Comments (6)
It's frames, which are 256/sr, or ~23 ms at 11 kHz. Thus, the time alias
window is about 6 minutes by default; durations beyond this can still be
matched, but the reported offsets will be modulo 380 seconds.
DAn.
On Tuesday, June 9, 2015, apiszcz [email protected] wrote:
Does -- maxtime parameter represent the number of samples or seconds?
—
Reply to this email directly or view it on GitHub
#8.
from audfprint.
Thank you, and another easy question. At 8KHZ my maxtime will be
.032*16384 or 524.288 seconds. That works out good for my case.
Since all my data is 8KHZ mono, do I need to resample to 8KHZ? or am 'OK' I
without specifying the --resample flag 8000?, I noted the resample option
mentions a default of 11KHZ.
Thank you.
On Tue, Jun 9, 2015 at 11:37 AM, Dan Ellis [email protected] wrote:
It's frames, which are 256/sr, or ~23 ms at 11 kHz. Thus, the time alias
window is about 6 minutes by default; durations beyond this can still be
matched, but the reported offsets will be modulo 380 seconds.DAn.
On Tuesday, June 9, 2015, apiszcz [email protected] wrote:
Does -- maxtime parameter represent the number of samples or seconds?
—
Reply to this email directly or view it on GitHub
#8.—
Reply to this email directly or view it on GitHub
#8 (comment).
from audfprint.
You should specify --resample 8000 to prevent the data from being
resampled. Yeah, maybe not the most intuitive option name.
DAn.
On Tue, Jun 9, 2015 at 3:19 PM, apiszcz [email protected] wrote:
Thank you, and another easy question. At 8KHZ my maxtime will be
.032*16384 or 524.288 seconds. That works out good for my case.Since all my data is 8KHZ mono, do I need to resample to 8KHZ? or am 'OK' I
without specifying the --resample flag 8000?, I noted the resample option
mentions a default of 11KHZ.Thank you.
On Tue, Jun 9, 2015 at 11:37 AM, Dan Ellis [email protected]
wrote:It's frames, which are 256/sr, or ~23 ms at 11 kHz. Thus, the time alias
window is about 6 minutes by default; durations beyond this can still be
matched, but the reported offsets will be modulo 380 seconds.DAn.
On Tuesday, June 9, 2015, apiszcz [email protected] wrote:
Does -- maxtime parameter represent the number of samples or seconds?
—
Reply to this email directly or view it on GitHub
#8.—
Reply to this email directly or view it on GitHub
#8 (comment).—
Reply to this email directly or view it on GitHub
#8 (comment).
from audfprint.
Thanks, I really like all the parameters you expose, now to understand them
with my use case.
I need to test -I and more of the capabilities. I'm interested in any
tidbits like: http://www.ee.columbia.edu/~dpwe/resources/matlab/audfprint/
On Tue, Jun 9, 2015 at 3:43 PM, Dan Ellis [email protected] wrote:
You should specify --resample 8000 to prevent the data from being
resampled. Yeah, maybe not the most intuitive option name.DAn.
On Tue, Jun 9, 2015 at 3:19 PM, apiszcz [email protected] wrote:
Thank you, and another easy question. At 8KHZ my maxtime will be
.032*16384 or 524.288 seconds. That works out good for my case.Since all my data is 8KHZ mono, do I need to resample to 8KHZ? or am
'OK' I
without specifying the --resample flag 8000?, I noted the resample option
mentions a default of 11KHZ.Thank you.
On Tue, Jun 9, 2015 at 11:37 AM, Dan Ellis [email protected]
wrote:It's frames, which are 256/sr, or ~23 ms at 11 kHz. Thus, the time
alias
window is about 6 minutes by default; durations beyond this can still
be
matched, but the reported offsets will be modulo 380 seconds.DAn.
On Tuesday, June 9, 2015, apiszcz [email protected] wrote:
Does -- maxtime parameter represent the number of samples or seconds?
—
Reply to this email directly or view it on GitHub
#8.—
Reply to this email directly or view it on GitHub
#8 (comment).—
Reply to this email directly or view it on GitHub
#8 (comment).—
Reply to this email directly or view it on GitHub
#8 (comment).
from audfprint.
To explain: This Python codebase has the same name as the Matlab code you link to, and in fact the Python code will attempt to read databases written by Matlab, and they may work. I did the original implementation in Matlab and spent several years enhancing that version, but then I chose to start from scratch with a Python version to make it smaller, cleaner, and easier for everyone to use. Only the core functionality was supported in the original Python version, although I'm gradually adding things. The reporting of time support that I recently added in Python was something I never got around to in the Matlab.
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Understand, Moving/porting from MATLAB takes considerable energy for some applications. Maybe Mathworks will create a Python export capability.
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Related Issues (20)
- Incorrect time range HOT 1
- Incorrect Time range. HOT 1
- Convert .afpk files to mp3? HOT 1
- Problem with "spreadpeaksinvector"
- Reduce memory usage HOT 2
- Use audfprint as a module
- How to increase bits for storing IDs and timestamp?
- illustrate
- Scan every folder in every fingerprint base named as folder HOT 3
- UNICODE chaaracters ERROR HOT 11
- Show more than 1 finded matched names in results. HOT 4
- Can this algorithm load the historical features into memory first, so that the matching speed is improved, but I don't know how to modify your basic code HOT 7
- Hello, if the song is 1 million (the duration of the song is about 3 minutes), the matching time is very slow, how to optimize it? HOT 1
- I found that according to The time and hash generated by audfprint are not continuous in time, which led me to use the binary method to search for the same hash, conduct a statistical ranking of the number of hashes, and search for the original version of individual audio (the climax audio), and the ranking is not the first.
- I found that some match matches are inaccurate. I want to know, is the time and hash generated by this audfprint continuous at the start-end time, or is it a peak value, which leads to the fact that if one song is 1 minute, another song 3 minutes, there are a lot of hashes in the previous minute in the last two minutes of the next song, which leads to the fact that the hash statistics are larger than one minute, resulting in inaccurate sorting, then the match situation is inaccurate, how to optimize this? HOT 2
- output matching different between windows and linux. I created a database of filehashes which is around 340MB. When i try to query around 100 mp3 files my output is different between my windows machine and my raspberri pi. The database is identical, the query is identical but the windows machine finds significantly more matches. Both are running python 3.9. Database was created on the windows machine and transfered to the pi. Anyone encountered something similar? HOT 7
- Question about concatenate afpk files HOT 2
- How to avoid big % Dropped HOT 5
- Can someone take on audfprint-gui for audfprint or create a new gui for it? HOT 2
- Ability to split pklzs into smaller sizes
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