Add files via upload

extract_f0_print.py

@@ -74,6 +74,15 @@ class FeatureInput(object):
                 frame_period=1000 * self.hop / self.fs,
             )
             f0 = pyworld.stonemask(x.astype(np.double), f0, t, self.fs)
+        elif f0_method == "rmvpe":
+            if hasattr(self, "model_rmvpe") == False:
+                from lib.rmvpe import RMVPE
+
+                print("loading rmvpe model")
+                self.model_rmvpe = RMVPE(
+                    "rmvpe.pt", is_half=False, device="cpu"
+                )
+            f0 = self.model_rmvpe.infer_from_audio(x, thred=0.03)
         return f0
 
     def coarse_f0(self, f0):

extract_f0_rmvpe.py

@@ -0,0 +1,135 @@
+import os, traceback, sys, parselmouth
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+from lib.audio import load_audio
+import pyworld
+import numpy as np, logging
+
+logging.getLogger("numba").setLevel(logging.WARNING)
+
+n_part = int(sys.argv[1])
+i_part = int(sys.argv[2])
+i_gpu = sys.argv[3]
+os.environ["CUDA_VISIBLE_DEVICES"] = str(i_gpu)
+exp_dir = sys.argv[4]
+is_half = sys.argv[5]
+f = open("%s/extract_f0_feature.log" % exp_dir, "a+")
+
+
+def printt(strr):
+    print(strr)
+    f.write("%s\n" % strr)
+    f.flush()
+
+
+
+class FeatureInput(object):
+    def __init__(self, samplerate=16000, hop_size=160):
+        self.fs = samplerate
+        self.hop = hop_size
+
+        self.f0_bin = 256
+        self.f0_max = 1100.0
+        self.f0_min = 50.0
+        self.f0_mel_min = 1127 * np.log(1 + self.f0_min / 700)
+        self.f0_mel_max = 1127 * np.log(1 + self.f0_max / 700)
+
+    def compute_f0(self, path, f0_method):
+        x = load_audio(path, self.fs)
+        p_len = x.shape[0] // self.hop
+        if(f0_method=="rmvpe"):
+            if hasattr(self, "model_rmvpe") == False:
+                from lib.rmvpe import RMVPE
+
+                print("loading rmvpe model")
+                self.model_rmvpe = RMVPE(
+                    "rmvpe.pt", is_half=True, device="cuda"
+                )
+            f0 = self.model_rmvpe.infer_from_audio(x, thred=0.03)
+        return f0
+
+    def coarse_f0(self, f0):
+        f0_mel = 1127 * np.log(1 + f0 / 700)
+        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - self.f0_mel_min) * (
+            self.f0_bin - 2
+        ) / (self.f0_mel_max - self.f0_mel_min) + 1
+
+        # use 0 or 1
+        f0_mel[f0_mel <= 1] = 1
+        f0_mel[f0_mel > self.f0_bin - 1] = self.f0_bin - 1
+        f0_coarse = np.rint(f0_mel).astype(int)
+        assert f0_coarse.max() <= 255 and f0_coarse.min() >= 1, (
+            f0_coarse.max(),
+            f0_coarse.min(),
+        )
+        return f0_coarse
+
+    def go(self, paths, f0_method):
+        if len(paths) == 0:
+            printt("no-f0-todo")
+        else:
+            printt("todo-f0-%s" % len(paths))
+            n = max(len(paths) // 5, 1)  # 每个进程最多打印5条
+            for idx, (inp_path, opt_path1, opt_path2) in enumerate(paths):
+                try:
+                    if idx % n == 0:
+                        printt("f0ing,now-%s,all-%s,-%s" % (idx, len(paths), inp_path))
+                    if (
+                        os.path.exists(opt_path1 + ".npy") == True
+                        and os.path.exists(opt_path2 + ".npy") == True
+                    ):
+                        continue
+                    featur_pit = self.compute_f0(inp_path, f0_method)
+                    np.save(
+                        opt_path2,
+                        featur_pit,
+                        allow_pickle=False,
+                    )  # nsf
+                    coarse_pit = self.coarse_f0(featur_pit)
+                    np.save(
+                        opt_path1,
+                        coarse_pit,
+                        allow_pickle=False,
+                    )  # ori
+                except:
+                    printt("f0fail-%s-%s-%s" % (idx, inp_path, traceback.format_exc()))
+
+
+if __name__ == "__main__":
+    # exp_dir=r"E:\codes\py39\dataset\mi-test"
+    # n_p=16
+    # f = open("%s/log_extract_f0.log"%exp_dir, "w")
+    printt(sys.argv)
+    featureInput = FeatureInput()
+    paths = []
+    inp_root = "%s/1_16k_wavs" % (exp_dir)
+    opt_root1 = "%s/2a_f0" % (exp_dir)
+    opt_root2 = "%s/2b-f0nsf" % (exp_dir)
+
+    os.makedirs(opt_root1, exist_ok=True)
+    os.makedirs(opt_root2, exist_ok=True)
+    for name in sorted(list(os.listdir(inp_root))):
+        inp_path = "%s/%s" % (inp_root, name)
+        if "spec" in inp_path:
+            continue
+        opt_path1 = "%s/%s" % (opt_root1, name)
+        opt_path2 = "%s/%s" % (opt_root2, name)
+        paths.append([inp_path, opt_path1, opt_path2])
+    try:
+        featureInput.go(paths[i_part::n_part],"rmvpe")
+    except:
+        printt("f0_all_fail-%s" % (traceback.format_exc()))
+    # ps = []
+    # for i in range(n_p):
+    #     p = Process(
+    #         target=featureInput.go,
+    #         args=(
+    #             paths[i::n_p],
+    #             f0method,
+    #         ),
+    #     )
+    #     ps.append(p)
+    #     p.start()
+    # for i in range(n_p):
+    #     ps[i].join()

infer-web.py

@@ -44,7 +44,7 @@ now_dir = os.getcwd()
 tmp = os.path.join(now_dir, "TEMP")
 shutil.rmtree(tmp, ignore_errors=True)
 shutil.rmtree(
-    "%s/runtime/Lib/site-packages/lib.infer_pack" % (now_dir), ignore_errors=True
+    "%s/runtime/Lib/site-packages/infer_pack" % (now_dir), ignore_errors=True
 )
 shutil.rmtree("%s/runtime/Lib/site-packages/uvr5_pack" % (now_dir), ignore_errors=True)
 os.makedirs(tmp, exist_ok=True)
@@ -542,7 +542,7 @@ def preprocess_dataset(trainset_dir, exp_dir, sr, n_p):
     f.close()
     cmd = (
         config.python_cmd
-        + " trainset_preprocess_pipeline_print.py %s %s %s %s/logs/%s "
+        + ' trainset_preprocess_pipeline_print.py "%s" %s %s "%s/logs/%s" '
         % (trainset_dir, sr, n_p, now_dir, exp_dir)
         + str(config.noparallel)
     )
@@ -570,13 +570,14 @@ def preprocess_dataset(trainset_dir, exp_dir, sr, n_p):
 
 
 # but2.click(extract_f0,[gpus6,np7,f0method8,if_f0_3,trainset_dir4],[info2])
-def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19):
+def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19,gpus_rmvpe):
     gpus = gpus.split("-")
     os.makedirs("%s/logs/%s" % (now_dir, exp_dir), exist_ok=True)
     f = open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "w")
     f.close()
     if if_f0:
-        cmd = config.python_cmd + " extract_f0_print.py %s/logs/%s %s %s" % (
+        if(f0method!="rmvpe_gpu"):
+            cmd = config.python_cmd + ' extract_f0_print.py "%s/logs/%s" %s %s' % (
                 now_dir,
                 exp_dir,
                 n_p,
@@ -605,6 +606,47 @@ def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19):
                 log = f.read()
             print(log)
             yield log
+        else:
+            gpus_rmvpe = gpus_rmvpe.split("-")
+            leng = len(gpus_rmvpe)
+            ps = []
+            for idx, n_g in enumerate(gpus_rmvpe):
+                cmd = (
+                        config.python_cmd
+                        + ' extract_f0_rmvpe.py %s %s %s "%s/logs/%s" %s '
+                        % (
+                            leng,
+                            idx,
+                            n_g,
+                            now_dir,
+                            exp_dir,
+                            config.is_half
+                        )
+                )
+                print(cmd)
+                p = Popen(
+                    cmd, shell=True, cwd=now_dir
+                )  # , shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir
+                ps.append(p)
+            ###煞笔gr, popen read都非得全跑完了再一次性读取, 不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读
+            done = [False]
+            threading.Thread(
+                target=if_done_multi,
+                args=(
+                    done,
+                    ps,
+                ),
+            ).start()
+            while 1:
+                with open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r") as f:
+                    yield (f.read())
+                sleep(1)
+                if done[0]:
+                    break
+            with open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r") as f:
+                log = f.read()
+            print(log)
+            yield log
     ####对不同part分别开多进程
     """
     n_part=int(sys.argv[1])
@@ -618,7 +660,7 @@ def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19):
     for idx, n_g in enumerate(gpus):
         cmd = (
             config.python_cmd
-            + " extract_feature_print.py %s %s %s %s %s/logs/%s %s"
+            + ' extract_feature_print.py %s %s %s %s "%s/logs/%s" %s'
             % (
                 config.device,
                 leng,
@@ -854,7 +896,7 @@ def click_train(
     if gpus16:
         cmd = (
             config.python_cmd
-            + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s"
+            + ' train_nsf_sim_cache_sid_load_pretrain.py -e "%s" -sr %s -f0 %s -bs %s -g %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s'
             % (
                 exp_dir1,
                 sr2,
@@ -874,7 +916,7 @@ def click_train(
     else:
         cmd = (
             config.python_cmd
-            + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s"
+            + ' train_nsf_sim_cache_sid_load_pretrain.py -e "%s" -sr %s -f0 %s -bs %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s'
             % (
                 exp_dir1,
                 sr2,
@@ -995,7 +1037,7 @@ def train1key(
     gpus16,
     if_cache_gpu17,
     if_save_every_weights18,
-    version19,
+    version19,gpus_rmvpe
 ):
     infos = []
 
@@ -1018,7 +1060,7 @@ def train1key(
     open(preprocess_log_path, "w").close()
     cmd = (
         config.python_cmd
-        + " trainset_preprocess_pipeline_print.py %s %s %s %s "
+        + ' trainset_preprocess_pipeline_print.py "%s" %s %s "%s" '
         % (trainset_dir4, sr_dict[sr2], np7, model_log_dir)
         + str(config.noparallel)
     )
@@ -1032,7 +1074,8 @@ def train1key(
     open(extract_f0_feature_log_path, "w")
     if if_f0_3:
         yield get_info_str("step2a:正在提取音高")
-        cmd = config.python_cmd + " extract_f0_print.py %s %s %s" % (
+        if(f0method8!="rmvpe_gpu"):
+            cmd = config.python_cmd + ' extract_f0_print.py "%s" %s %s' % (
                 model_log_dir,
                 np7,
                 f0method8,
@@ -1040,6 +1083,29 @@ def train1key(
             yield get_info_str(cmd)
             p = Popen(cmd, shell=True, cwd=now_dir)
             p.wait()
+        else:
+            gpus_rmvpe = gpus_rmvpe.split("-")
+            leng = len(gpus_rmvpe)
+            ps = []
+            for idx, n_g in enumerate(gpus_rmvpe):
+                cmd = (
+                        config.python_cmd
+                        + ' extract_f0_rmvpe.py %s %s %s "%s" %s '
+                        % (
+                            leng,
+                            idx,
+                            n_g,
+                            model_log_dir,
+                            config.is_half
+                        )
+                )
+                yield get_info_str(cmd)
+                p = Popen(
+                    cmd, shell=True, cwd=now_dir
+                )  # , shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir
+                ps.append(p)
+            for p in ps:
+                p.wait()
         with open(extract_f0_feature_log_path, "r") as f:
             print(f.read())
     else:
@@ -1050,7 +1116,7 @@ def train1key(
     leng = len(gpus)
     ps = []
     for idx, n_g in enumerate(gpus):
-        cmd = config.python_cmd + " extract_feature_print.py %s %s %s %s %s %s" % (
+        cmd = config.python_cmd + ' extract_feature_print.py %s %s %s %s "%s" %s' % (
             config.device,
             leng,
             idx,
@@ -1131,7 +1197,7 @@ def train1key(
     if gpus16:
         cmd = (
             config.python_cmd
-            + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s"
+            + ' train_nsf_sim_cache_sid_load_pretrain.py -e "%s" -sr %s -f0 %s -bs %s -g %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s'
             % (
                 exp_dir1,
                 sr2,
@@ -1151,7 +1217,7 @@ def train1key(
     else:
         cmd = (
             config.python_cmd
-            + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s"
+            + ' train_nsf_sim_cache_sid_load_pretrain.py -e "%s" -sr %s -f0 %s -bs %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s'
             % (
                 exp_dir1,
                 sr2,
@@ -1252,6 +1318,10 @@ def change_info_(ckpt_path):
         traceback.print_exc()
         return {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
 
+def change_f0_method(f0method8):
+    if(f0method8=="rmvpe_gpu"):visible=True
+    else:visible=False
+    return {"visible": visible, "__type__": "update"}
 
 def export_onnx(ModelPath, ExportedPath):
     global cpt
@@ -1340,7 +1410,7 @@ with gr.Blocks(title="RVC WebUI") as app:
                         )
                         f0method0 = gr.Radio(
                             label=i18n(
-                                "选择音高提取算法,输入歌声可用pm提速,harvest低音好但巨慢无比,crepe效果好但吃GPU"
+                                "选择音高提取算法,输入歌声可用pm提速,harvest低音好但巨慢无比,crepe效果好但吃GPU,rmvpe效果最好且微吃GPU"
                             ),
                             choices=["pm", "harvest", "crepe", "rmvpe"],
                             value="pm",
@@ -1442,7 +1512,7 @@ with gr.Blocks(title="RVC WebUI") as app:
                         opt_input = gr.Textbox(label=i18n("指定输出文件夹"), value="opt")
                         f0method1 = gr.Radio(
                             label=i18n(
-                                "选择音高提取算法,输入歌声可用pm提速,harvest低音好但巨慢无比,crepe效果好但吃GPU"
+                                "选择音高提取算法,输入歌声可用pm提速,harvest低音好但巨慢无比,crepe效果好但吃GPU,rmvpe效果最好且微吃GPU"
                             ),
                             choices=["pm", "harvest", "crepe", "rmvpe"],
                             value="pm",
@@ -1630,7 +1700,7 @@ with gr.Blocks(title="RVC WebUI") as app:
                 version19 = gr.Radio(
                     label=i18n("版本"),
                     choices=["v1", "v2"],
-                    value="v1",
+                    value="v2",
                     interactive=True,
                     visible=True,
                 )
@@ -1680,15 +1750,26 @@ with gr.Blocks(title="RVC WebUI") as app:
                             label=i18n(
                                 "选择音高提取算法:输入歌声可用pm提速,高质量语音但CPU差可用dio提速,harvest质量更好但慢"
                             ),
-                            choices=["pm", "harvest", "dio"],
+                            choices=["pm", "harvest", "dio", "rmvpe", "rmvpe_gpu"],
-                            value="harvest",
+                            value="rmvpe_gpu",
                             interactive=True,
                         )
+                        gpus_rmvpe = gr.Textbox(
+                            label=i18n("rmvpe卡号配置：以-分隔输入使用的不同进程卡号,例如0-0-1使用在卡0上跑2个进程并在卡1上跑1个进程"),
+                            value="%s-%s"%(gpus,gpus),
+                            interactive=True,
+                            visible=True
+                        )
                     but2 = gr.Button(i18n("特征提取"), variant="primary")
                     info2 = gr.Textbox(label=i18n("输出信息"), value="", max_lines=8)
+                    f0method8.change(
+                        fn=change_f0_method,
+                        inputs=[f0method8],
+                        outputs=[gpus_rmvpe],
+                    )
                     but2.click(
                         extract_f0_feature,
-                        [gpus6, np7, f0method8, if_f0_3, exp_dir1, version19],
+                        [gpus6, np7, f0method8, if_f0_3, exp_dir1, version19,gpus_rmvpe],
                         [info2],
                     )
             with gr.Group():
@@ -1741,12 +1822,12 @@ with gr.Blocks(title="RVC WebUI") as app:
                 with gr.Row():
                     pretrained_G14 = gr.Textbox(
                         label=i18n("加载预训练底模G路径"),
-                        value="pretrained/f0G40k.pth",
+                        value="pretrained_v2/f0G40k.pth",
                         interactive=True,
                     )
                     pretrained_D15 = gr.Textbox(
                         label=i18n("加载预训练底模D路径"),
-                        value="pretrained/f0D40k.pth",
+                        value="pretrained_v2/f0D40k.pth",
                         interactive=True,
                     )
                     sr2.change(
@@ -1813,7 +1894,7 @@ with gr.Blocks(title="RVC WebUI") as app:
                             gpus16,
                             if_cache_gpu17,
                             if_save_every_weights18,
-                            version19,
+                            version19,gpus_rmvpe
                         ],
                         info3,
                     )

train_nsf_sim_cache_sid_load_pretrain.py

@@ -3,7 +3,6 @@ now_dir = os.getcwd()
 sys.path.append(os.path.join(now_dir))
 sys.path.append(os.path.join(now_dir, "train"))
 
-from lib.train import utils
 from lib.train import utils
 import datetime
 

trainset_preprocess_pipeline_print.py

@@ -3,7 +3,7 @@ from scipy import signal
 
 now_dir = os.getcwd()
 sys.path.append(now_dir)
-
+print(sys.argv)
 inp_root = sys.argv[1]
 sr = int(sys.argv[2])
 n_p = int(sys.argv[3])