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import os, sys |
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import gradio as gr |
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import regex as re |
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import shutil |
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import datetime |
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import json |
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from core import ( |
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run_infer_script, |
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run_batch_infer_script, |
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) |
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from assets.i18n.i18n import I18nAuto |
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from rvc.lib.utils import format_title |
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i18n = I18nAuto() |
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now_dir = os.getcwd() |
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sys.path.append(now_dir) |
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model_root = os.path.join(now_dir, "logs") |
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audio_root = os.path.join(now_dir, "assets", "audios") |
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custom_embedder_root = os.path.join( |
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now_dir, "rvc", "models", "embedders", "embedders_custom" |
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) |
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PRESETS_DIR = "assets/presets" |
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|
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os.makedirs(custom_embedder_root, exist_ok=True) |
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custom_embedder_root_relative = os.path.relpath(custom_embedder_root, now_dir) |
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model_root_relative = os.path.relpath(model_root, now_dir) |
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audio_root_relative = os.path.relpath(audio_root, now_dir) |
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sup_audioext = { |
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"wav", |
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"mp3", |
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"flac", |
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"ogg", |
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"opus", |
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"m4a", |
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"mp4", |
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"aac", |
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"alac", |
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"wma", |
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"aiff", |
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"webm", |
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"ac3", |
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} |
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names = [ |
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os.path.join(root, file) |
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for root, _, files in os.walk(model_root_relative, topdown=False) |
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for file in files |
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if ( |
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file.endswith((".pth", ".onnx")) |
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and not (file.startswith("G_") or file.startswith("D_")) |
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) |
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] |
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indexes_list = [ |
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os.path.join(root, name) |
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for root, _, files in os.walk(model_root_relative, topdown=False) |
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for name in files |
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if name.endswith(".index") and "trained" not in name |
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] |
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audio_paths = [ |
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os.path.join(root, name) |
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for root, _, files in os.walk(audio_root_relative, topdown=False) |
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for name in files |
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if name.endswith(tuple(sup_audioext)) |
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and root == audio_root_relative |
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and "_output" not in name |
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] |
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custom_embedders = [ |
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os.path.join(dirpath, filename) |
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for dirpath, _, filenames in os.walk(custom_embedder_root_relative) |
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for filename in filenames |
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if filename.endswith(".pt") |
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] |
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def update_sliders(preset): |
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with open( |
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os.path.join(PRESETS_DIR, f"{preset}.json"), "r", encoding="utf-8" |
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) as json_file: |
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values = json.load(json_file) |
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return ( |
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values["pitch"], |
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values["filter_radius"], |
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values["index_rate"], |
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values["rms_mix_rate"], |
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values["protect"], |
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) |
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def export_presets(presets, file_path): |
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with open(file_path, "w", encoding="utf-8") as json_file: |
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json.dump(presets, json_file, ensure_ascii=False, indent=4) |
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def import_presets(file_path): |
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with open(file_path, "r", encoding="utf-8") as json_file: |
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presets = json.load(json_file) |
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return presets |
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def get_presets_data(pitch, filter_radius, index_rate, rms_mix_rate, protect): |
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return { |
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"pitch": pitch, |
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"filter_radius": filter_radius, |
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"index_rate": index_rate, |
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"rms_mix_rate": rms_mix_rate, |
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"protect": protect, |
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} |
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def export_presets_button( |
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preset_name, pitch, filter_radius, index_rate, rms_mix_rate, protect |
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): |
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if preset_name: |
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file_path = os.path.join(PRESETS_DIR, f"{preset_name}.json") |
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presets_data = get_presets_data( |
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pitch, filter_radius, index_rate, rms_mix_rate, protect |
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) |
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with open(file_path, "w", encoding="utf-8") as json_file: |
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json.dump(presets_data, json_file, ensure_ascii=False, indent=4) |
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return "Export successful" |
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return "Export cancelled" |
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def import_presets_button(file_path): |
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if file_path: |
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imported_presets = import_presets(file_path.name) |
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return ( |
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list(imported_presets.keys()), |
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imported_presets, |
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"Presets imported successfully!", |
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) |
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return [], {}, "No file selected for import." |
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def list_json_files(directory): |
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return [f.rsplit(".", 1)[0] for f in os.listdir(directory) if f.endswith(".json")] |
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def refresh_presets(): |
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json_files = list_json_files(PRESETS_DIR) |
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return gr.update(choices=json_files) |
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def update_visibility(selected_preset): |
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if selected_preset == "Custom": |
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json_files = list_json_files(PRESETS_DIR) |
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return ( |
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gr.update(visible=True, choices=json_files), |
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gr.update(visible=True), |
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gr.update(visible=True), |
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gr.update(visible=True), |
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gr.update(visible=True), |
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) |
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else: |
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return ( |
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gr.update(visible=False), |
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gr.update(visible=False), |
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gr.update(visible=False), |
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gr.update(visible=False), |
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gr.update(visible=False), |
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) |
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def output_path_fn(input_audio_path): |
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original_name_without_extension = os.path.basename(input_audio_path).rsplit(".", 1)[ |
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0 |
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] |
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new_name = original_name_without_extension + "_output.wav" |
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output_path = os.path.join(os.path.dirname(input_audio_path), new_name) |
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return output_path |
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def change_choices(): |
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names = [ |
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os.path.join(root, file) |
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for root, _, files in os.walk(model_root_relative, topdown=False) |
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for file in files |
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if ( |
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file.endswith((".pth", ".onnx")) |
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and not (file.startswith("G_") or file.startswith("D_")) |
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) |
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] |
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indexes_list = [ |
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os.path.join(root, name) |
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for root, _, files in os.walk(model_root_relative, topdown=False) |
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for name in files |
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if name.endswith(".index") and "trained" not in name |
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] |
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audio_paths = [ |
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os.path.join(root, name) |
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for root, _, files in os.walk(audio_root_relative, topdown=False) |
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for name in files |
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if name.endswith(tuple(sup_audioext)) |
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and root == audio_root_relative |
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and "_output" not in name |
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] |
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custom_embedder = [ |
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os.path.join(dirpath, filename) |
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for dirpath, _, filenames in os.walk(custom_embedder_root_relative) |
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for filename in filenames |
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if filename.endswith(".pt") |
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] |
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return ( |
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{"choices": sorted(names), "__type__": "update"}, |
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{"choices": sorted(indexes_list), "__type__": "update"}, |
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{"choices": sorted(audio_paths), "__type__": "update"}, |
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{"choices": sorted(custom_embedder), "__type__": "update"}, |
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{"choices": sorted(custom_embedder), "__type__": "update"}, |
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) |
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def get_indexes(): |
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indexes_list = [ |
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os.path.join(dirpath, filename) |
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for dirpath, _, filenames in os.walk(model_root_relative) |
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for filename in filenames |
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if filename.endswith(".index") and "trained" not in filename |
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] |
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return indexes_list if indexes_list else "" |
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def save_to_wav(record_button): |
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if record_button is None: |
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pass |
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else: |
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path_to_file = record_button |
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new_name = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S") + ".wav" |
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target_path = os.path.join(audio_root_relative, os.path.basename(new_name)) |
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shutil.move(path_to_file, target_path) |
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return target_path, output_path_fn(target_path) |
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def save_to_wav2(upload_audio): |
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file_path = upload_audio |
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formated_name = format_title(os.path.basename(file_path)) |
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target_path = os.path.join(audio_root_relative, formated_name) |
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if os.path.exists(target_path): |
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os.remove(target_path) |
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shutil.copy(file_path, target_path) |
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return target_path, output_path_fn(target_path) |
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def delete_outputs(): |
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gr.Info(f"Outputs cleared!") |
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for root, _, files in os.walk(audio_root_relative, topdown=False): |
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for name in files: |
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if name.endswith(tuple(sup_audioext)) and name.__contains__("_output"): |
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os.remove(os.path.join(root, name)) |
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def match_index(model_file_value): |
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if model_file_value: |
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model_folder = os.path.dirname(model_file_value) |
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model_name = os.path.basename(model_file_value) |
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index_files = get_indexes() |
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pattern = r"^(.*?)_" |
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match = re.match(pattern, model_name) |
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for index_file in index_files: |
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if os.path.dirname(index_file) == model_folder: |
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return index_file |
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elif match and match.group(1) in os.path.basename(index_file): |
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return index_file |
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elif model_name in os.path.basename(index_file): |
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return index_file |
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return "" |
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def save_drop_custom_embedder(dropbox): |
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if ".pt" not in dropbox: |
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gr.Info( |
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i18n("The file you dropped is not a valid embedder file. Please try again.") |
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) |
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else: |
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file_name = os.path.basename(dropbox) |
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custom_embedder_path = os.path.join(custom_embedder_root, file_name) |
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if os.path.exists(custom_embedder_path): |
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os.remove(custom_embedder_path) |
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os.rename(dropbox, custom_embedder_path) |
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gr.Info( |
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i18n( |
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"Click the refresh button to see the embedder file in the dropdown menu." |
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) |
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) |
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return None |
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def inference_tab(): |
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default_weight = names[0] if names else None |
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with gr.Row(): |
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with gr.Row(): |
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model_file = gr.Dropdown( |
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label=i18n("Voice Model"), |
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info=i18n("Select the voice model to use for the conversion."), |
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choices=sorted(names, key=lambda path: os.path.getsize(path)), |
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interactive=True, |
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value=default_weight, |
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allow_custom_value=True, |
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) |
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index_file = gr.Dropdown( |
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label=i18n("Index File"), |
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info=i18n("Select the index file to use for the conversion."), |
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choices=get_indexes(), |
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value=match_index(default_weight) if default_weight else "", |
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interactive=True, |
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allow_custom_value=True, |
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) |
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with gr.Column(): |
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refresh_button = gr.Button(i18n("Refresh")) |
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unload_button = gr.Button(i18n("Unload Voice")) |
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unload_button.click( |
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fn=lambda: ( |
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{"value": "", "__type__": "update"}, |
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{"value": "", "__type__": "update"}, |
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), |
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inputs=[], |
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outputs=[model_file, index_file], |
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) |
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model_file.select( |
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fn=lambda model_file_value: match_index(model_file_value), |
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inputs=[model_file], |
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outputs=[index_file], |
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) |
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with gr.Tab(i18n("Single")): |
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with gr.Column(): |
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upload_audio = gr.Audio( |
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label=i18n("Upload Audio"), type="filepath", editable=False |
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) |
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with gr.Row(): |
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audio = gr.Dropdown( |
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label=i18n("Select Audio"), |
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info=i18n("Select the audio to convert."), |
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choices=sorted(audio_paths), |
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value=audio_paths[0] if audio_paths else "", |
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interactive=True, |
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allow_custom_value=True, |
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) |
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with gr.Accordion(i18n("Advanced Settings"), open=False): |
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with gr.Column(): |
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clear_outputs_infer = gr.Button( |
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i18n("Clear Outputs (Deletes all audios in assets/audios)") |
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) |
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output_path = gr.Textbox( |
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label=i18n("Output Path"), |
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placeholder=i18n("Enter output path"), |
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info=i18n( |
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"The path where the output audio will be saved, by default in assets/audios/output.wav" |
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), |
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value=( |
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output_path_fn(audio_paths[0]) |
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if audio_paths |
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else os.path.join(now_dir, "assets", "audios", "output.wav") |
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), |
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interactive=True, |
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) |
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export_format = gr.Radio( |
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label=i18n("Export Format"), |
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info=i18n("Select the format to export the audio."), |
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choices=["WAV", "MP3", "FLAC", "OGG", "M4A"], |
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value="WAV", |
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interactive=True, |
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) |
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split_audio = gr.Checkbox( |
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label=i18n("Split Audio"), |
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info=i18n( |
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"Split the audio into chunks for inference to obtain better results in some cases." |
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), |
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visible=True, |
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value=False, |
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interactive=True, |
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) |
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autotune = gr.Checkbox( |
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label=i18n("Autotune"), |
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info=i18n( |
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"Apply a soft autotune to your inferences, recommended for singing conversions." |
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), |
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visible=True, |
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value=False, |
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interactive=True, |
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) |
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clean_audio = gr.Checkbox( |
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label=i18n("Clean Audio"), |
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info=i18n( |
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"Clean your audio output using noise detection algorithms, recommended for speaking audios." |
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), |
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visible=True, |
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value=False, |
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interactive=True, |
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) |
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clean_strength = gr.Slider( |
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minimum=0, |
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maximum=1, |
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label=i18n("Clean Strength"), |
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info=i18n( |
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"Set the clean-up level to the audio you want, the more you increase it the more it will clean up, but it is possible that the audio will be more compressed." |
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), |
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visible=False, |
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value=0.5, |
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interactive=True, |
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) |
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upscale_audio = gr.Checkbox( |
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label=i18n("Upscale Audio"), |
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info=i18n( |
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"Upscale the audio to a higher quality, recommended for low-quality audios. (It could take longer to process the audio)" |
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), |
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visible=True, |
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value=False, |
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interactive=True, |
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) |
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with gr.Accordion(i18n("Preset Settings"), open=False): |
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with gr.Row(): |
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preset_dropdown = gr.Dropdown( |
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label=i18n("Select Custom Preset"), |
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choices=list_json_files(PRESETS_DIR), |
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interactive=True, |
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) |
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presets_refresh_button = gr.Button(i18n("Refresh Presets")) |
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import_file = gr.File( |
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label=i18n("Select file to import"), |
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file_count="single", |
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type="filepath", |
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interactive=True, |
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) |
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import_file.change( |
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import_presets_button, |
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inputs=import_file, |
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outputs=[preset_dropdown], |
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) |
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presets_refresh_button.click( |
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refresh_presets, outputs=preset_dropdown |
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) |
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with gr.Row(): |
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preset_name_input = gr.Textbox( |
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label=i18n("Preset Name"), |
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placeholder=i18n("Enter preset name"), |
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) |
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export_button = gr.Button(i18n("Export Preset")) |
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pitch = gr.Slider( |
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minimum=-24, |
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maximum=24, |
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step=1, |
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label=i18n("Pitch"), |
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info=i18n( |
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"Set the pitch of the audio, the higher the value, the higher the pitch." |
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), |
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value=0, |
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interactive=True, |
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) |
|
filter_radius = gr.Slider( |
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minimum=0, |
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maximum=7, |
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label=i18n("Filter Radius"), |
|
info=i18n( |
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"If the number is greater than or equal to three, employing median filtering on the collected tone results has the potential to decrease respiration." |
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), |
|
value=3, |
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step=1, |
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interactive=True, |
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) |
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index_rate = gr.Slider( |
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minimum=0, |
|
maximum=1, |
|
label=i18n("Search Feature Ratio"), |
|
info=i18n( |
|
"Influence exerted by the index file; a higher value corresponds to greater influence. However, opting for lower values can help mitigate artifacts present in the audio." |
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), |
|
value=0.75, |
|
interactive=True, |
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) |
|
rms_mix_rate = gr.Slider( |
|
minimum=0, |
|
maximum=1, |
|
label=i18n("Volume Envelope"), |
|
info=i18n( |
|
"Substitute or blend with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is employed." |
|
), |
|
value=1, |
|
interactive=True, |
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) |
|
protect = gr.Slider( |
|
minimum=0, |
|
maximum=0.5, |
|
label=i18n("Protect Voiceless Consonants"), |
|
info=i18n( |
|
"Safeguard distinct consonants and breathing sounds to prevent electro-acoustic tearing and other artifacts. Pulling the parameter to its maximum value of 0.5 offers comprehensive protection. However, reducing this value might decrease the extent of protection while potentially mitigating the indexing effect." |
|
), |
|
value=0.5, |
|
interactive=True, |
|
) |
|
preset_dropdown.change( |
|
update_sliders, |
|
inputs=preset_dropdown, |
|
outputs=[ |
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pitch, |
|
filter_radius, |
|
index_rate, |
|
rms_mix_rate, |
|
protect, |
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], |
|
) |
|
export_button.click( |
|
export_presets_button, |
|
inputs=[ |
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preset_name_input, |
|
pitch, |
|
filter_radius, |
|
index_rate, |
|
rms_mix_rate, |
|
protect, |
|
], |
|
) |
|
hop_length = gr.Slider( |
|
minimum=1, |
|
maximum=512, |
|
step=1, |
|
label=i18n("Hop Length"), |
|
info=i18n( |
|
"Denotes the duration it takes for the system to transition to a significant pitch change. Smaller hop lengths require more time for inference but tend to yield higher pitch accuracy." |
|
), |
|
visible=False, |
|
value=128, |
|
interactive=True, |
|
) |
|
f0_method = gr.Radio( |
|
label=i18n("Pitch extraction algorithm"), |
|
info=i18n( |
|
"Pitch extraction algorithm to use for the audio conversion. The default algorithm is rmvpe, which is recommended for most cases." |
|
), |
|
choices=[ |
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"crepe", |
|
"crepe-tiny", |
|
"rmvpe", |
|
"fcpe", |
|
"hybrid[rmvpe+fcpe]", |
|
], |
|
value="rmvpe", |
|
interactive=True, |
|
) |
|
embedder_model = gr.Radio( |
|
label=i18n("Embedder Model"), |
|
info=i18n("Model used for learning speaker embedding."), |
|
choices=[ |
|
"contentvec", |
|
"japanese-hubert-base", |
|
"chinese-hubert-large", |
|
"custom", |
|
], |
|
value="contentvec", |
|
interactive=True, |
|
) |
|
with gr.Column(visible=False) as embedder_custom: |
|
with gr.Accordion(i18n("Custom Embedder"), open=True): |
|
embedder_upload_custom = gr.File( |
|
label=i18n("Upload Custom Embedder"), |
|
type="filepath", |
|
interactive=True, |
|
) |
|
embedder_custom_refresh = gr.Button(i18n("Refresh")) |
|
embedder_model_custom = gr.Dropdown( |
|
label=i18n("Custom Embedder"), |
|
info=i18n( |
|
"Select the custom embedder to use for the conversion." |
|
), |
|
choices=sorted(custom_embedders), |
|
interactive=True, |
|
allow_custom_value=True, |
|
) |
|
f0_file = gr.File( |
|
label=i18n( |
|
"The f0 curve represents the variations in the base frequency of a voice over time, showing how pitch rises and falls." |
|
), |
|
visible=True, |
|
) |
|
|
|
convert_button1 = gr.Button(i18n("Convert")) |
|
|
|
with gr.Row(): |
|
vc_output1 = gr.Textbox( |
|
label=i18n("Output Information"), |
|
info=i18n("The output information will be displayed here."), |
|
) |
|
vc_output2 = gr.Audio(label=i18n("Export Audio")) |
|
|
|
|
|
with gr.Tab(i18n("Batch")): |
|
with gr.Row(): |
|
with gr.Column(): |
|
input_folder_batch = gr.Textbox( |
|
label=i18n("Input Folder"), |
|
info=i18n("Select the folder containing the audios to convert."), |
|
placeholder=i18n("Enter input path"), |
|
value=os.path.join(now_dir, "assets", "audios"), |
|
interactive=True, |
|
) |
|
output_folder_batch = gr.Textbox( |
|
label=i18n("Output Folder"), |
|
info=i18n( |
|
"Select the folder where the output audios will be saved." |
|
), |
|
placeholder=i18n("Enter output path"), |
|
value=os.path.join(now_dir, "assets", "audios"), |
|
interactive=True, |
|
) |
|
with gr.Accordion(i18n("Advanced Settings"), open=False): |
|
with gr.Column(): |
|
clear_outputs_batch = gr.Button( |
|
i18n("Clear Outputs (Deletes all audios in assets/audios)") |
|
) |
|
export_format_batch = gr.Radio( |
|
label=i18n("Export Format"), |
|
info=i18n("Select the format to export the audio."), |
|
choices=["WAV", "MP3", "FLAC", "OGG", "M4A"], |
|
value="WAV", |
|
interactive=True, |
|
) |
|
split_audio_batch = gr.Checkbox( |
|
label=i18n("Split Audio"), |
|
info=i18n( |
|
"Split the audio into chunks for inference to obtain better results in some cases." |
|
), |
|
visible=True, |
|
value=False, |
|
interactive=True, |
|
) |
|
autotune_batch = gr.Checkbox( |
|
label=i18n("Autotune"), |
|
info=i18n( |
|
"Apply a soft autotune to your inferences, recommended for singing conversions." |
|
), |
|
visible=True, |
|
value=False, |
|
interactive=True, |
|
) |
|
clean_audio_batch = gr.Checkbox( |
|
label=i18n("Clean Audio"), |
|
info=i18n( |
|
"Clean your audio output using noise detection algorithms, recommended for speaking audios." |
|
), |
|
visible=True, |
|
value=False, |
|
interactive=True, |
|
) |
|
clean_strength_batch = gr.Slider( |
|
minimum=0, |
|
maximum=1, |
|
label=i18n("Clean Strength"), |
|
info=i18n( |
|
"Set the clean-up level to the audio you want, the more you increase it the more it will clean up, but it is possible that the audio will be more compressed." |
|
), |
|
visible=False, |
|
value=0.5, |
|
interactive=True, |
|
) |
|
upscale_audio_batch = gr.Checkbox( |
|
label=i18n("Upscale Audio"), |
|
info=i18n( |
|
"Upscale the audio to a higher quality, recommended for low-quality audios. (It could take longer to process the audio)" |
|
), |
|
visible=True, |
|
value=False, |
|
interactive=True, |
|
) |
|
with gr.Accordion(i18n("Preset Settings"), open=False): |
|
with gr.Row(): |
|
preset_dropdown = gr.Dropdown( |
|
label=i18n("Select Custom Preset"), |
|
choices=list_json_files(PRESETS_DIR), |
|
interactive=True, |
|
) |
|
presets_batch_refresh_button = gr.Button( |
|
i18n("Refresh Presets") |
|
) |
|
import_file = gr.File( |
|
label=i18n("Select file to import"), |
|
file_count="single", |
|
type="filepath", |
|
interactive=True, |
|
) |
|
import_file.change( |
|
import_presets_button, |
|
inputs=import_file, |
|
outputs=[preset_dropdown], |
|
) |
|
presets_batch_refresh_button.click( |
|
refresh_presets, outputs=preset_dropdown |
|
) |
|
with gr.Row(): |
|
preset_name_input = gr.Textbox( |
|
label=i18n("Preset Name"), |
|
placeholder=i18n("Enter preset name"), |
|
) |
|
export_button = gr.Button(i18n("Export Preset")) |
|
pitch_batch = gr.Slider( |
|
minimum=-24, |
|
maximum=24, |
|
step=1, |
|
label=i18n("Pitch"), |
|
info=i18n( |
|
"Set the pitch of the audio, the higher the value, the higher the pitch." |
|
), |
|
value=0, |
|
interactive=True, |
|
) |
|
filter_radius_batch = gr.Slider( |
|
minimum=0, |
|
maximum=7, |
|
label=i18n("Filter Radius"), |
|
info=i18n( |
|
"If the number is greater than or equal to three, employing median filtering on the collected tone results has the potential to decrease respiration." |
|
), |
|
value=3, |
|
step=1, |
|
interactive=True, |
|
) |
|
index_rate_batch = gr.Slider( |
|
minimum=0, |
|
maximum=1, |
|
label=i18n("Search Feature Ratio"), |
|
info=i18n( |
|
"Influence exerted by the index file; a higher value corresponds to greater influence. However, opting for lower values can help mitigate artifacts present in the audio." |
|
), |
|
value=0.75, |
|
interactive=True, |
|
) |
|
rms_mix_rate_batch = gr.Slider( |
|
minimum=0, |
|
maximum=1, |
|
label=i18n("Volume Envelope"), |
|
info=i18n( |
|
"Substitute or blend with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is employed." |
|
), |
|
value=1, |
|
interactive=True, |
|
) |
|
protect_batch = gr.Slider( |
|
minimum=0, |
|
maximum=0.5, |
|
label=i18n("Protect Voiceless Consonants"), |
|
info=i18n( |
|
"Safeguard distinct consonants and breathing sounds to prevent electro-acoustic tearing and other artifacts. Pulling the parameter to its maximum value of 0.5 offers comprehensive protection. However, reducing this value might decrease the extent of protection while potentially mitigating the indexing effect." |
|
), |
|
value=0.5, |
|
interactive=True, |
|
) |
|
preset_dropdown.change( |
|
update_sliders, |
|
inputs=preset_dropdown, |
|
outputs=[ |
|
pitch_batch, |
|
filter_radius_batch, |
|
index_rate_batch, |
|
rms_mix_rate_batch, |
|
protect_batch, |
|
], |
|
) |
|
export_button.click( |
|
export_presets_button, |
|
inputs=[ |
|
preset_name_input, |
|
pitch, |
|
filter_radius, |
|
index_rate, |
|
rms_mix_rate, |
|
protect, |
|
], |
|
outputs=[], |
|
) |
|
hop_length_batch = gr.Slider( |
|
minimum=1, |
|
maximum=512, |
|
step=1, |
|
label=i18n("Hop Length"), |
|
info=i18n( |
|
"Denotes the duration it takes for the system to transition to a significant pitch change. Smaller hop lengths require more time for inference but tend to yield higher pitch accuracy." |
|
), |
|
visible=False, |
|
value=128, |
|
interactive=True, |
|
) |
|
f0_method_batch = gr.Radio( |
|
label=i18n("Pitch extraction algorithm"), |
|
info=i18n( |
|
"Pitch extraction algorithm to use for the audio conversion. The default algorithm is rmvpe, which is recommended for most cases." |
|
), |
|
choices=[ |
|
"crepe", |
|
"crepe-tiny", |
|
"rmvpe", |
|
"fcpe", |
|
"hybrid[rmvpe+fcpe]", |
|
], |
|
value="rmvpe", |
|
interactive=True, |
|
) |
|
embedder_model_batch = gr.Radio( |
|
label=i18n("Embedder Model"), |
|
info=i18n("Model used for learning speaker embedding."), |
|
choices=[ |
|
"contentvec", |
|
"japanese-hubert-base", |
|
"chinese-hubert-large", |
|
"custom", |
|
], |
|
value="contentvec", |
|
interactive=True, |
|
) |
|
f0_file_batch = gr.File( |
|
label=i18n( |
|
"The f0 curve represents the variations in the base frequency of a voice over time, showing how pitch rises and falls." |
|
), |
|
visible=True, |
|
) |
|
with gr.Column(visible=False) as embedder_custom_batch: |
|
with gr.Accordion(i18n("Custom Embedder"), open=True): |
|
embedder_upload_custom_batch = gr.File( |
|
label=i18n("Upload Custom Embedder"), |
|
type="filepath", |
|
interactive=True, |
|
) |
|
embedder_custom_refresh_batch = gr.Button(i18n("Refresh")) |
|
embedder_model_custom_batch = gr.Dropdown( |
|
label=i18n("Custom Embedder"), |
|
info=i18n( |
|
"Select the custom embedder to use for the conversion." |
|
), |
|
choices=sorted(custom_embedders), |
|
interactive=True, |
|
allow_custom_value=True, |
|
) |
|
|
|
convert_button2 = gr.Button(i18n("Convert")) |
|
|
|
with gr.Row(): |
|
vc_output3 = gr.Textbox( |
|
label=i18n("Output Information"), |
|
info=i18n("The output information will be displayed here."), |
|
) |
|
|
|
def toggle_visible(checkbox): |
|
return {"visible": checkbox, "__type__": "update"} |
|
|
|
def toggle_visible_hop_length(f0_method): |
|
if f0_method == "crepe" or f0_method == "crepe-tiny": |
|
return {"visible": True, "__type__": "update"} |
|
return {"visible": False, "__type__": "update"} |
|
|
|
def toggle_visible_embedder_custom(embedder_model): |
|
if embedder_model == "custom": |
|
return {"visible": True, "__type__": "update"} |
|
return {"visible": False, "__type__": "update"} |
|
|
|
clean_audio.change( |
|
fn=toggle_visible, |
|
inputs=[clean_audio], |
|
outputs=[clean_strength], |
|
) |
|
clean_audio_batch.change( |
|
fn=toggle_visible, |
|
inputs=[clean_audio_batch], |
|
outputs=[clean_strength_batch], |
|
) |
|
f0_method.change( |
|
fn=toggle_visible_hop_length, |
|
inputs=[f0_method], |
|
outputs=[hop_length], |
|
) |
|
f0_method_batch.change( |
|
fn=toggle_visible_hop_length, |
|
inputs=[f0_method_batch], |
|
outputs=[hop_length_batch], |
|
) |
|
refresh_button.click( |
|
fn=change_choices, |
|
inputs=[], |
|
outputs=[ |
|
model_file, |
|
index_file, |
|
audio, |
|
embedder_model_custom, |
|
embedder_model_custom_batch, |
|
], |
|
) |
|
audio.change( |
|
fn=output_path_fn, |
|
inputs=[audio], |
|
outputs=[output_path], |
|
) |
|
upload_audio.upload( |
|
fn=save_to_wav2, |
|
inputs=[upload_audio], |
|
outputs=[audio, output_path], |
|
) |
|
upload_audio.stop_recording( |
|
fn=save_to_wav, |
|
inputs=[upload_audio], |
|
outputs=[audio, output_path], |
|
) |
|
clear_outputs_infer.click( |
|
fn=delete_outputs, |
|
inputs=[], |
|
outputs=[], |
|
) |
|
clear_outputs_batch.click( |
|
fn=delete_outputs, |
|
inputs=[], |
|
outputs=[], |
|
) |
|
embedder_model.change( |
|
fn=toggle_visible_embedder_custom, |
|
inputs=[embedder_model], |
|
outputs=[embedder_custom], |
|
) |
|
embedder_upload_custom.upload( |
|
fn=save_drop_custom_embedder, |
|
inputs=[embedder_upload_custom], |
|
outputs=[embedder_upload_custom], |
|
) |
|
embedder_custom_refresh.click( |
|
fn=change_choices, |
|
inputs=[], |
|
outputs=[ |
|
model_file, |
|
index_file, |
|
audio, |
|
embedder_model_custom, |
|
embedder_model_custom_batch, |
|
], |
|
) |
|
embedder_model_batch.change( |
|
fn=toggle_visible_embedder_custom, |
|
inputs=[embedder_model_batch], |
|
outputs=[embedder_custom_batch], |
|
) |
|
embedder_upload_custom_batch.upload( |
|
fn=save_drop_custom_embedder, |
|
inputs=[embedder_upload_custom_batch], |
|
outputs=[embedder_upload_custom_batch], |
|
) |
|
embedder_custom_refresh_batch.click( |
|
fn=change_choices, |
|
inputs=[], |
|
outputs=[ |
|
model_file, |
|
index_file, |
|
audio, |
|
embedder_model_custom, |
|
embedder_model_custom_batch, |
|
], |
|
) |
|
convert_button1.click( |
|
fn=run_infer_script, |
|
inputs=[ |
|
pitch, |
|
filter_radius, |
|
index_rate, |
|
rms_mix_rate, |
|
protect, |
|
hop_length, |
|
f0_method, |
|
audio, |
|
output_path, |
|
model_file, |
|
index_file, |
|
split_audio, |
|
autotune, |
|
clean_audio, |
|
clean_strength, |
|
export_format, |
|
upscale_audio, |
|
f0_file, |
|
embedder_model, |
|
embedder_model_custom, |
|
], |
|
outputs=[vc_output1, vc_output2], |
|
) |
|
convert_button2.click( |
|
fn=run_batch_infer_script, |
|
inputs=[ |
|
pitch_batch, |
|
filter_radius_batch, |
|
index_rate_batch, |
|
rms_mix_rate_batch, |
|
protect_batch, |
|
hop_length_batch, |
|
f0_method_batch, |
|
input_folder_batch, |
|
output_folder_batch, |
|
model_file, |
|
index_file, |
|
split_audio_batch, |
|
autotune_batch, |
|
clean_audio_batch, |
|
clean_strength_batch, |
|
export_format_batch, |
|
upscale_audio_batch, |
|
f0_file_batch, |
|
embedder_model_batch, |
|
embedder_model_custom_batch, |
|
], |
|
outputs=[vc_output3], |
|
) |
|
|
