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import os, subprocess
import gradio as gr
import shutil, time, torch, gc
from mega import Mega
from datetime import datetime
import pandas as pd
import os, sys, subprocess, numpy as np
from pydub import AudioSegment
# Class to handle caching model urls from a spreadsheet
class CachedModels:
def __init__(self):
csv_url = "https://docs.google.com/spreadsheets/d/1tAUaQrEHYgRsm1Lvrnj14HFHDwJWl0Bd9x0QePewNco/export?format=csv&gid=1977693859"
if os.path.exists("spreadsheet.csv"):
self.cached_data = pd.read_csv("spreadsheet.csv")
else:
self.cached_data = pd.read_csv(csv_url)
self.cached_data.to_csv("spreadsheet.csv", index=False)
# Cache model urls
self.models = {}
for _, row in self.cached_data.iterrows():
filename = row['Filename']
url = None
for value in row.values:
if isinstance(value, str) and "huggingface" in value:
url = value
break
if url:
self.models[filename] = url
# Get cached model urls
def get_models(self):
return self.models
def show(path,ext,on_error=None):
try:
return list(filter(lambda x: x.endswith(ext), os.listdir(path)))
except:
return on_error
def run_subprocess(command):
try:
subprocess.run(command, check=True)
return True, None
except Exception as e:
return False, e
def download_from_url(url=None, model=None):
if not url:
try:
url = model[f'{model}']
except:
gr.Warning("Failed")
return ''
if model == '':
try:
model = url.split('/')[-1].split('?')[0]
except:
gr.Warning('Please name the model')
return
model = model.replace('.pth', '').replace('.index', '').replace('.zip', '')
url = url.replace('/blob/main/', '/resolve/main/').strip()
for directory in ["downloads", "unzips","zip"]:
#shutil.rmtree(directory, ignore_errors=True)
os.makedirs(directory, exist_ok=True)
try:
if url.endswith('.pth'):
subprocess.run(["wget", url, "-O", f'assets/weights/{model}.pth'])
elif url.endswith('.index'):
os.makedirs(f'logs/{model}', exist_ok=True)
subprocess.run(["wget", url, "-O", f'logs/{model}/added_{model}.index'])
elif url.endswith('.zip'):
subprocess.run(["wget", url, "-O", f'downloads/{model}.zip'])
else:
if "drive.google.com" in url:
url = url.split('/')[0]
subprocess.run(["gdown", url, "--fuzzy", "-O", f'downloads/{model}'])
elif "mega.nz" in url:
Mega().download_url(url, 'downloads')
else:
subprocess.run(["wget", url, "-O", f'downloads/{model}'])
downloaded_file = next((f for f in os.listdir("downloads")), None)
if downloaded_file:
if downloaded_file.endswith(".zip"):
shutil.unpack_archive(f'downloads/{downloaded_file}', "unzips", 'zip')
for root, _, files in os.walk('unzips'):
for file in files:
file_path = os.path.join(root, file)
if file.endswith(".index"):
os.makedirs(f'logs/{model}', exist_ok=True)
shutil.copy2(file_path, f'logs/{model}')
elif file.endswith(".pth") and "G_" not in file and "D_" not in file:
shutil.copy(file_path, f'assets/weights/{model}.pth')
elif downloaded_file.endswith(".pth"):
shutil.copy(f'downloads/{downloaded_file}', f'assets/weights/{model}.pth')
elif downloaded_file.endswith(".index"):
os.makedirs(f'logs/{model}', exist_ok=True)
shutil.copy(f'downloads/{downloaded_file}', f'logs/{model}/added_{model}.index')
else:
gr.Warning("Failed to download file")
return 'Failed'
gr.Info("Done")
except Exception as e:
gr.Warning(f"There's been an error: {str(e)}")
finally:
shutil.rmtree("downloads", ignore_errors=True)
shutil.rmtree("unzips", ignore_errors=True)
shutil.rmtree("zip", ignore_errors=True)
return 'Done'
def speak(audio, text):
print(f"({audio}, {text})")
current_dir = os.getcwd()
os.chdir('./gpt_sovits_demo')
process = subprocess.Popen([
"python", "./zero.py",
"--input_file", audio,
"--audio_lang", "English",
"--text", text,
"--text_lang", "English"
], stdout=subprocess.PIPE, text=True)
for line in process.stdout:
line = line.strip()
if "All keys matched successfully" in line:
continue
if line.startswith("(") and line.endswith(")"):
path, finished = line[1:-1].split(", ")
if finished:
os.chdir(current_dir)
return path
os.chdir(current_dir)
return None
def stereo_process(audio1,audio2,choice):
audio = audio1 if choice == "Input" else audio2
print(audio)
sample_rate, audio_array = audio
if len(audio_array.shape) == 1:
audio_bytes = audio_array.tobytes()
segment = AudioSegment(
data=audio_bytes,
sample_width=audio_array.dtype.itemsize, # 2 bytes for int16
frame_rate=sample_rate, # Use the sample rate from your tuple
channels=1 # Adjust if your audio has more channels
)
samples = np.array(segment.get_array_of_samples())
delay_samples = int(segment.frame_rate * (0.6 / 1000.0))
left_channel = np.zeros_like(samples)
right_channel = samples
left_channel[delay_samples:] = samples[:-delay_samples]
stereo_samples = np.column_stack((left_channel, right_channel))
return (sample_rate, stereo_samples.astype(np.int16))
else:
return audio
def split_audio(input_file, output_folder, chunk_duration=5.12):
os.makedirs(output_folder, exist_ok=True)
ffmpeg_command = f"ffmpeg -i {input_file} -f segment -segment_time {chunk_duration} -c:a pcm_s16le {output_folder}/out%03d.wav"
subprocess.run(ffmpeg_command, shell=True, check=True)
def create_file_list(output_folder):
file_list = os.path.join(output_folder, "file_list.txt")
with open(file_list, "w") as f:
for filename in sorted(os.listdir(output_folder)):
if filename.endswith(".wav"):
f.write(os.path.join(output_folder, filename) + "\n")
return file_list
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