fix

data_utils.py

@@ -54,7 +54,7 @@ def get_audio(self, filename):
             spec = torch.squeeze(spec, 0)
             torch.save(spec, spec_filename)
 
-        spk = filename.split("/")[-2]
+        spk = filename.replace("\\", "/").split("/")[-2]
         spk = torch.LongTensor([self.spk_map[spk]])
 
         c = torch.load(filename + ".soft.pt").squeeze(0)

inference/infer_tool.py

@@ -32,7 +32,7 @@ def read_temp(file_name):
                 data = f.read()
             data_dict = json.loads(data)
             if os.path.getsize(file_name) > 50 * 1024 * 1024:
-                f_name = file_name.split("/")[-1]
+                f_name = file_name.replace("\\", "/").split("/")[-1]
                 print(f"clean {f_name}")
                 for wav_hash in list(data_dict.keys()):
                     if int(time.time()) - int(data_dict[wav_hash]["time"]) > 14 * 24 * 3600:

resample.py

@@ -10,7 +10,7 @@
 def process(item):
     spkdir, wav_name, args = item
     # speaker 's5', 'p280', 'p315' are excluded,
-    speaker = spkdir.split("/")[-1]
+    speaker = spkdir.replace("\\", "/").split("/")[-1]
     wav_path = os.path.join(args.in_dir, speaker, wav_name)
     if os.path.exists(wav_path) and '.wav' in wav_path:
         os.makedirs(os.path.join(args.out_dir2, speaker), exist_ok=True)