouTube-8M dataset
...The code demonstrates how to process frame-level features, train logistic and deep learning models, evaluate them using metrics like global Average Precision (gAP) and mean Average Precision (mAP), and export trained models for MediaPipe inference. -
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WebExKit
An HTML/CSS/JavaScript editor with preview window
The Web Experimentation Kit allows you to enter HTML, CSS and JavaScript and see the results immediately in a browser frame side-by-side with the editor. If you've seen the W3Schools Tryit Editor, JSFiddle or CodePen then this should be familiar to you. The difference between WebExKit and these other applications is that WebExKit is a stand-alone application that runs on your desktop and it allows you to save (and reload) files to your own disk drive. -
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GIF for CLI
Takes in a GIF, short video, or a query to the Tenor GIF API
...It’s useful for quick visual feedback, lightweight demos, or just adding some personality to scripts and readmes. Despite its whimsical nature, the project is a tight example of frame decoding, timing, and terminal rendering glued together in a single command. -
19
Green Recorder
A simple screen recorder for Linux desktop
...The application allows users to record full screens or specific areas, making it suitable for tutorials and demonstrations. It includes options for selecting audio sources and controlling frame rates to balance quality and performance. green-recorder is designed to be lightweight and user-friendly, minimizing system overhead during recording sessions. It also supports Wayland and Xorg environments, ensuring compatibility across different Linux setups. Overall, it offers an accessible solution for screen recording with essential customization options. -
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DetectAndTrack
The implementation of an algorithm presented in the CVPR18 paper
DetectAndTrack is the reference implementation for the CVPR 2018 paper “Detect-and-Track: Efficient Pose Estimation in Videos,” focusing on human keypoint detection and tracking across video frames. The system combines per-frame pose detection with a tracking mechanism to maintain identities over time, enabling efficient multi-person pose estimation in video. Code and instructions are organized to replicate paper results and to serve as a starting point for researchers working on pose in video. Although the repo has been archived and is now read-only, its issue tracker and artifacts remain useful for understanding implementation details and experimental settings. ... -
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Video Nonlocal Net
Non-local Neural Networks for Video Classification
video-nonlocal-net implements Non-local Neural Networks for video understanding, adding long-range dependency modeling to 2D/3D ConvNet backbones. 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. ... -
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darc
Durham Adaptive-optics Real-time Controller
darc, the Durham Adaptive optics Real-time Controller. For documentation or darctalk client only, select "View all files". For the latest bleeding-edge version, please use: git clone git://git.code.sf.net/p/darc2/code darc (no password required) (this changed May 2013 due to a sourceforge update). If you use darc, please cite with: Basden, A and Myers, R, MNRAS Vol 242, page 1483, 2012 -
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MysticBBS Shoutcast Panel
Python Script for Mystic BBS Shoutcast Dashboard
... - Contains simple code to grab XML/RSS feed and display on the BBS. - Contains various functions to make it easy to display information in a correctly sized mystic bbs text based frame including titles and prompts. This script can be a skeleton to get you going in writing your own properly fit modular text based python apps for Mystic BBS. -
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Five video classification methods
Code that accompanies my blog post outlining five video classification
...This reduces model complexity, training time, and a whole whack load of hyperparameters we don’t have to worry about. Every video will be subsampled down to 40 frames. So a 41-frame video and a 500-frame video will both be reduced to 40 frames, with the 500-frame video essentially being fast-forwarded. We won’t do much preprocessing. A common preprocessing step for video classification is subtracting the mean, but we’ll keep the frames pretty raw from start to finish. -
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Lip Reading
Cross Audio-Visual Recognition using 3D Architectures
The input pipeline must be prepared by the users. This code is aimed to provide the implementation for Coupled 3D Convolutional Neural Networks for audio-visual matching. Lip-reading can be a specific application for this work. Audio-visual recognition (AVR) has been considered as a solution for speech recognition tasks when the audio is corrupted, as well as a visual recognition method used for speaker verification in multi-speaker scenarios. The approach of AVR systems is to leverage the...
