Spaces:
Build error
Build error
| import io | |
| import shlex | |
| from io import BytesIO | |
| import gradio as gr | |
| import librosa | |
| import numpy as np | |
| import soundfile | |
| from inference import slicer | |
| from inference.infer_tool import Svc | |
| import logging | |
| from logmmse import logmmse | |
| from typing import Tuple | |
| import time | |
| import requests | |
| import os,json | |
| from subprocess import getoutput | |
| from urllib.parse import quote | |
| logging.getLogger('numba').setLevel(logging.WARNING) | |
| model_sing = "./G_2000.pth" | |
| #model_talk = "logs/32k/talk1.pth" | |
| config_name = "./config.json" | |
| sid_map ={"chiya":"./chiya.pth","koyomi":"./koyomi.pth","yuki":"./yuki.pth","plw":"./plw.pth","vik":"./vik.pth"} | |
| os.system('chmod +x ./pget') | |
| class YukieGradio: | |
| def __init__(self): | |
| self.UI = gr.Blocks() | |
| with self.UI: | |
| with gr.Tabs(): | |
| with gr.TabItem("Basic"): | |
| gr.Markdown(value=""" | |
| 偷的界面，参考LICENSE """) | |
| self.sid = gr.Dropdown(label="音色", choices=["chiya","koyomi","yuki","plw","vik"], value="yuki", interactive=True) | |
| self.dev = gr.Dropdown(label="设备（云端一般请勿切换，使用默认值即可）", choices=[ | |
| "cuda", "cpu"], value="cpu", interactive=True) | |
| self.inMic = gr.Textbox(label='url(@start)') | |
| self.inAudio = gr.Audio(label="or 上传音频") | |
| self.needLogmmse = gr.Checkbox(label="是否使用自带降噪") | |
| self.slice_db = gr.Slider(label="切片阈值(较嘈杂时-30，保留呼吸声时-50，一般默认-40)", | |
| maximum=0, minimum=-60, step=1, value=-40) | |
| self.vcTransform = gr.Number( | |
| label="升降调（整数，可以正负，半音数量，升高八度就是12）", value=0) | |
| self.vcSubmit = gr.Button("转换", variant="primary") | |
| self.outVcText = gr.Textbox( | |
| label="音高平均偏差半音数量，体现转换音频的跑调情况（一般小于0.5）") | |
| self.outAudio = gr.Audio( | |
| type="numpy", label="Output Audio") | |
| self.f0_image = gr.Image( | |
| label="f0曲线，蓝色为输入音高，橙色为合成音频的音高（代码有误差）") | |
| gr.Markdown(value=""" | |
| ## 注意 | |
| 如果要在本地使用该demo，请使用 `git lfs clone https://huggingface.co/spaces/yukie/yukie-sovits3`克隆该仓库([简单教程](https://huggingface.co/spaces/yukie/yukie-sovits3/edit/main/local.md)) | |
| """) | |
| self.vcSubmit.click(infer, inputs=[self.inMic, self.inAudio, self.vcTransform, self.slice_db, self.needLogmmse, self.sid, self.dev], outputs=[ | |
| self.outVcText, self.outAudio, self.f0_image],api_name="go") | |
| def download_audio(url): | |
| # 下载音频数据 | |
| response = requests.get(url) | |
| audio_bytes = BytesIO(response.content) | |
| # 转换音频格式为wav | |
| y, sr = librosa.load(audio_bytes, sr=None) | |
| with BytesIO() as wav_bytes: | |
| soundfile.write(wav_bytes, y, sr, format='wav') | |
| wav_bytes.seek(0) | |
| # 读取wav文件 | |
| data, sr = soundfile.read(wav_bytes) | |
| # 转换数据类型为int16 | |
| data = np.asarray(data * 32767, dtype=np.int16) | |
| return sr, data | |
| def downloadTubeUpload(query): | |
| pquery=shlex.quote(query.split('@')[0]) | |
| proxy=os.environ['proxy'] | |
| os.system('chmod +x ./yt-dlp') | |
| os.system(f'./yt-dlp -f worstaudio* -o "temp.mp4" --force-overwrites --no-playlist --concurrent-fragments 4 --proxy "{proxy}" {pquery}') | |
| upload_url = "https://lalal.ai/api/upload/" | |
| headers = { | |
| "Content-Disposition": f"attachment; filename=video_id.mp4" | |
| } | |
| result = os.popen('ffprobe -v error -show_entries format=duration -of default=noprint_wrappers=1:nokey=1 temp.mp4') | |
| duration = float(result.read().strip()) | |
| # 计算需要截取的时间区间 | |
| start_time = max(0, (duration) / 2) | |
| if len(query.split('@'))==2: | |
| start_time=int(query.split('@')[-1]) | |
| end_time = start_time + 60 | |
| # 使用ffmpeg进行截取 | |
| os.system(f'ffmpeg -i temp.mp4 -ss {start_time} -t 60 -c copy output.mp4') | |
| command= f'curl --url https://www.lalal.ai/api/upload/ --data-binary @output.mp4 --header "Content-Disposition: attachment; filename=output.mp4" -s' | |
| moutput=getoutput(command) | |
| print(moutput) | |
| upload_response=json.loads(moutput) | |
| return upload_response.get("id") | |
| def split_file(file_id): | |
| command = f'rm temp.mp4' | |
| os.system(command) | |
| command = f'rm output.mp4' | |
| os.system(command) | |
| url_for_split = "https://www.lalal.ai/api/preview/" | |
| headers = { | |
| 'accept': 'application/json, text/plain, */*', | |
| 'accept-language': 'zh-CN,zh;q=0.9,en;q=0.8,en-GB;q=0.7,en-US;q=0.6', | |
| 'dnt': '1', | |
| 'origin': 'https://www.lalal.ai', | |
| 'priority': 'u=1, i', | |
| 'referer': 'https://www.lalal.ai/', | |
| 'sec-ch-ua': '"Not/A)Brand";v="8", "Chromium";v="126", "Microsoft Edge";v="126"', | |
| 'sec-ch-ua-mobile': '?0', | |
| 'sec-ch-ua-platform': '"Windows"', | |
| 'sec-fetch-dest': 'empty', | |
| 'sec-fetch-mode': 'cors', | |
| 'sec-fetch-site': 'same-origin', | |
| 'sentry-trace': 'efee9c07725645dc896a8be5ace08ba4-87568d216d25918a-0', | |
| 'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36 Edg/126.0.0.0', | |
| 'x-csrftoken': 'ytk6iENZ6uT71lFQ6NgAPBGvwUt6A2Xi', | |
| 'x-request-id': 'lalalai' | |
| } | |
| query_args = {'id': file_id, 'stem': "vocals",'dereverb_enabled':True} | |
| response = requests.post(url_for_split, data=query_args,headers=headers)# | |
| split_result = response.json() | |
| if split_result["status"] == "error": | |
| print(split_result["error"]) | |
| raise RuntimeError('split err') | |
| def check_file(file_id): | |
| url_for_check = "https://www.lalal.ai/api/check/" | |
| query_args = {'id': file_id} | |
| is_queueup = False | |
| while True: | |
| response = requests.get(url_for_check, params=query_args) | |
| check_result = response.json() | |
| if check_result["status"] == "error": | |
| raise RuntimeError(check_result["error"]) | |
| task_state = check_result["task"]["state"] | |
| if task_state == "error": | |
| raise RuntimeError(check_result["task"]["error"]) | |
| if task_state == "progress": | |
| progress = int(check_result["task"]["progress"]) | |
| if progress == 0 and not is_queueup: | |
| print("Queue up...") | |
| is_queueup = True | |
| elif progress > 0: | |
| print(f"Progress: {progress}%") | |
| if task_state == "success": | |
| stem_track_url = check_result["preview"]["stem_track"] | |
| back_track_url = check_result["preview"]["back_track"] | |
| return stem_track_url, back_track_url | |
| time.sleep(30) | |
| def infer(inMic, inAudio, transform, slice_db, lm, sid, dev): | |
| if inAudio != None: | |
| sampling_rate, inaudio = inAudio | |
| else: | |
| if inMic != None: | |
| id=downloadTubeUpload(inMic) | |
| split_file(id) | |
| sampling_rate, inaudio=download_audio(check_file(id)[0]) | |
| else: | |
| return "请上传一段音频后再次尝试", None | |
| print("start inference") | |
| start_time = time.time() | |
| # 预处理，重编码 | |
| inaudio = (inaudio / np.iinfo(inaudio.dtype).max).astype(np.float32) | |
| if len(inaudio.shape) > 1: | |
| inaudio = librosa.to_mono(inaudio.transpose(1, 0)) | |
| if sampling_rate != 32000: | |
| inaudio = librosa.resample( | |
| inaudio, orig_sr=sampling_rate, target_sr=32000) | |
| if lm: | |
| inaudio = logmmse(inaudio, 32000) | |
| ori_wav_path = "tmp_ori.wav" | |
| soundfile.write(ori_wav_path, inaudio, 32000, format="wav") | |
| chunks = slicer.cut(ori_wav_path, db_thresh=slice_db) | |
| audio_data, audio_sr = slicer.chunks2audio(ori_wav_path, chunks) | |
| audio = [] | |
| sid = sid_map[sid] | |
| if sid!=None: | |
| svc_model = Svc(sid, config_name, dev=dev) | |
| #sid is model path now | |
| for (slice_tag, data) in audio_data: | |
| length = int(np.ceil(len(data) / audio_sr * svc_model.target_sample)) | |
| raw_path = io.BytesIO() | |
| soundfile.write(raw_path, data, audio_sr, format="wav") | |
| raw_path.seek(0) | |
| if slice_tag: | |
| _audio = np.zeros(length) | |
| else: | |
| out_audio, out_str = svc_model.infer(0, transform, raw_path) | |
| _audio = out_audio.cpu().numpy() | |
| audio.extend(list(_audio)) | |
| audio = (np.array(audio) * 32768.0).astype('int16') | |
| used_time = time.time() - start_time | |
| out_wav_path = "tmp.wav" | |
| soundfile.write(out_wav_path, audio, 32000, format="wav") | |
| mistake, var = svc_model.calc_error(ori_wav_path, out_wav_path, transform) | |
| out_picture = svc_model.f0_plt(ori_wav_path, out_wav_path, transform) | |
| out_str = ("Success! total use time:{}s\n半音偏差:{}\n半音方差:{}".format( | |
| used_time, mistake, var)) | |
| return out_str, (32000, audio), "temp.jpg" | |
| if __name__ == "__main__": | |
| app = YukieGradio() | |
| app.UI.launch() | |