update README

mlu_370-gpt-sovits/GPT-SoVITS/tools/cmd-denoise.py

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+import os
+import argparse
+import traceback
+
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+from tqdm import tqdm
+
+path_denoise = "tools/denoise-model/speech_frcrn_ans_cirm_16k"
+path_denoise = path_denoise if os.path.exists(path_denoise) else "damo/speech_frcrn_ans_cirm_16k"
+ans = pipeline(Tasks.acoustic_noise_suppression, model=path_denoise)
+
+
+def execute_denoise(input_folder, output_folder):
+    os.makedirs(output_folder, exist_ok=True)
+    # print(input_folder)
+    # print(list(os.listdir(input_folder).sort()))
+    for name in tqdm(os.listdir(input_folder)):
+        try:
+            ans("%s/%s" % (input_folder, name), output_path="%s/%s" % (output_folder, name))
+        except:
+            traceback.print_exc()
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "-i", "--input_folder", type=str, required=True, help="Path to the folder containing WAV files."
+    )
+    parser.add_argument("-o", "--output_folder", type=str, required=True, help="Output folder to store transcriptions.")
+    parser.add_argument(
+        "-p", "--precision", type=str, default="float16", choices=["float16", "float32"], help="fp16 or fp32"
+    )  # 还没接入
+    cmd = parser.parse_args()
+    execute_denoise(
+        input_folder=cmd.input_folder,
+        output_folder=cmd.output_folder,
+    )