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Updated readme and fixed a gramma error

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mrepetto 2019-10-13 18:01:34 -03:00
parent 27bf6b380b
commit acca344f23
2 changed files with 10 additions and 8 deletions
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16
README.md
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@ -24,6 +24,8 @@ Second, you'll need to create a MySQL database where Dejavu can store fingerprin
Now you're ready to start fingerprinting your audio collection!
Obs: The same from above goes for postgres database if you want to use it.
## Quickstart
```bash
@ -81,7 +83,7 @@ The following keys are mandatory:
The following keys are optional:
* `fingerprint_limit`: allows you to control how many seconds of each audio file to fingerprint. Leaving out this key, or alternatively using `-1` and `None` will cause Dejavu to fingerprint the entire audio file. Default value is `None`.
* `database_type`: as of now, only `mysql` (the default value) is supported. If you'd like to subclass `Database` and add another, please fork and send a pull request!
* `database_type`: `mysql` (the default value) and `postgres` are supported. If you'd like to add another subclass for `BaseDatabase` and implement a new type of database, please fork and send a pull request!
An example configuration is as follows:
@ -102,16 +104,16 @@ An example configuration is as follows:
## Tuning
Inside `fingerprint.py`, you may want to adjust following parameters (some values are given below).
Inside `config/settings.py`, you may want to adjust following parameters (some values are given below).
FINGERPRINT_REDUCTION = 30
PEAK_SORT = False
DEFAULT_OVERLAP_RATIO = 0.4
DEFAULT_FAN_VALUE = 10
DEFAULT_AMP_MIN = 15
PEAK_NEIGHBORHOOD_SIZE = 30
DEFAULT_FAN_VALUE = 5
DEFAULT_AMP_MIN = 10
PEAK_NEIGHBORHOOD_SIZE = 10
These parameters are described in the `fingerprint.py` in detail. Read that in-order to understand the impact of changing these values.
These parameters are described within the file in detail. Read that in-order to understand the impact of changing these values.
## Recognizing
@ -123,7 +125,7 @@ Through the terminal:
```bash
$ python dejavu.py --recognize file sometrack.wav
{'song_id': 1, 'song_name': 'Taylor Swift - Shake It Off', 'confidence': 3948, 'offset_seconds': 30.00018, 'match_time': 0.7159781455993652, 'offset': 646L}
{'total_time': 2.863781690597534, 'fingerprint_time': 2.4306554794311523, 'query_time': 0.4067542552947998, 'align_time': 0.007731199264526367, 'results': [{'song_id': 1, 'song_name': 'Taylor Swift - Shake It Off', 'input_total_hashes': 76168, 'fingerprinted_hashes_in_db': 4919, 'hashes_matched_in_input': 794, 'input_confidence': 0.01, 'fingerprinted_confidence': 0.16, 'offset': -924, 'offset_seconds': -30.00018, 'file_sha1': b'3DC269DF7B8DB9B30D2604DA80783155912593E8'}, {...}, ...]}
```
or in scripting, assuming you've already instantiated a Dejavu object:

2
dejavu/__init__.py
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@ -121,7 +121,7 @@ class Dejavu:
def fingerprint_file(self, file_path: str, song_name: str = None) -> None:
"""
Given a path to a file the method generates hashes for it and stores them in the database
for later being queried.
for later be queried.
:param file_path: path to the file.
:param song_name: song name associated to the audio file.