surfmore/SimpleRVC

1import zipfile2import hashlib3from utils.model import model_downloader, get_model4import requests5import json6import torch7import os8from inference import Inference9import gradio as gr10from constants import VOICE_METHODS, BARK_VOICES, EDGE_VOICES, zips_folder, unzips_folder11from tts.conversion import tts_infer, ELEVENLABS_VOICES_RAW, ELEVENLABS_VOICES_NAMES12 13api_url = "https://rvc-models-api.onrender.com/uploadfile/"14 15if not os.path.exists(zips_folder):16      os.mkdir(zips_folder)17if not os.path.exists(unzips_folder):18  os.mkdir(unzips_folder)19           20def get_info(path):21    path = os.path.join(unzips_folder, path)22    try:23        a = torch.load(path, map_location="cpu")24        return a25    except Exception as e:26        print("*****************eeeeeeeeeeeeeeeeeeeerrrrrrrrrrrrrrrrrr*****")27        print(e)28        return {29 30        }31def calculate_md5(file_path):32    hash_md5 = hashlib.md5()33    with open(file_path, "rb") as f:34        for chunk in iter(lambda: f.read(4096), b""):35            hash_md5.update(chunk)36    return hash_md5.hexdigest()37 38def compress(modelname, files):39    file_path = os.path.join(zips_folder, f"{modelname}.zip")40    # Select the compression mode ZIP_DEFLATED for compression41    # or zipfile.ZIP_STORED to just store the file42    compression = zipfile.ZIP_DEFLATED43 44    # Comprueba si el archivo ZIP ya existe45    if not os.path.exists(file_path):46        # Si no existe, crea el archivo ZIP47        with zipfile.ZipFile(file_path, mode="w") as zf:48            try:49                for file in files:50                    if file:51                        # Agrega el archivo al archivo ZIP52                        zf.write(unzips_folder if ".index" in file else os.path.join(unzips_folder, file), compress_type=compression)53            except FileNotFoundError as fnf:54                print("An error occurred", fnf)55    else:56        # Si el archivo ZIP ya existe, agrega los archivos a un archivo ZIP existente57        with zipfile.ZipFile(file_path, mode="a") as zf:58            try:59                for file in files:60                    if file:61                        # Agrega el archivo al archivo ZIP62                         zf.write(unzips_folder if ".index" in file else os.path.join(unzips_folder, file), compress_type=compression)63            except FileNotFoundError as fnf:64                print("An error occurred", fnf)65 66    return file_path67 68def infer(model, f0_method, audio_file, index_rate, vc_transform0, protect0, resample_sr1, filter_radius1):69    70    if not model:71        return "No model url specified, please specify a model url.", None72    73    if not audio_file:74        return "No audio file specified, please load an audio file.", None75    76    77    inference = Inference(78        model_name=model,79        f0_method=f0_method,80        source_audio_path=audio_file,81        feature_ratio=index_rate,82        transposition=vc_transform0,83        protection_amnt=protect0,84        resample=resample_sr1,85        harvest_median_filter=filter_radius1,86        output_file_name=os.path.join("./audio-outputs", os.path.basename(audio_file))87    )88    output = inference.run()89    if 'success' in output and output['success']:90        print("Inferencia realizada exitosamente...")91        return output, output['file']92    else:93        print("Fallo en la inferencia...", output)94        return "Failed", None95    96def post_model(name, model_url, version, creator):97    modelname = model_downloader(model_url, zips_folder, unzips_folder)98    model_files = get_model(unzips_folder, modelname)99    100    if not model_files:101        return "No se encontrado un modelo valido, verifica el contenido del enlace e intentalo más tarde."102 103    if not model_files.get('pth'):104        return "No se encontrado un modelo valido, verifica el contenido del enlace e intentalo más tarde."105    106    md5_hash = calculate_md5(os.path.join(unzips_folder,model_files['pth']))107    zipfile = compress(modelname, list(model_files.values()))108    109    a = get_info(model_files.get('pth'))110    file_to_upload = open(zipfile, "rb")111    info = a.get("info", "None"),112    sr = a.get("sr", "None"),113    f0 = a.get("f0", "None"),114    115    data = {116        "name": name,117        "version": version,118        "creator": creator,119        "hash": md5_hash,120        "info": info,121        "sr": sr,122        "f0": f0123    }124    print("Subiendo archivo...")125    # Realizar la solicitud POST126    response = requests.post(api_url, files={"file": file_to_upload}, data=data)127    result = response.json()128    129    # Comprobar la respuesta130    if response.status_code == 200:131        result = response.json()132        return json.dumps(result, indent=4)133    else:134        print("Error al cargar el archivo:", response.status_code)135        return result136        137 138def search_model(name):139    web_service_url = "https://script.google.com/macros/s/AKfycbyRaNxtcuN8CxUrcA_nHW6Sq9G2QJor8Z2-BJUGnQ2F_CB8klF4kQL--U2r2MhLFZ5J/exec"140    response = requests.post(web_service_url, json={141        'type': 'search_by_filename',142        'name': name143    })144    result = []145    response.raise_for_status()  # Lanza una excepción en caso de error146    json_response = response.json()147    cont = 0148    result.append("""| Nombre del modelo | Url | Epoch | Sample Rate |149                  | ---------------- | -------------- |:------:|:-----------:|150                  """)151    yield "<br />".join(result)152    if json_response.get('ok', None):153        for model in json_response['ocurrences']:154            if cont < 20:155                model_name = str(model.get('name', 'N/A')).strip()156                model_url = model.get('url', 'N/A')157                epoch = model.get('epoch', 'N/A')158                sr = model.get('sr', 'N/A')159                line = f"""|{model_name}|<a>{model_url}</a>|{epoch}|{sr}|160                """161                result.append(line)162                yield "".join(result)163            cont += 1164            165def update_tts_methods_voice(select_value):166    if select_value == "Edge-tts":167        return gr.Dropdown.update(choices=EDGE_VOICES, visible=True, value="es-CO-GonzaloNeural-Male"), gr.Markdown.update(visible=False), gr.Textbox.update(visible=False),gr.Radio.update(visible=False)168    elif select_value == "Bark-tts":169        return gr.Dropdown.update(choices=BARK_VOICES, visible=True), gr.Markdown.update(visible=False), gr.Textbox.update(visible=False),gr.Radio.update(visible=False)170    elif select_value == 'ElevenLabs':171        return gr.Dropdown.update(choices=ELEVENLABS_VOICES_NAMES, visible=True, value="Bella"), gr.Markdown.update(visible=True), gr.Textbox.update(visible=True), gr.Radio.update(visible=False)172    elif select_value == 'CoquiTTS':173        return gr.Dropdown.update(visible=False), gr.Markdown.update(visible=False), gr.Textbox.update(visible=False), gr.Radio.update(visible=True)174