Comparison between Frechet Video Distance implementation from StyleGAN-V and the original paper

In this repo, we demonstrate that the FVD implementation from StyleGAN-V paper is equivalent to the original one when the videos are already loaded into memory and resized to a necessary resolution. The main difference of our FVD evaluation protocol from the paper is that we strictly specify how data should be processed, clips sampled, etc. The problem with the original implementation is that it does not handle: data processing: in which format videos are being stored (JPG/PNG directories of […]

Read more

Refine video frame based on nearby frames

Introduction Refine a video frame based on nearby frames. WIP CLI Usage Installation git clone [email protected]:hzwer/ResynNet.git cd ResynNet pip3 install -r requirements.txt Download the pretrained model from here. Unzip and move the pretrained parameters to train_log/* Run python3 inference_img.py –origin example/origin.png –ref example/ref0.png example/ref1.png Sponsor Many thanks to Grisk. 感谢支持 Paypal Sponsor: https://www.paypal.com/paypalme/hzwer GitHub View Github    

Read more

All in One: Exploring Unified Video-Language Pre-training

Code for the paper: All in One: Exploring Unified Video-Language Pre-training Arxiv Install 1. PytorchLighting In this work, we use PytorchLighting for distributed training with mixed precision.Install pytorch and PytorchLighting first. conda create -n allinone python=3.7 source activate allinone conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch cd [Path_To_This_Code] pip install -r requirements.txt 2. On-the-fly decode To speed up the pre-training, we adopt on-the-fly decode for fast IO.Install ffmpeg and pytorchvideo (for data augmentation) as below.

Read more

Video-quality calculates VMAF and (optionally) other video quality metrics

video-quality calculates VMAF and (optionally) other video quality metrics for a distorted video relative to a reference video before outputting them in a csv file and providing a summary. It utilises FFmpeg, FFprobe and VMAF to achieve this. Features Different quality metrics Support for distorted videos that are clips of the reference video Support for distorted videos that are cropped relative to the reference video Limitations Only supports FHD (1080p) video Has a crop feature deigned for the removal of […]

Read more

VRT: A Video Restoration Transformer

Jingyun Liang, Jiezhang Cao, Yuchen Fan, Kai Zhang, Rakesh Ranjan, Yawei Li, Radu Timofte, Luc Van Gool Computer Vision Lab, ETH Zurich & Meta Inc. arxiv|supplementary|pretrained models|visual results This repository is the official PyTorch implementation of “VRT: A Video Restoration Transformer”(arxiv, supp, pretrained models, visual results). VRT ahcieves state-of-the-art performance (up to 2.16dB) in video SR (REDS, Vimeo90K, Vid4 and UDM10) video deblurring (GoPro, DVD and REDS) video denoising (DAVIS and Set8)

Read more

Deepstream python play rtsp h264

deepstream python play rtsp h264 n gstreamer python play rtsp h264 and h265 n common=> deepstream_python_apps=>apps n dstest3_pgie_config.txt : test pgie n deepstream_rtsp_h264.py :play one rtsp h264 n deepstream_rtsps_h264.py :play Multiple rtsp h264 n deepstream_videos_h264.py :play Multiple video h264 n gstreamer_test_h264.py :play one rtsp h264 n gstreamer_test_h265.py :play one rtsp h265 n GitHub View Github    

Read more

Video Stream: an Advanced Telegram Bot that’s allow you to play Video & Music on Telegram Group Video Chat

Video Stream is an Advanced Telegram Bot that’s allow you to play Video & Music on Telegram Group Video Chat 📊 Stats 🧪 Get SESSION_NAME from below: Pyrogram 🎭 Preview ✨ Features Music & Video stream support MultiChat support Playlist & Queue support Skip, Pause, Resume, Stop feature Music & Video downloader feature Inline Search support YouTube direct search support YouTube/Local/Live/m3u8 stream support Inline Search support Control With Button support Volume Control Userbot Auto Join Direct Updater 🛠 Commands: Command […]

Read more

EssentialMC2 Video Understanding

EssentialMC2 is a complete system to solve video understanding tasks including MHRL(representation learning), MECR2(relation reasoning) and MOSL3(openset life-long learning) powered by DAMO AcademyMinD(Machine IntelligenNce of Damo) Lab. Run pip install essmc2. Run python setup.py install. For each specific task, please refer to task specific README.

Read more

Convert lecture videos to slides in one line

About Convert lecture videos to slides in one line. Takes an input of a directory containing your lecture videos and outputs a directory containing .PDF files containing the slides of each lecture. (You can download the videos from Google Drive even if you only have View-Only permissions. Google it) The utility only captures slides when it detects that a slide has changed and does not capture every frame. Thus your pdf will be very close to the actual slides used. […]

Read more
1 2 3