30,000 256x256 mel spectrograms of 5 second samples that have been used in music, sourced from [WhoSampled](https://whosampled.com) and [YouTube](https://youtube.com). 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 = 256
y_res = 256
sample_rate = 22050
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 sampled music", "tags": ["audio", "spectrograms"]}
TAGS
#task_categories-image-to-image #size_categories-10K<n<100K #audio #spectrograms #region-us 

30,000 256x256 mel spectrograms of 5 second samples that have been used in music, sourced from WhoSampled and YouTube. 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 
