From 02b15b312d5c5c8c5614aa0cdb9a0191b75755cb Mon Sep 17 00:00:00 2001
From: Paul Best <paul.best@lis-lab.fr>
Date: Fri, 26 May 2023 10:52:19 +0200
Subject: [PATCH] Update file compute_embeddings.py
---
new_specie/compute_embeddings.py | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/new_specie/compute_embeddings.py b/new_specie/compute_embeddings.py
index 512554b..696b735 100755
--- a/new_specie/compute_embeddings.py
+++ b/new_specie/compute_embeddings.py
@@ -7,7 +7,7 @@ import argparse
torch.multiprocessing.set_sharing_strategy('file_system')
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter, description="Compute the auto-encoder embeddings of vocalizations once it was trained with train_AE.py")
-parser.add_argument('modelname', type=str, help='Filename of the AE weights (.stdc)')
+parser.add_argument('modelname', type=str, help='Filename of the AE weights (.stdc or .weights)')
parser.add_argument("detections", type=str, help=".csv file with detections to be encoded. Columns filename (path of the soundfile) and pos (center of the detection in seconds) are needed")
parser.add_argument("-audio_folder", type=str, default='./', help="Folder from which to load sound files")
parser.add_argument("-NFFT", type=int, default=1024, help="FFT size for the spectrogram computation")
@@ -38,4 +38,4 @@ encodings = np.stack(encodings)
print('Computing UMAP projections...')
X = umap.UMAP(n_jobs=-1).fit_transform(encodings)
-np.save('encodings_'+args.modelname[:-4]+'npy', {'encodings':encodings, 'idx':idxs, 'umap':X})
+np.save(f'encodings_{args.detections[:-4]}_{args.modelname.split('.')[0]}.npy', {'encodings':encodings, 'idx':idxs, 'umap':X})
--
GitLab