| """ |
| Copyright (c) : Calixte Mayoraz 2024 |
| https://gitlab.com/calixtemayoraz |
| |
| |
| This is an example showing how to get predictions from the model |
| """ |
| from src import MusicSquidModel |
| from scipy.spatial.distance import cosine, euclidean |
|
|
|
|
| if __name__ == '__main__': |
| |
| file_1 = "" |
| file_2 = "" |
| file_3 = "" |
|
|
| msm = MusicSquidModel() |
| emb_1 = msm.embed(file_1) |
| emb_2 = msm.embed(file_2) |
| emb_3 = msm.embed(file_3) |
|
|
| print(f"Cosine Distance between 1 and 2: {cosine(emb_1, emb_2)}") |
| print(f"Cosine Distance between 1 and 3: {cosine(emb_1, emb_3)}") |
| print(f"Cosine Distance between 2 and 3: {cosine(emb_2, emb_3)}") |
| print("---") |
| print(f"Euclidean Distance between 1 and 2: {euclidean(emb_1, emb_2)}") |
| print(f"Euclidean Distance between 1 and 3: {euclidean(emb_1, emb_3)}") |
| print(f"Euclidean Distance between 2 and 3: {euclidean(emb_2, emb_3)}") |
|
|
