jensenn / videohash Goto Github PK

Videohash is a Python package for detecting near-duplicate videos (Perceptual Video Hashing). It can take any input video and generate a 64-bit equivalent hash value. Videohash is way more faster than comparing the imagehash values of individual frames of the video and more reliable than hashing keyframes.

The video-hash-values for identical or near-duplicate videos are the same or similar, implying that if the video is resized (upscaled/downscaled), transcoded, watermark added/removed, stabilized, color changed, frame rate changed, changed aspect ratio, cropped, black-bars added or removed, the hash-value should remain unchanged or not vary substantially.

• In layman's terms : Every one second, a frame from the input video is extracted, the frames are shrunk to a 144x144 pixel square, a collage is constructed that contains all of the resized frames(square-shaped), the collage's wavelet hash is the video hash value for the original input video.

• Videohash cannot be used to verify whether one video is a part of another (video fingerprinting). If the video is reversed or rotated by a substantial angle (greater than 10 degrees), Videohash will not provide the same or similar hash result, but you can always reverse the video manually and generate the hash value for reversed video.

• Read Hamming Distance / Similarity searches in a database - Stack Overflow (Archive link)

To use this software, you must have FFmpeg installed. Please read how to install FFmpeg if you don't already know how.

Upgrade pip

python3 -m pip install --upgrade pip

If you do not want to upgrade pip and the installation fails try appending --prefer-binary to the following installation command(s).

• Install from the PyPi (recommended):

pip install videohash

• Install directly from the GitHub repository (NOT recommended):

pip install git+https://github.com/akamhy/videohash.git

• It is fast!
• Generate videohash of a video directly from its URL(uses yt-dlp) or its path.
• Can be used as the core of a scalable Near Duplicate Video Retrieval (NDVR) system.
• The end-user can access the image representation(the collage) of the video.
• A videohash instance can be compared to a 64-bit stored hash, its hex representation, bitlist, and other videohash instances.

In the following usage example the first three instance of VideoHash class are computing the hash for the same video(not same as in checksum) and the last one is a different video.

• videohash1 is the video at https://www.youtube.com/watch?v=PapBjpzRhnA.

• videohash2 is downscaled copy of https://www.youtube.com/watch?v=PapBjpzRhnA contained in Matroska Multimedia Container.

• videohash3 is the same video as videohash2 but on local storage.

• videohash4 uses a completely different video at https://www.youtube.com/watch?v=_T8cn2J13-4.

>>> from videohash import VideoHash
>>> # video: Artemis I Hot Fire Test
>>> url1 = "https://www.youtube.com/watch?v=PapBjpzRhnA"
>>> videohash1 = VideoHash(url=url1)
>>>
>>> videohash1.hash # video hash value of the file, value is same as str(videohash1)
'0b0011010000011111111011111111111110001111011110000000000000000000'
>>>
>>> #VIDEO:Artemis I Hot Fire Test
>>> url2="https://raw.githubusercontent.com/akamhy/videohash/main/assets/rocket.mkv"
>>> videohash2 = VideoHash(url=url2)
>>> videohash2.hash
'0b0011010000011111111011111111111110001111011110000000000000000000'
>>> videohash2.hash_hex
'0x341fefff8f780000'
>>> videohash2.hash_hex
'0x341fefff8f780000'
>>> videohash1 - videohash2
0
>>> videohash1 == videohash2
True
>>> videohash1 == "0b0011010000011111111011111111111110001111011110000000000000000000"
True
>>> videohash1 != videohash2
False
>>> path3 = "/home/akamhy/Downloads/rocket.mkv" #VIDEO: Artemis I Hot Fire Test
>>> videohash3 = VideoHash(path=path3)
>>> videohash3.hash
'0b0011010000011111111011111111111110001111011110000000000000000000'
>>> videohash3 - videohash2
0
>>> videohash3 == videohash1
True
>>> url4 = "https://www.youtube.com/watch?v=_T8cn2J13-4" #VIDEO: How We Are Going to the Moon
>>> videohash4 = VideoHash(url=url4)
>>> videohash4.hash_hex
'0x7cffff000000eff0'
>>> videohash4 - "0x7cffff000000eff0"
0
>>> videohash4.hash
'0b0111110011111111111111110000000000000000000000001110111111110000'
>>> videohash4 - videohash2
34
>>> videohash4 != videohash2
True

_{Run the above code @ https://replit.com/@akamhy/videohash-usage-2xx-example-code-for-video-hashing#main.py}

Extended Usage : https://github.com/akamhy/videohash/wiki/Extended-Usage

API Reference : https://github.com/akamhy/videohash/wiki/API-Reference

• JohannesBuchner and bunchesofdonald for imagehash.
• Dmitry Petrov for implementing discrete wavelet transform (DWT) based image hashing in Python.
• FFmpeg developers.
• Eddievin for README design.
• iconolocode for the videohash logo.

Copyright (c) 2021 Akash Mahanty. See license for details.

The VideoHash logo was created by iconolocode. See license for details.

Videos are from NASA and are in the public domain.

NASA copyright policy states that "NASA material is not protected by copyright unless noted".