Datasets:
| annotations_creators: [] | |
| language: [] | |
| language_creators: [] | |
| license: [] | |
| multilinguality: [] | |
| pretty_name: Mel spectrograms of music | |
| size_categories: | |
| - 10K<n<100K | |
| source_datasets: [] | |
| tags: | |
| - audio | |
| - spectrograms | |
| task_categories: | |
| - image-to-image | |
| task_ids: [] | |
| 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 | |
| ``` |