Comments (6)
@suxianbaozi can you provide some information / graphs for you experiments with large sets of mp3 files? I'd be very interested to see the rates of hashes used.
from dejavu.
Ok I'll try
from dejavu.
Currently,I used this for radio song recognize ,the radio stream is HLS with many 10 seconds TS(AAC) file blocks,every 5 seconds ,I'll take one for recognizing . because of the song library was big,I have change song fingerprint algorithm to short the number of hash。
In "generate_hashes" method of fingerprint.py,I changed the peaks(list) to time-frequence(list) and sort it , every time I'll take one frequence(list) to make len(freqs[i]) * len(freqs[i + 1]) + len(freqs[i]) * len(freqs[i + 2]) number of hashes,
and it works good. I don't know if it works for other recognize such as microphone. or some sound with noise.
hope you can read it!
Now I have 2000 songs in my database ,with about 20,000,000 number of hashes.
One 10 seconds TS(ACC) file with about 250 hashes that will affect about 5000 hashes in database,and the confidence is 30-200 as common,and which would take about 3 seconds of time
CPU:Intel(R) Xeon(R) CPU E5-2430 0 @ 2.20GHz
MEMERY:8G
OS: Ubuntu 12.04
from dejavu.
Very cool! Is that change to the code in your personal branch? I'm not quite understanding from your description.
But yes, it stands to reason that different settings for microphone recognition and file recognition (with regards to memory and accuracy) have different settings that are optimal. Glad to see the project is of use to you!
from dejavu.
Thanks for your project,
I think it will take more convenience to more people
I make a mistake pullrequest and I don't how to delete it - -!
from dejavu.
https://github.com/suxianbaozi/dejavu/blob/master/dejavu/fingerprint.py
you can find the change of generate_hashes method
from dejavu.
Related Issues (20)
- Which field in the results indicates the best match with the original song HOT 3
- run_tests.py: error: the following arguments are required src HOT 4
- Trying to fingerprint about 200 000 files. After 15000 files INSERT operation is very slow. HOT 1
- Do maximum_filter with cupy instead of scipy
- Failed to solve HOT 1
- Comparing short audio files
- Python Docker image bloated
- A directory of potentially duplicate audio files?
- it works well with python3.6 ~
- Not working for recordings
- Some errors when I use python3.7
- multiple concurrency
- Fingerprinting Audio With Differing Sample Rates HOT 1
- Jscght
- figerprinting file HOT 1
- Any way to generate the result image of the plots? HOT 1
- Does this package supports Python 3 HOT 4
- does this project work well on recognizing human speak? HOT 5
- Problem running the sample project HOT 1
- erors using fingerprint_file HOT 1
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from dejavu.