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inference.py

@@ -10,27 +10,12 @@ from model import MusicClassifier, MusicAudioClassifier
 import argparse
 import torch
 import torchaudio
-import deepspeed
 import scipy.signal as signal
 from typing import Dict, List
-from google.cloud import storage
 from dataset_f import FakeMusicCapsDataset
 
 from preprocess import get_segments_from_wav, find_optimal_segment_length
 
-#not for ismir
-
-def download_from_gcs(bucket_name, source_blob_name, destination_file_name):
-    destination_dir = os.path.dirname(destination_file_name)
-    if not os.path.exists(destination_dir):
-        os.makedirs(destination_dir)
-
-    storage_client = storage.Client()
-    bucket = storage_client.bucket(bucket_name)
-    blob = bucket.blob(source_blob_name)
-    blob.download_to_filename(destination_file_name)
-
-
 
 def highpass_filter(y, sr, cutoff=1000, order=5):
     if isinstance(sr, np.ndarray):

preprocess.py

@@ -9,8 +9,6 @@ import argparse
 from tqdm import tqdm
 import shutil
 import concurrent.futures
-from madmom.features.downbeats import DBNDownBeatTrackingProcessor
-from madmom.features.downbeats import RNNDownBeatProcessor
 
 
 def get_segments_from_wav(wav_path, device="cuda"):
@@ -19,12 +17,10 @@ def get_segments_from_wav(wav_path, device="cuda"):
     file2beats = File2Beats(checkpoint_path="final0", device="cuda", dbn=False)
     all_models = ["final0", "final1", "final2", "small0", "small1", "small2","single_final0", "single_final1", "single_final2"]
     beats, downbeats = file2beats(wav_path)
-    if len(downbeats) <1:
-        proc = DBNDownBeatTrackingProcessor(beats_per_bar=[3, 4], fps=100)
-        act = RNNDownBeatProcessor()(wav_path)
-        array = proc(act)  
-        downbeats = array[:, 0]
-        return beats, downbeats#beats는 빈거 맞음 
+    if len(downbeats)==0: # downbeats를 그냥 0 2 4..로 넣어주자. 음악 길이에 맞게
+        waveform, sample_rate = torchaudio.load(wav_path)
+        duration = waveform.size(1) / sample_rate
+        downbeats = np.arange(0, duration, 2)
 
     return beats, downbeats
     #except Exception as e:

requirements.txt

@@ -3,4 +3,5 @@ torch
 tqdm
 imblearn
 transformers
-https://github.com/CPJKU/beat_this/archive/main.zip
+https://github.com/CPJKU/beat_this/archive/main.zip
+pytorch_lightning