videohash
vidgear
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videohash | vidgear | |
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4 | 14 | |
257 | 3,190 | |
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0.0 | 7.2 | |
4 months ago | 2 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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videohash
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videohash / video fingerprinting Question : Detecting if a small clip is part of a longer movie
Hi all, I try to create a program to detect if a certain video scene (normally within 10 seconds) is within a longer video file. The idea is that if I find an scene on youtube, I want to know from which episodes of a particular TV show (assuming I know which tv show, but no idea which episode), so I want to find it out. Current solution: [a] - Extract Frame using ffmpeg from the reference clip (fps = 1) [b] - Extract Frame using ffmpeg from the longer video file (fps around 0.1 or 0.5) For each frame from [a] , I do a imagehash for [a] and [b] and comparing the hamming distance, get the lowest distance from this round of comparision and move on to the next frame from [a] Eventually I got an average score and I can find out if this TV episode contain the scene I was looking for. However, this is slow and not efficient. I found out that there is a videohash library https://github.com/akamhy/videohash But it said "Videohash cannot be used to verify whether one video is a part of another (video fingerprinting)." Does anybody know why? Is it because it gets a videohash for the whole video? If this is the case, how about I use the video hash lib to create a hash for my reference clip (let's say it is about 10 seconds) and then I create multiple 10-second version of the Longer video, generate a videohash just for it and compared that with my reference clip. Would that work? (Yes I understand that for a 60 minutes movie, that would be like 360 video hash to be calculated)... Do you think this is better? Thanks.
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tips on scraping for porn?
2) Sorting through all the scraped data. This is going to vary depending on your approach. If you want to remove duplicates, there is a library called videohash that will allow you to take the perceptual hash of video files. If 2 videos have the same perceptual hash, they are duplicate.
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Videohash – Perceptual Video Hashing Package
I think it creates a collage of the video frames: https://github.com/akamhy/videohash/blob/8759b6ad7fdabcdf4dd...
and passes that on to the videohash.py module to generate a hash:
- GitHub - akamhy/videohash: Python package for Perceptual Video Hashing - Get a 64-bit comparable hash-value for any video.
vidgear
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Why HTTP/3 is eating the world
My experience that played out over the last few weeks lead me to a similar belief, somewhat. For rather uninteresting reasons I decided I wanted to create mp4 videos of an animation programmatically, from scratch.
The first solution suggested when googling around is to just create all the frames, save them to disk, and then let ffmpeg do its thing from there. I would have just gone with that for a one-off task, but it seems like a pretty bad solution if the video is long, or high res, or both. Plus, what I really wanted was to build something more "scalable/flexible".
Maybe I didn't know the right keywords to search for, but there really didn't seem to be many options for creating frames, piping them straight to an encoder, and writing just the final video file to disk. The only one I found that seemed like it could maybe do it the way I had in mind was VidGear[1] (Python). I had figured that with the popularity of streaming, and video in general on the web, there would be so much more tooling for these sorts of things.
I ended up digging way deeper into this than I had intended, and built myself something on top of Membrane[2] (Elixir)
[1] https://abhitronix.github.io/vidgear/
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Need help to choose toolchain for setting up a video streaming server on my PC.
I've been googling and reading for a while but I'm very unsure about which tools I need, which tools will help me achieve what I want the easiest way. What about (pylivestream)[https://pypi.org/project/pylivestream/] for example? Will this do the job for me? What about a lower level approach including (pyopencv)[https://pypi.org/project/opencv-python/]? What about a higher level approach using (vidgear)[https://github.com/abhiTronix/vidgear], which seems promising but I don't feel confident in assessing if it's the tool I really need?
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Which not so well known Python packages do you like to use on a regular basis and why?
Vidgear and new deffcode library are my best. I bet you don't know none of them. But they're pretty awesome when it comes to video-processing and stuff.
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Deffcode: FFmpeg decoding made easy with python.
Yes, fortunately I already resolved it in my previous(popular) library called vidgearthrough its WriteGear API: https://abhitronix.github.io/vidgear/latest/gears/writegear/compression/overview/
- VidGear Is a High-Performance Video Processing Python Library
- VidGear: Making Video-Processing with Python as easy as pie
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I created VidGear that makes Video-Processing with Python as easy as can be
Code: https://github.com/abhiTronix/vidgear
- VidGear 0.2.3: Video-Processing with Python as easy as can.
- VidGear – A High-Performance Video Processing Python Framework
What are some alternatives?
neuralhash-collisions - A catalog of naturally occurring images whose Apple NeuralHash is identical.
moviepy - Video editing with Python
imgdupes - Identifying and removing near-duplicate images using perceptual hashing.
scikit-video - Video processing routines for SciPy
scala-phash - Image comparison by hash codes
OpenCV - Open Source Computer Vision Library
openshot-qt - OpenShot Video Editor is an award-winning free and open-source video editor for Linux, Mac, and Windows, and is dedicated to delivering high quality video editing and animation solutions to the world.
SaveTube - Youtube-dl GUI Wrapper
emdrive - 💫 Fast similarity search DBMS
opencv-steel-darts - Automatic scoring system for steel darts using OpenCV, a Raspberry Pi 3 Model B and two webcams.
motion-tracking-video-crop - Crop motion tracked video with added smoothing movement
ffmpeg-normalize - Audio Normalization for Python/ffmpeg