mirror of
https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2026-07-22 01:47:57 +08:00
feat: 兼容 proplus-hc-dev 训练数据 + 新增「情绪/括注」字段
兼容 proplus-hc-dev 分支基于 6 列 .list 训练的模型，并按主分支自身流程
增加 emotion 字段（标注/推理 UI 单输入框「情绪/括注」，存 emotion 列，
保留 remark 列以兼容 proplus 6 列结构）。emotion/remark 不参与训练。
核心兼容性修复（消除 3 处硬编码拒绝 proplus 的 6 列 .list）:
- 新增 tools/list_metadata.py: 6 列 .list 解析/格式化器 (parse/format_list_line)
- 1-get-text.py:129 line.split("|") 严格 4 列解包 -> parse_list_line
(proplus 同款修复，只取训练所需前 4 列，emotion/remark 静默忽略)
- subfix_webui b_load_list: 仅接受 len==4 -> 改用 parse_list_line (>=4 列)
- subfix_webui b_save_list: 写 4 列 -> 写 6 列 (保留 emotion/remark，向前向后兼容)
标注 UI (tools/subfix_webui.py):
- 每条音频新增「情绪/括注」Text 输入框 (g_emotion_list)
- b_change_index/reload_data/b_submit_change 贯通 emotion 读写
- 8 个分页事件输出列表统一追加 *g_emotion_list
推理 WebUI (inference_webui.py):
- _read_emotion_map_for_webui: 读 output/asr_opt/<exp>/*.list 的 emotion 列
- 训练样本下拉标签附加【emotion】(有则显示)
- 选中样本时同步刷新「情绪/括注」只读文本框; 应用样本一并填入
- 无 emotion 数据则文本框留空 (符合「无数据不显示」)
API (api_v2.py):
- GET /models/{name}/samples 响应增加 emotion 字段 (来自同源 .list)
向后兼容: 主分支原生 4 列 .list 全程正常; 训练 pipeline 不感知 emotion。
list_metadata/parse/emotion/round-trip 单元自测通过; py_compile 全通过。
This commit is contained in:
XucroYuri
parent
7be8a59e52
commit
e1720e7e5a
@ -1245,6 +1245,34 @@ def _read_name2text_for_webui(logs_dir: Path) -> dict[str, dict[str, str]]:
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return output
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def _read_emotion_map_for_webui(model_name: str) -> dict[str, str]:
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"""读取 ASR 标注 .list 中的 emotion 列，返回 {audio_name|stem: emotion}。
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扫描 output/asr_opt/<model_name>/ 下所有 *.list（4/5/6 列均兼容）。
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无 emotion 列或文件不存在时返回空 dict。
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"""
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from tools.list_metadata import parse_list_line
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emotion_map: dict[str, str] = {}
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list_dir = Path("output") / "asr_opt" / model_name
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if not list_dir.exists():
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return emotion_map
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for list_path in sorted(list_dir.glob("*.list")):
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try:
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for line in list_path.read_text(encoding="utf-8", errors="ignore").splitlines():
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item = parse_list_line(line)
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if item is None or not item.emotion:
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continue
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name = os.path.basename(item.wav_path.strip("\"'"))
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if not name:
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continue
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emotion_map[name] = item.emotion
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emotion_map[Path(name).stem] = item.emotion
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except Exception:
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continue
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return emotion_map
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def on_model_name_change(model_name: str):
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"""模型名变化时，加载该模型的训练样本列表到下拉框与预览播放器。"""
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if not model_name:
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@ -1256,10 +1284,16 @@ def on_model_name_change(model_name: str):
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samples: list[tuple[str, str]] = []
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if wav_dir.exists():
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name2text = _read_name2text_for_webui(logs_dir)
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emotion_map = _read_emotion_map_for_webui(model_name)
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for f in sorted(wav_dir.iterdir()):
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if f.is_file() and f.suffix.lower() in (".wav", ".mp3", ".flac"):
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text = name2text.get(f.name, {}).get("text", "") or name2text.get(f.stem, {}).get("text", "")
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label = f"{f.name}" + (f" | {text[:30]}" if text else "")
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emotion = emotion_map.get(f.name, "") or emotion_map.get(f.stem, "")
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label = f"{f.name}"
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if text:
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label += f" | {text[:30]}"
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if emotion:
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label += f" | 【{emotion}】"
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samples.append((label, str(f)))
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choices = [s[0] for s in samples]
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value = samples[0][0] if samples else ""
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@ -1268,28 +1302,33 @@ def on_model_name_change(model_name: str):
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def on_ref_sample_change(sample_label: str, model_name: str):
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"""训练样本选择变化时，更新预览播放器。"""
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"""训练样本选择变化时，更新预览播放器与情绪/括注文本框。"""
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if not sample_label or not model_name:
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return gr.Audio(value=None)
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return gr.Audio(value=None), ""
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from config import exp_root
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wav_name = sample_label.split(" | ")[0]
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audio_path = Path(exp_root) / model_name / "5-wav32k" / wav_name
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return gr.Audio(value=str(audio_path) if audio_path.exists() else None)
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emotion_map = _read_emotion_map_for_webui(model_name)
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emotion = emotion_map.get(wav_name, "") or emotion_map.get(Path(wav_name).stem, "")
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return gr.Audio(value=str(audio_path) if audio_path.exists() else None), emotion
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def on_apply_sample(sample_label: str, model_name: str):
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"""应用选中样本：写入参考音频路径和参考文本。"""
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"""应用选中样本：写入参考音频路径、参考文本、情绪/括注。"""
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if not sample_label or not model_name:
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return None, "", gr.Dropdown()
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return None, "", gr.Dropdown(), ""
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from config import exp_root
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wav_name = sample_label.split(" | ")[0]
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audio_path = Path(exp_root) / model_name / "5-wav32k" / wav_name
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logs_dir = Path(exp_root) / model_name
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name2text = _read_name2text_for_webui(logs_dir)
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emotion_map = _read_emotion_map_for_webui(model_name)
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text = name2text.get(wav_name, {}).get("text", "") or name2text.get(Path(wav_name).stem, {}).get("text", "")
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return (str(audio_path) if audio_path.exists() else None), text, gr.Dropdown()
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emotion = emotion_map.get(wav_name, "") or emotion_map.get(Path(wav_name).stem, "")
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audio_out = str(audio_path) if audio_path.exists() else None
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return audio_out, text, gr.Dropdown(), emotion
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def _scan_model_weights_for_webui() -> dict[str, dict[str, list[str]]]:
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@ -1412,6 +1451,12 @@ with gr.Blocks(title="GPT-SoVITS WebUI", analytics_enabled=False, js=js, css=css
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)
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)
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prompt_text = gr.Textbox(label=i18n("参考音频的文本"), value="", lines=5, max_lines=5, scale=1)
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ref_emotion_text = gr.Textbox(
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label=i18n("情绪/括注（来自训练样本，无数据留空）"),
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value="",
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interactive=False,
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scale=1,
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)
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with gr.Column(scale=14):
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prompt_language = gr.Dropdown(
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label=i18n("参考音频的语种"),
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@ -1584,12 +1629,12 @@ with gr.Blocks(title="GPT-SoVITS WebUI", analytics_enabled=False, js=js, css=css
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ref_sample_dropdown.change(
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fn=on_ref_sample_change,
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inputs=[ref_sample_dropdown, model_name_dropdown],
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outputs=[ref_sample_player],
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outputs=[ref_sample_player, ref_emotion_text],
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)
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apply_sample_btn.click(
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fn=on_apply_sample,
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inputs=[ref_sample_dropdown, model_name_dropdown],
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outputs=[inp_ref, prompt_text, ref_sample_dropdown],
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outputs=[inp_ref, prompt_text, ref_sample_dropdown, ref_emotion_text],
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)
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auto_select_weights_btn.click(
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fn=on_auto_select_weights,
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@ -20,6 +20,7 @@ import os.path
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from text.cleaner import clean_text
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from transformers import AutoModelForMaskedLM, AutoTokenizer
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from tools.my_utils import clean_path
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from tools.list_metadata import parse_list_line
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# inp_text=sys.argv[1]
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# inp_wav_dir=sys.argv[2]
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@ -126,7 +127,12 @@ if os.path.exists(txt_path) == False:
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}
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for line in lines[int(i_part) :: int(all_parts)]:
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try:
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wav_name, spk_name, language, text = line.split("|")
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# 兼容 4/5/6 列 .list：parse_list_line 只取训练所需前 4 列，
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# 额外的 emotion/remark 列（proplus-hc-dev 分支）被静默忽略，不影响训练。
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item = parse_list_line(line)
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if item is None:
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raise ValueError("list 行列数不足，需至少 4 列：wav_path|speaker_name|language|text")
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wav_name, language, text = item.wav_path, item.language, item.text
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# todo.append([name,text,"zh"])
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if language in language_v1_to_language_v2.keys():
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todo.append([wav_name, text, language_v1_to_language_v2.get(language, language)])
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33
api_v2.py
33
api_v2.py
@ -637,6 +637,36 @@ def _read_name2text(logs_dir: Path) -> dict[str, dict[str, str]]:
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return output
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def _read_emotion_map(model_name: str) -> dict[str, str]:
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"""读取 ASR 标注 .list 中的 emotion 列，返回 {audio_name|stem: emotion}。
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扫描 output/asr_opt/<model_name>/ 下所有 *.list（兼容 4/5/6 列）。
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兼容 proplus-hc-dev 分支训练数据：emotion 为第 5 列，缺省为空串。
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无 .list 或无 emotion 列时返回空 dict。
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"""
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from tools.list_metadata import parse_list_line
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emotion_map: dict[str, str] = {}
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list_dir = Path("output") / "asr_opt" / model_name
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if not list_dir.exists():
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return emotion_map
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for list_path in sorted(list_dir.glob("*.list")):
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try:
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for line in list_path.read_text(encoding="utf-8", errors="ignore").splitlines():
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item = parse_list_line(line)
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if item is None or not item.emotion:
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continue
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name = os.path.basename(item.wav_path.strip("\"'"))
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if not name:
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continue
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emotion_map[name] = item.emotion
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emotion_map[Path(name).stem] = item.emotion
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except Exception:
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continue
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return emotion_map
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def _safe_logs_subpath(model_name: str, *parts: str) -> Path | None:
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"""解析 logs/<model_name>/<parts...> 路径并做目录穿越校验。
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@ -706,6 +736,7 @@ async def list_model_samples(model_name: str):
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if logs_abs is None or not logs_abs.exists():
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return JSONResponse(status_code=404, content={"message": f"model '{model_name}' not found"})
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name2text = _read_name2text(logs_abs)
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emotion_map = _read_emotion_map(model_name)
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wav_dir = logs_abs / "5-wav32k"
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samples: list[dict] = []
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if wav_dir.exists():
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@ -718,11 +749,13 @@ async def list_model_samples(model_name: str):
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if entry is None:
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continue # 与 name2text 取交集，只返回有标注的样本
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rel = os.path.relpath(f, now_dir)
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emotion = emotion_map.get(f.name, "") or emotion_map.get(f.stem, "")
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samples.append({
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"audio_name": f.name,
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"audio_path": rel.replace(os.sep, "/"),
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"text": entry["text"],
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"lang": entry["lang"],
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"emotion": emotion,
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})
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return {"model_name": model_name, "samples": samples, "total": len(samples)}
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61
tools/list_metadata.py
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61
tools/list_metadata.py
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@ -0,0 +1,61 @@
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from __future__ import annotations
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from dataclasses import dataclass
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@dataclass(frozen=True)
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class ListLine:
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"""一条 `.list` 标注行（兼容 4/5/6 列）。
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列定义: wav_path|speaker_name|language|text[|emotion|remark]
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训练只用前 4 列（training_fields）；emotion / remark 为元数据，
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不参与模型训练，用于标注与参考音频展示。
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"""
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wav_path: str
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speaker_name: str
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language: str
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text: str
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emotion: str = ""
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remark: str = ""
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@property
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def training_fields(self):
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return [self.wav_path, self.speaker_name, self.language, self.text]
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def _clean(value):
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return str(value or "").strip()
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def parse_list_line(line):
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"""解析一行 `.list`。列数 < 4 返回 None；emotion/remark 缺省为空串。"""
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parts = str(line or "").rstrip("\r\n").split("|")
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if len(parts) < 4:
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return None
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return ListLine(
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wav_path=_clean(parts[0]),
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speaker_name=_clean(parts[1]),
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language=_clean(parts[2]),
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text=_clean(parts[3]),
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emotion=_clean(parts[4]) if len(parts) >= 5 else "",
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remark=_clean(parts[5]) if len(parts) >= 6 else "",
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)
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def format_list_line(item):
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"""把 ListLine 格式化为 6 列 `.list` 行（emotion/remark 为空也保留分隔符）。
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注意：写出 6 列以保证与 proplus-hc-dev 分支互操作，主分支训练侧
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（1-get-text.py）已用 parse_list_line 只消费前 4 列，多余列不影响训练。
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"""
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return "|".join(
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[
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str(item.wav_path or ""),
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str(item.speaker_name or ""),
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str(item.language or ""),
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str(item.text or ""),
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str(item.emotion or ""),
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str(item.remark or ""),
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]
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)
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@ -32,6 +32,7 @@ g_batch = 10
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g_text_list = []
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g_audio_list = []
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g_checkbox_list = []
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g_emotion_list = []
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g_data_json = []
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@ -43,7 +44,13 @@ def reload_data(index, batch):
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datas = g_data_json[index : index + batch]
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output = []
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for d in datas:
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output.append({g_json_key_text: d[g_json_key_text], g_json_key_path: d[g_json_key_path]})
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output.append(
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{
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g_json_key_text: d[g_json_key_text],
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g_json_key_path: d[g_json_key_path],
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"emotion": d.get("emotion", ""),
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}
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)
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return output
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@ -52,26 +59,26 @@ def b_change_index(index, batch):
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g_index, g_batch = index, batch
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datas = reload_data(index, batch)
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output = []
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# 文本框组
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for i, _ in enumerate(datas):
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output.append(
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# gr.Textbox(
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# label=f"Text {i+index}",
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# value=_[g_json_key_text]#text
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# )
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{"__type__": "update", "label": f"Text {i + index}", "value": _[g_json_key_text]}
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)
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for _ in range(g_batch - len(datas)):
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output.append({"__type__": "update", "label": "Text", "value": ""})
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# 情绪/括注框组（与文本框一一对应）
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for i, _ in enumerate(datas):
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output.append(
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# gr.Textbox(
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# label=f"Text",
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# value=""
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# )
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{"__type__": "update", "label": "Text", "value": ""}
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{"__type__": "update", "label": f"情绪/括注 {i + index}", "value": _.get("emotion", "")}
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)
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for _ in range(g_batch - len(datas)):
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output.append({"__type__": "update", "label": "情绪/括注", "value": ""})
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# 音频组
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for _ in datas:
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output.append(_[g_json_key_path])
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for _ in range(g_batch - len(datas)):
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output.append(None)
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# 复选框组
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for _ in range(g_batch):
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output.append(False)
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return output
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@ -93,8 +100,12 @@ def b_previous_index(index, batch):
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return 0, *b_change_index(0, batch)
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def b_submit_change(*text_list):
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def b_submit_change(*args):
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# 输入约定：[text×batch] + [emotion×batch]（由事件绑定顺序拼成）
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global g_data_json
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half = g_batch
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text_list = args[:half]
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emotion_list = args[half:]
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change = False
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for i, new_text in enumerate(text_list):
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if g_index + i <= g_max_json_index:
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@ -102,6 +113,12 @@ def b_submit_change(*text_list):
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if g_data_json[g_index + i][g_json_key_text] != new_text:
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g_data_json[g_index + i][g_json_key_text] = new_text
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change = True
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for i, new_emotion in enumerate(emotion_list):
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if g_index + i <= g_max_json_index:
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new_emotion = (new_emotion or "").strip()
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if g_data_json[g_index + i].get("emotion", "") != new_emotion:
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g_data_json[g_index + i]["emotion"] = new_emotion
|
||||
change = True
|
||||
if change:
|
||||
b_save_file()
|
||||
return g_index, *b_change_index(g_index, g_batch)
|
||||
@ -226,13 +243,25 @@ def b_save_json():
|
||||
|
||||
|
||||
def b_save_list():
|
||||
from tools.list_metadata import format_list_line, ListLine
|
||||
|
||||
with open(g_load_file, "w", encoding="utf-8") as file:
|
||||
for data in g_data_json:
|
||||
wav_path = data["wav_path"]
|
||||
speaker_name = data["speaker_name"]
|
||||
language = data["language"]
|
||||
text = data["text"]
|
||||
file.write(f"{wav_path}|{speaker_name}|{language}|{text}".strip() + "\n")
|
||||
# 写出 6 列以保留 emotion/remark（proplus-hc-dev 互操作）；
|
||||
# 主分支训练侧（1-get-text.py）只消费前 4 列，多余列不影响训练。
|
||||
file.write(
|
||||
format_list_line(
|
||||
ListLine(
|
||||
wav_path=data.get("wav_path", ""),
|
||||
speaker_name=data.get("speaker_name", ""),
|
||||
language=data.get("language", ""),
|
||||
text=data.get("text", ""),
|
||||
emotion=data.get("emotion", ""),
|
||||
remark=data.get("remark", ""),
|
||||
)
|
||||
).strip()
|
||||
+ "\n"
|
||||
)
|
||||
|
||||
|
||||
def b_load_json():
|
||||
@ -245,17 +274,25 @@ def b_load_json():
|
||||
|
||||
def b_load_list():
|
||||
global g_data_json, g_max_json_index
|
||||
from tools.list_metadata import parse_list_line
|
||||
|
||||
with open(g_load_file, "r", encoding="utf-8") as source:
|
||||
data_list = source.readlines()
|
||||
for _ in data_list:
|
||||
data = _.split("|")
|
||||
if len(data) == 4:
|
||||
wav_path, speaker_name, language, text = data
|
||||
g_data_json.append(
|
||||
{"wav_path": wav_path, "speaker_name": speaker_name, "language": language, "text": text.strip()}
|
||||
)
|
||||
else:
|
||||
print("error line:", data)
|
||||
item = parse_list_line(_)
|
||||
if item is None:
|
||||
print("error line:", _)
|
||||
continue
|
||||
g_data_json.append(
|
||||
{
|
||||
"wav_path": item.wav_path,
|
||||
"speaker_name": item.speaker_name,
|
||||
"language": item.language,
|
||||
"text": item.text,
|
||||
"emotion": item.emotion,
|
||||
"remark": item.remark,
|
||||
}
|
||||
)
|
||||
g_max_json_index = len(g_data_json) - 1
|
||||
|
||||
|
||||
@ -338,9 +375,16 @@ if __name__ == "__main__":
|
||||
text = gr.Textbox(label="Text", visible=True, scale=5)
|
||||
audio_output = gr.Audio(label="Output Audio", visible=True, scale=5)
|
||||
audio_check = gr.Checkbox(label="Yes", show_label=True, info="Choose Audio", scale=1)
|
||||
emotion = gr.Textbox(
|
||||
label="情绪/括注",
|
||||
visible=True,
|
||||
scale=3,
|
||||
placeholder="可选：台词对应的表演情绪或括注",
|
||||
)
|
||||
g_text_list.append(text)
|
||||
g_audio_list.append(audio_output)
|
||||
g_checkbox_list.append(audio_check)
|
||||
g_emotion_list.append(emotion)
|
||||
|
||||
with gr.Row():
|
||||
batchsize_slider = gr.Slider(
|
||||
@ -356,15 +400,16 @@ if __name__ == "__main__":
|
||||
index_slider,
|
||||
batchsize_slider,
|
||||
],
|
||||
outputs=[*g_text_list, *g_audio_list, *g_checkbox_list],
|
||||
outputs=[*g_text_list, *g_emotion_list, *g_audio_list, *g_checkbox_list],
|
||||
)
|
||||
|
||||
btn_submit_change.click(
|
||||
b_submit_change,
|
||||
inputs=[
|
||||
*g_text_list,
|
||||
*g_emotion_list,
|
||||
],
|
||||
outputs=[index_slider, *g_text_list, *g_audio_list, *g_checkbox_list],
|
||||
outputs=[index_slider, *g_text_list, *g_emotion_list, *g_audio_list, *g_checkbox_list],
|
||||
)
|
||||
|
||||
btn_previous_index.click(
|
||||
@ -373,7 +418,7 @@ if __name__ == "__main__":
|
||||
index_slider,
|
||||
batchsize_slider,
|
||||
],
|
||||
outputs=[index_slider, *g_text_list, *g_audio_list, *g_checkbox_list],
|
||||
outputs=[index_slider, *g_text_list, *g_emotion_list, *g_audio_list, *g_checkbox_list],
|
||||
)
|
||||
|
||||
btn_next_index.click(
|
||||
@ -382,25 +427,25 @@ if __name__ == "__main__":
|
||||
index_slider,
|
||||
batchsize_slider,
|
||||
],
|
||||
outputs=[index_slider, *g_text_list, *g_audio_list, *g_checkbox_list],
|
||||
outputs=[index_slider, *g_text_list, *g_emotion_list, *g_audio_list, *g_checkbox_list],
|
||||
)
|
||||
|
||||
btn_delete_audio.click(
|
||||
b_delete_audio,
|
||||
inputs=[*g_checkbox_list],
|
||||
outputs=[index_slider, *g_text_list, *g_audio_list, *g_checkbox_list],
|
||||
outputs=[index_slider, *g_text_list, *g_emotion_list, *g_audio_list, *g_checkbox_list],
|
||||
)
|
||||
|
||||
btn_merge_audio.click(
|
||||
b_merge_audio,
|
||||
inputs=[interval_slider, *g_checkbox_list],
|
||||
outputs=[index_slider, *g_text_list, *g_audio_list, *g_checkbox_list],
|
||||
outputs=[index_slider, *g_text_list, *g_emotion_list, *g_audio_list, *g_checkbox_list],
|
||||
)
|
||||
|
||||
btn_audio_split.click(
|
||||
b_audio_split,
|
||||
inputs=[splitpoint_slider, *g_checkbox_list],
|
||||
outputs=[index_slider, *g_text_list, *g_audio_list, *g_checkbox_list],
|
||||
outputs=[index_slider, *g_text_list, *g_emotion_list, *g_audio_list, *g_checkbox_list],
|
||||
)
|
||||
|
||||
btn_invert_selection.click(b_invert_selection, inputs=[*g_checkbox_list], outputs=[*g_checkbox_list])
|
||||
@ -413,7 +458,7 @@ if __name__ == "__main__":
|
||||
index_slider,
|
||||
batchsize_slider,
|
||||
],
|
||||
outputs=[*g_text_list, *g_audio_list, *g_checkbox_list],
|
||||
outputs=[*g_text_list, *g_emotion_list, *g_audio_list, *g_checkbox_list],
|
||||
)
|
||||
|
||||
demo.launch(
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user