Upload 10 files

ckpts/first_stage.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3ca02a04ccab31b6f658d08857f9eb42b9f866aa8062c13bcbc6da3c241c164e
+size 442697445

ckpts/vae.yaml

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+version: 1.0
+
+params: 
+  monitor: val/rec_loss
+  image_key: fbank
+  subband: 1
+  embed_dim: 8
+  time_shuffle: 1
+  ddconfig: 
+    double_z: True
+    z_channels: 8
+    resolution: 256
+    downsample_time: False
+    in_channels: 1
+    out_ch: 1
+    ch: 128
+    ch_mult: [1, 2, 4]
+    num_res_blocks: 2
+    attn_resolutions: []
+    dropout: 0.0

data/fsd2018/eval.csv

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+subset,folder,file,cls,onset,offset
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data/fsd2018/test.zip

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+oid sha256:a310ede3a4f8ed7246835cc5e775eb8309ce4646b6eee07bd783b4d4486edc5f
+size 1271032225

data/fsd2018/train.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:767c480c13a28f10928e0da58a073f883afa53cbfb62316a376b08fc34e81c49
+size 12515599613

data/fsd2018/train1.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4c54e62c66f312109e3cbed1a3e3d38b9e98128c97dd4f0a71a022ee9e1fce6d
+size 17147486304

data/fsd2018/train2.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:16eec54c3e7769a1569791f5282e8e1de17e236a3b27c0825bfede5e1e8c4795
+size 10873535070

data/fsd2018/val.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:52dc4ddfc6662cd6527c8e32d0b09cfe8bcc1a9133e49bd9d79e886d26bf7ade
+size 1275808263

data/resample.py

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+import librosa
+import soundfile as sf
+import os
+import concurrent.futures
+
+
+def resample_audio(file_path, target_directory, target_sr=24000):
+    # Load the audio file
+    audio, sr = librosa.load(file_path, sr=None)
+    # Resample the audio
+    if sr != target_sr:
+        audio_resampled = librosa.resample(audio, orig_sr=sr, target_sr=target_sr)
+        # Determine the new file path
+        target_file_path = os.path.join(target_directory, os.path.basename(file_path))
+        # Export the resampled audio
+        sf.write(target_file_path, audio_resampled, target_sr)
+
+
+def resample_audio_multithreaded(source_folder, target_folder, target_sr=24000):
+    if not os.path.exists(target_folder):
+        os.makedirs(target_folder)
+
+    # Create a list of tasks
+    tasks = []
+    for root, dirs, files in os.walk(source_folder):
+        for file in files:
+            if file.endswith(".wav"):
+                source_file_path = os.path.join(root, file)
+                relative_path = os.path.relpath(root, source_folder)
+                target_directory = os.path.join(target_folder, relative_path)
+                if not os.path.exists(target_directory):
+                    os.makedirs(target_directory)
+
+                tasks.append((source_file_path, target_directory))
+
+    # Process the tasks in parallel using multiple threads
+    with concurrent.futures.ThreadPoolExecutor() as executor:
+        futures = [executor.submit(resample_audio, task[0], task[1], target_sr) for task in tasks]
+        concurrent.futures.wait(futures)
+
+
+if __name__ == '__main__':
+    # Example usage
+    resample_audio_multithreaded("fsd2018", 'fsd2018_24k')
+
+    # Note: The actual execution of this code is not possible here due to the lack of access to the user's filesystem.
+    # The user should run this script on their local machine.