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import gradio as gr | |
import requests | |
import random | |
import os | |
import zipfile | |
import librosa | |
import time | |
from infer_rvc_python import BaseLoader | |
from pydub import AudioSegment | |
from tts_voice import tts_order_voice | |
import edge_tts | |
import tempfile | |
from audio_separator.separator import Separator | |
from animalesepy import * | |
import model_handler | |
import psutil | |
import cpuinfo | |
import re | |
import numpy as np | |
import wave | |
language_dict = tts_order_voice | |
from blaise import * | |
try: | |
import spaces | |
spaces_status = True | |
except ImportError: | |
spaces_status = False | |
separator = Separator() | |
converter = BaseLoader(only_cpu=True, hubert_path=None, rmvpe_path=None) | |
global pth_file | |
global index_file | |
pth_file = "model.pth" | |
index_file = "model.index" | |
#CONFIGS | |
TEMP_DIR = "temp" | |
MODEL_PREFIX = "model" | |
PITCH_ALGO_OPT = [ | |
"pm", | |
"harvest", | |
"crepe", | |
"rmvpe", | |
"rmvpe+", | |
] | |
MODELS = [ | |
{"model": "model.pth", "index": "model.index", "model_name": "Test Model"}, | |
] | |
os.makedirs(TEMP_DIR, exist_ok=True) | |
def unzip_file(file): | |
filename = os.path.basename(file).split(".")[0] | |
with zipfile.ZipFile(file, 'r') as zip_ref: | |
zip_ref.extractall(os.path.join(TEMP_DIR, filename)) | |
return True | |
def progress_bar(total, current): | |
return "[" + "=" * int(current / total * 20) + ">" + " " * (20 - int(current / total * 20)) + "] " + str(int(current / total * 100)) + "%" | |
def contains_bad_word(text, bad_words): | |
text_lower = text.lower() | |
for word in bad_words: | |
if word.lower() in text_lower: | |
return True | |
return False | |
bad_words = ['puttana', 'whore', 'badword3', 'badword4'] | |
class BadWordError(Exception): | |
def __init__(self, msg): | |
super().__init__(msg) | |
self.word = word | |
def download_from_url(url, name=None): | |
if name is None: | |
raise ValueError("The model name must be provided") | |
if "/blob/" in url: | |
url = url.replace("/blob/", "/resolve/") | |
if "huggingface" not in url: | |
return ["The URL must be from huggingface", "Failed", "Failed"] | |
if contains_bad_word(url, bad_words): | |
return BadWordError("The file url has a bad word.") | |
if contains_bad_word(name, bad_words): | |
return BadWordError("The file name has a bad word.") | |
filename = os.path.join(TEMP_DIR, MODEL_PREFIX + str(random.randint(1, 1000)) + ".zip") | |
response = requests.get(url) | |
total = int(response.headers.get('content-length', 0)) | |
if total > 500000000: | |
return ["The file is too large. You can only download files up to 500 MB in size.", "Failed", "Failed"] | |
current = 0 | |
with open(filename, "wb") as f: | |
for data in response.iter_content(chunk_size=4096): | |
f.write(data) | |
current += len(data) | |
print(progress_bar(total, current), end="\r") # | |
try: | |
unzip_file(filename) | |
except Exception as e: | |
return ["Failed to unzip the file", "Failed", "Failed"] | |
unzipped_dir = os.path.join(TEMP_DIR, os.path.basename(filename).split(".")[0]) | |
pth_files = [] | |
index_files = [] | |
for root, dirs, files in os.walk(unzipped_dir): | |
for file in files: | |
if file.endswith(".pth"): | |
pth_files.append(os.path.join(root, file)) | |
elif file.endswith(".index"): | |
index_files.append(os.path.join(root, file)) | |
print(pth_files, index_files) | |
global pth_file | |
global index_file | |
pth_file = pth_files[0] | |
index_file = index_files[0] | |
print(pth_file) | |
print(index_file) | |
if name == "": | |
name = pth_file.split(".")[0] | |
MODELS.append({"model": pth_file, "index": index_file, "model_name": name}) | |
return ["Downloaded as " + name, pth_files[0], index_files[0]] | |
def inference(audio, model_name): | |
output_data = inf_handler(audio, model_name) | |
vocals = output_data[0] | |
inst = output_data[1] | |
return vocals, inst | |
if spaces_status: | |
def convert_now(audio_files, random_tag, converter): | |
return converter( | |
audio_files, | |
random_tag, | |
overwrite=False, | |
parallel_workers=8 | |
) | |
else: | |
def convert_now(audio_files, random_tag, converter): | |
return converter( | |
audio_files, | |
random_tag, | |
overwrite=False, | |
parallel_workers=8 | |
) | |
def run( | |
model, | |
audio_files, | |
pitch_alg, | |
pitch_lvl, | |
index_inf, | |
r_m_f, | |
e_r, | |
c_b_p, | |
): | |
if not audio_files: | |
raise ValueError("The audio pls") | |
if isinstance(audio_files, str): | |
audio_files = [audio_files] | |
try: | |
duration_base = librosa.get_duration(filename=audio_files[0]) | |
print("Duration:", duration_base) | |
except Exception as e: | |
print(e) | |
random_tag = "USER_"+str(random.randint(10000000, 99999999)) | |
file_m = model | |
print("File model:", file_m) | |
# get from MODELS | |
for model in MODELS: | |
if model["model_name"] == file_m: | |
print(model) | |
file_m = model["model"] | |
file_index = model["index"] | |
break | |
if not file_m.endswith(".pth"): | |
raise ValueError("The model file must be a .pth file") | |
print("Random tag:", random_tag) | |
print("File model:", file_m) | |
print("Pitch algorithm:", pitch_alg) | |
print("Pitch level:", pitch_lvl) | |
print("File index:", file_index) | |
print("Index influence:", index_inf) | |
print("Respiration median filtering:", r_m_f) | |
print("Envelope ratio:", e_r) | |
converter.apply_conf( | |
tag=random_tag, | |
file_model=file_m, | |
pitch_algo=pitch_alg, | |
pitch_lvl=pitch_lvl, | |
file_index=file_index, | |
index_influence=index_inf, | |
respiration_median_filtering=r_m_f, | |
envelope_ratio=e_r, | |
consonant_breath_protection=c_b_p, | |
resample_sr=44100 if audio_files[0].endswith('.mp3') else 0, | |
) | |
time.sleep(0.1) | |
result = convert_now(audio_files, random_tag, converter) | |
print("Result:", result) | |
return result[0] | |
def upload_model(index_file, pth_file, model_name): | |
pth_file = pth_file.name | |
index_file = index_file.name | |
MODELS.append({"model": pth_file, "index": index_file, "model_name": model_name}) | |
return "Uploaded!" | |
with gr.Blocks(theme=secret, title="Animalese RVC 🔶") as app: | |
gr.Markdown("## Animalese RVC 🔶") | |
gr.Markdown("**this project is forked of Ilaria RVC!**") | |
with gr.Tab("Inference"): | |
text_input = gr.Textbox(label="Input Text", placeholder="Enter text to convert to Animalese") | |
shorten_input = gr.Checkbox(label="Shorten Words") | |
pitch_input = gr.Slider(minimum=0.2, maximum=2.0, step=0.1, value=1.0, label="Pitch", visible=False) | |
sound_gui = gr.Audio(type="filepath",autoplay=False,visible=True) | |
def update(): | |
print(MODELS) | |
return gr.Dropdown(label="Model",choices=[model["model_name"] for model in MODELS],visible=True,interactive=True, value=MODELS[0]["model_name"],) | |
with gr.Row(): | |
models_dropdown = gr.Dropdown(label="Model",choices=[model["model_name"] for model in MODELS],visible=True,interactive=True, value=MODELS[0]["model_name"],) | |
pitch_lvl_conf = gr.Slider(label="Pitch level (lower -> 'male' while higher -> 'female')",minimum=-12,maximum=12,step=1,value=0,visible=True,interactive=True,) | |
with gr.Accordion("Settings", open=False, visible=False): | |
pitch_algo_conf = gr.Dropdown(PITCH_ALGO_OPT,value=PITCH_ALGO_OPT[4],label="Pitch algorithm",visible=True,interactive=True,) | |
index_inf_conf = gr.Slider(minimum=0,maximum=1,label="Index influence -> How much accent is applied",value=0.75,) | |
respiration_filter_conf = gr.Slider(minimum=0,maximum=7,label="Respiration median filtering",value=3,step=1,interactive=True,) | |
envelope_ratio_conf = gr.Slider(minimum=0,maximum=1,label="Envelope ratio",value=0.25,interactive=True,) | |
consonant_protec_conf = gr.Slider(minimum=0,maximum=0.5,label="Consonant breath protection",value=0.5,interactive=True,) | |
with gr.Group(): | |
refresh_button = gr.Button("1. Refresh Models") | |
preview_button = gr.Button("2. Preview!") | |
button_conf = gr.Button("3. Convert",variant="primary",) | |
output_conf = gr.Audio(type="filepath",label="Output",) | |
refresh_button.click(update, outputs=[models_dropdown]) | |
preview_button.click(fn=lambda text, shorten, pitch: preview_audio(generate_audio(text, shorten, pitch)), | |
inputs=[text_input, shorten_input, pitch_input], | |
outputs=sound_gui) | |
button_conf.click(lambda :None, None, output_conf) | |
button_conf.click( | |
run, | |
inputs=[ | |
models_dropdown, | |
sound_gui, | |
pitch_algo_conf, | |
pitch_lvl_conf, | |
index_inf_conf, | |
respiration_filter_conf, | |
envelope_ratio_conf, | |
consonant_protec_conf, | |
], | |
outputs=[output_conf], | |
) | |
with gr.Tab("Model Loader (Download and Upload)"): | |
with gr.Accordion("Model Downloader", open=False): | |
gr.Markdown( | |
"Download the model from the following URL and upload it here. (Huggingface RVC model)" | |
) | |
model = gr.Textbox(lines=1, label="Model URL") | |
name = gr.Textbox(lines=1, label="Model Name", placeholder="Model Name") | |
download_button = gr.Button("Download Model") | |
status = gr.Textbox(lines=1, label="Status", placeholder="Waiting....", interactive=False) | |
model_pth = gr.Textbox(lines=1, label="Model pth file", placeholder="Waiting....", interactive=False) | |
index_pth = gr.Textbox(lines=1, label="Index pth file", placeholder="Waiting....", interactive=False) | |
download_button.click(download_from_url, [model, name], outputs=[status, model_pth, index_pth]) | |
with gr.Accordion("Upload A Model", open=False): | |
index_file_upload = gr.File(label="Index File (.index)") | |
pth_file_upload = gr.File(label="Model File (.pth)") | |
model_name = gr.Textbox(label="Model Name", placeholder="Model Name") | |
upload_button = gr.Button("Upload Model") | |
upload_status = gr.Textbox(lines=1, label="Status", placeholder="Waiting....", interactive=False) | |
upload_button.click(upload_model, [index_file_upload, pth_file_upload, model_name], upload_status) | |
with gr.Tab("Credits"): | |
gr.Markdown( | |
""" | |
Animalese RVC made by [Blane187](https://huggingface.co/Blane187) | |
Ilaria RVC made by [Ilaria](https://huggingface.co/TheStinger) suport her on [ko-fi](https://ko-fi.com/ilariaowo) | |
The modules made by [r3gm](https://huggingface.co/r3gm) | |
made with ❤️ by [mikus](https://github.com/cappuch) - made the ui! | |
""" | |
) | |
with gr.Tab(("")): | |
gr.Markdown(''' | |
![ilaria](https://i.ytimg.com/vi/5PWqt2Wg-us/maxresdefault.jpg) | |
''') | |
app.queue(api_open=False).launch(show_api=False) | |