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License: Apache License 2.0
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
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'
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.
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?
hi,dear
I found that you get the features with postprocess, here
if I must postprocess ?
thx
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?
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.
Thank you for sharing such a audio analysis project!I wonder if I can use it on the Windows? Or it's limited in Ubuntu system?
where is the dh_webconfig?
Good night.
I want to create my own dataset with my own labels. is it possible for this repository?
Thanks
how to deploy this application in heroku ?
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!
-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
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