Over 20,000 256x256 mel spectrograms of 5 second samples of music from my Spotify liked playlist. The code to convert from audio to spectrogram and vice versa can be found in https://github.com/teticio/audio-diffusion along with scripts to train and run inference using De-noising Diffusion Probabilistic Models.
```
x_res = 1024
y_res = 1024
sample_rate = 44100
n_fft = 2048
hop_length = 512
```
task_categories:image-to-image size_categories:10K<n<100K audio spectrograms region:us
{"annotations_creators": [], "language_creators": [], "language": [], "license": [], "multilinguality": [], "size_categories": ["10K<n<100K"], "source_datasets": [], "task_categories": ["image-to-image"], "task_ids": [], "pretty_name": "Mel spectrograms of music", "tags": ["audio", "spectrograms"]}
TAGS
#task_categories-image-to-image #size_categories-10K<n<100K #audio #spectrograms #region-us 

Over 20,000 256x256 mel spectrograms of 5 second samples of music from my Spotify liked playlist. The code to convert from audio to spectrogram and vice versa can be found in URL along with scripts to train and run inference using De-noising Diffusion Probabilistic Models.

TAGS
#task_categories-image-to-image #size_categories-10K<n<100K #audio #spectrograms #region-us 

passage: TAGS
#task_categories-image-to-image #size_categories-10K<n<100K #audio #spectrograms #region-us 
