GithubHelp home page GithubHelp logo

devicehive / devicehive-audio-analysis Goto Github PK

View Code? Open in Web Editor NEW
195.0 195.0 80.0 60 KB

License: Apache License 2.0

Python 95.55% HTML 4.45%
audio audio-analysis devicehive machine-learning tensorflow youtube-8m

devicehive-audio-analysis's People

Contributors

doberman4ik avatar evantkchong avatar igor-panteleev avatar nikolay-kha avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

devicehive-audio-analysis's Issues

Predictions result array empty - minimum duration?

I'm testing with an 18 second long file WAV and the predictions array is empty - is there a recommended minimum duration? Here is the avprobe output

Input #0, wav, from 'test.wav':
  Metadata:
    encoder         : Lavf56.1.0
  Duration: 00:00:18.25, bitrate: 256 kb/s
    Stream #0.0: Audio: pcm_s16le, 16000 Hz, 1 channels, s16, 256 kb/s

repeating results of audioset paper

  1. Is your result close to what published by the audioset paper? How do you define hit rate? Is it accuracy?
  2. Is the feature you generated using vggish model close to their released feature? It seems very different. 3. They have quantized 8-bit feature and you used floating number feature? Is your model trained with their 8-bit feature?

How to resolve FileNotFoundError: [Errno 2] No such file or directory: 'models/vggish_pca_params.npz'

Hello,

I am getting this error while trying to run the code via command line on Ubuntu. I use the command python3 parse_file.py Recording_5.wav

Here is the Traceback:

Traceback (most recent call last):
File "parse_file.py", line 39, in
process_file(**vars(args))
File "parse_file.py", line 31, in process_file
with WavProcessor() as proc:
File "/home/akshay/devicehive-audio-analysis/audio/processor.py", line 40, in init
pca_params = np.load(params.VGGISH_PCA_PARAMS)
File "/home/akshay/.local/lib/python3.6/site-packages/numpy/lib/npyio.py", line 428, in load
fid = open(os_fspath(file), "rb")
FileNotFoundError: [Errno 2] No such file or directory: 'models/vggish_pca_params.npz'

Can't run project

For both variants (from wav and mic recording) that I try - same error:
Traceback (most recent call last): File "parse_file.py", line 39, in <module> process_file(**vars(args)) File "parse_file.py", line 31, in process_file with WavProcessor() as proc: File "/mnt/Data/project/devicehive-audio-analysis/audio/processor.py", line 45, in __init__ self._init_youtube() File "/mnt/Data/project/devicehive-audio-analysis/audio/processor.py", line 74, in _init_youtube youtube8m.model.load_model(sess, params.YOUTUBE_CHECKPOINT_FILE) File "/mnt/Data/project/devicehive-audio-analysis/audio/utils/youtube8m/model.py", line 43, in load_model set_up_init_ops(tf.get_collection_ref(tf.GraphKeys.LOCAL_VARIABLES)) File "/mnt/Data/project/devicehive-audio-analysis/audio/utils/youtube8m/model.py", line 26, in set_up_init_ops if "train_input" in variable.name: AttributeError: 'str' object has no attribute 'name'
Model was downloaded from your link.

Timing Information

Hi,
First of all, great work! I would like to get exact time information of the previously trained objects rather than the percentage of them. Is it possible if I tweak the current project?

TF record files for training custom new model

Hi @igor-panteleev, great job. I want to train my own model for two or three particular classes. I'm planning the following training pipeline.

128 dim embedding --> a classifier --> classes

Though I've seen the Google Audio set data is provided in 128 dim tf.records, I couldn't find it in a downloadable form in the site. I found a frame by frame tensorflow.SequenceExample file of 2.4 GB. But is that the same data you've used? Please help me on this.

On evaluation, the pipeline will be

WAV format --> VGGish --> 128 dim embedding --> a classifier --> prediction label

Do I miss something?

a pre-trained youtube model

hi, could you share a well pre_trained youtube8m-model? The existing you provided in your project youtube_model.ckpt.data-00000-of-00001 is not very accurate when run the demo server.

Creating own dataset

Good night.

I want to create my own dataset with my own labels. is it possible for this repository?

Thanks

Another dataset

Hello! Great work!

I'm new in audio analysis and tensorflow...

How i change the dataset?

I want to use a offline dataset in my computer(Example: Urbansound). I can train this dataset and use it in place of youtube-8M?

Thanks!

Error during installation

-e git://github.com/devicehive/devicehive-python-webconfig.git@a792db1babcedb5baa68ec6ba6ebcf0041f20469#egg=devicehive_webconfig

release file not available , can you please update the repository with the latest codes

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.