UVR-UI / app.py
Eddycrack864's picture
Update app.py
8c8860a verified
raw
history blame
36.6 kB
import os
import re
import random
from scipy.io.wavfile import write
from scipy.io.wavfile import read
import numpy as np
import gradio as gr
import yt_dlp
import subprocess
roformer_models = {
'BS-Roformer-Viperx-1297.ckpt': 'model_bs_roformer_ep_317_sdr_12.9755.ckpt',
'BS-Roformer-Viperx-1296.ckpt': 'model_bs_roformer_ep_368_sdr_12.9628.ckpt',
'BS-Roformer-Viperx-1053.ckpt': 'model_bs_roformer_ep_937_sdr_10.5309.ckpt',
'Mel-Roformer-Viperx-1143.ckpt': 'model_mel_band_roformer_ep_3005_sdr_11.4360.ckpt'
}
mdx23c_models = [
'MDX23C_D1581.ckpt',
'MDX23C-8KFFT-InstVoc_HQ.ckpt',
'MDX23C-8KFFT-InstVoc_HQ_2.ckpt',
]
mdxnet_models = [
'UVR-MDX-NET-Inst_full_292.onnx',
'UVR-MDX-NET_Inst_187_beta.onnx',
'UVR-MDX-NET_Inst_82_beta.onnx',
'UVR-MDX-NET_Inst_90_beta.onnx',
'UVR-MDX-NET_Main_340.onnx',
'UVR-MDX-NET_Main_390.onnx',
'UVR-MDX-NET_Main_406.onnx',
'UVR-MDX-NET_Main_427.onnx',
'UVR-MDX-NET_Main_438.onnx',
'UVR-MDX-NET-Inst_HQ_1.onnx',
'UVR-MDX-NET-Inst_HQ_2.onnx',
'UVR-MDX-NET-Inst_HQ_3.onnx',
'UVR-MDX-NET-Inst_HQ_4.onnx',
'UVR_MDXNET_Main.onnx',
'UVR-MDX-NET-Inst_Main.onnx',
'UVR_MDXNET_1_9703.onnx',
'UVR_MDXNET_2_9682.onnx',
'UVR_MDXNET_3_9662.onnx',
'UVR-MDX-NET-Inst_1.onnx',
'UVR-MDX-NET-Inst_2.onnx',
'UVR-MDX-NET-Inst_3.onnx',
'UVR_MDXNET_KARA.onnx',
'UVR_MDXNET_KARA_2.onnx',
'UVR_MDXNET_9482.onnx',
'UVR-MDX-NET-Voc_FT.onnx',
'Kim_Vocal_1.onnx',
'Kim_Vocal_2.onnx',
'Kim_Inst.onnx',
'Reverb_HQ_By_FoxJoy.onnx',
'UVR-MDX-NET_Crowd_HQ_1.onnx',
'kuielab_a_vocals.onnx',
'kuielab_a_other.onnx',
'kuielab_a_bass.onnx',
'kuielab_a_drums.onnx',
'kuielab_b_vocals.onnx',
'kuielab_b_other.onnx',
'kuielab_b_bass.onnx',
'kuielab_b_drums.onnx',
]
vrarch_models = [
'1_HP-UVR.pth',
'2_HP-UVR.pth',
'3_HP-Vocal-UVR.pth',
'4_HP-Vocal-UVR.pth',
'5_HP-Karaoke-UVR.pth',
'6_HP-Karaoke-UVR.pth',
'7_HP2-UVR.pth',
'8_HP2-UVR.pth',
'9_HP2-UVR.pth',
'10_SP-UVR-2B-32000-1.pth',
'11_SP-UVR-2B-32000-2.pth',
'12_SP-UVR-3B-44100.pth',
'13_SP-UVR-4B-44100-1.pth',
'14_SP-UVR-4B-44100-2.pth',
'15_SP-UVR-MID-44100-1.pth',
'16_SP-UVR-MID-44100-2.pth',
'17_HP-Wind_Inst-UVR.pth',
'UVR-De-Echo-Aggressive.pth',
'UVR-De-Echo-Normal.pth',
'UVR-DeEcho-DeReverb.pth',
'UVR-DeNoise-Lite.pth',
'UVR-DeNoise.pth',
'UVR-BVE-4B_SN-44100-1.pth',
'MGM_HIGHEND_v4.pth',
'MGM_LOWEND_A_v4.pth',
'MGM_LOWEND_B_v4.pth',
'MGM_MAIN_v4.pth',
]
demucs_models = [
'htdemucs_ft.yaml',
'htdemucs.yaml',
'hdemucs_mmi.yaml',
]
output_format = [
'wav',
'flac',
'mp3',
]
mdxnet_overlap_values = [
'0.25',
'0.5',
'0.75',
'0.99',
]
vrarch_window_size_values = [
'320',
'512',
'1024',
]
demucs_overlap_values = [
'0.25',
'0.50',
'0.75',
'0.99',
]
def download_audio(url):
ydl_opts = {
'format': 'bestaudio/best',
'outtmpl': 'ytdl/%(title)s.%(ext)s',
'postprocessors': [{
'key': 'FFmpegExtractAudio',
'preferredcodec': 'wav',
'preferredquality': '192',
}],
}
with yt_dlp.YoutubeDL(ydl_opts) as ydl:
info_dict = ydl.extract_info(url, download=True)
file_path = ydl.prepare_filename(info_dict).rsplit('.', 1)[0] + '.wav'
sample_rate, audio_data = read(file_path)
audio_array = np.asarray(audio_data, dtype=np.int16)
return sample_rate, audio_array
def roformer_separator(roformer_audio, roformer_model, roformer_output_format, roformer_overlap, roformer_segment_size):
files_list = []
files_list.clear()
directory = "./outputs"
random_id = str(random.randint(10000, 99999))
pattern = f"{random_id}"
os.makedirs("outputs", exist_ok=True)
write(f'{random_id}.wav', roformer_audio[0], roformer_audio[1])
full_roformer_model = roformer_models[roformer_model]
prompt = f"audio-separator {random_id}.wav --model_filename {full_roformer_model} --output_dir=./outputs --output_format={roformer_output_format} --normalization=0.9 --mdxc_overlap={roformer_overlap} --mdxc_segment_size={roformer_segment_size}"
os.system(prompt)
for file in os.listdir(directory):
if re.search(pattern, file):
files_list.append(os.path.join(directory, file))
stem1_file = files_list[0]
stem2_file = files_list[1]
return stem1_file, stem2_file
def mdxc_separator(mdx23c_audio, mdx23c_model, mdx23c_output_format, mdx23c_segment_size, mdx23c_overlap, mdx23c_denoise):
files_list = []
files_list.clear()
directory = "./outputs"
random_id = str(random.randint(10000, 99999))
pattern = f"{random_id}"
os.makedirs("outputs", exist_ok=True)
write(f'{random_id}.wav', mdx23c_audio[0], mdx23c_audio[1])
prompt = f"audio-separator {random_id}.wav --model_filename {mdx23c_model} --output_dir=./outputs --output_format={mdx23c_output_format} --normalization=0.9 --mdxc_segment_size={mdx23c_segment_size} --mdxc_overlap={mdx23c_overlap}"
if mdx23c_denoise:
prompt += " --mdx_enable_denoise"
os.system(prompt)
for file in os.listdir(directory):
if re.search(pattern, file):
files_list.append(os.path.join(directory, file))
stem1_file = files_list[0]
stem2_file = files_list[1]
return stem1_file, stem2_file
def mdxnet_separator(mdxnet_audio, mdxnet_model, mdxnet_output_format, mdxnet_segment_size, mdxnet_overlap, mdxnet_denoise):
files_list = []
files_list.clear()
directory = "./outputs"
random_id = str(random.randint(10000, 99999))
pattern = f"{random_id}"
os.makedirs("outputs", exist_ok=True)
write(f'{random_id}.wav', mdxnet_audio[0], mdxnet_audio[1])
prompt = f"audio-separator {random_id}.wav --model_filename {mdxnet_model} --output_dir=./outputs --output_format={mdxnet_output_format} --normalization=0.9 --mdx_segment_size={mdxnet_segment_size} --mdx_overlap={mdxnet_overlap}"
if mdxnet_denoise:
prompt += " --mdx_enable_denoise"
os.system(prompt)
for file in os.listdir(directory):
if re.search(pattern, file):
files_list.append(os.path.join(directory, file))
stem1_file = files_list[0]
stem2_file = files_list[1]
return stem1_file, stem2_file
def vrarch_separator(vrarch_audio, vrarch_model, vrarch_output_format, vrarch_window_size, vrarch_agression, vrarch_tta, vrarch_high_end_process):
files_list = []
files_list.clear()
directory = "./outputs"
random_id = str(random.randint(10000, 99999))
pattern = f"{random_id}"
os.makedirs("outputs", exist_ok=True)
write(f'{random_id}.wav', vrarch_audio[0], vrarch_audio[1])
prompt = f"audio-separator {random_id}.wav --model_filename {vrarch_model} --output_dir=./outputs --output_format={vrarch_output_format} --normalization=0.9 --vr_window_size={vrarch_window_size} --vr_aggression={vrarch_agression}"
if vrarch_tta:
prompt += " --vr_enable_tta"
if vrarch_high_end_process:
prompt += " --vr_high_end_process"
os.system(prompt)
for file in os.listdir(directory):
if re.search(pattern, file):
files_list.append(os.path.join(directory, file))
stem1_file = files_list[0]
stem2_file = files_list[1]
return stem1_file, stem2_file
def demucs_separator(demucs_audio, demucs_model, demucs_output_format, demucs_shifts, demucs_overlap):
files_list = []
files_list.clear()
directory = "./outputs"
random_id = str(random.randint(10000, 99999))
pattern = f"{random_id}"
os.makedirs("outputs", exist_ok=True)
write(f'{random_id}.wav', demucs_audio[0], demucs_audio[1])
prompt = f"audio-separator {random_id}.wav --model_filename {demucs_model} --output_dir=./outputs --output_format={demucs_output_format} --normalization=0.9 --demucs_shifts={demucs_shifts} --demucs_overlap={demucs_overlap}"
os.system(prompt)
for file in os.listdir(directory):
if re.search(pattern, file):
files_list.append(os.path.join(directory, file))
stem1_file = files_list[0]
stem2_file = files_list[1]
stem3_file = files_list[2]
stem4_file = files_list[3]
return stem1_file, stem2_file, stem3_file, stem4_file
def roformer_batch(path_input, path_output, model, output_format, overlap, segment_size):
found_files = []
logs = []
logs.clear()
extensions = (".mp3", ".wav", ".flac")
full_roformer_model = roformer_models[model]
for audio_files in os.listdir(path_input):
if audio_files.endswith(extensions):
found_files.append(audio_files)
total_files = len(found_files)
if total_files == 0:
logs.append("No valid audio files.")
yield "\n".join(logs)
else:
logs.append(f"{total_files} audio files found")
found_files.sort()
for audio_files in found_files:
file_path = os.path.join(path_input, audio_files)
prompt = ["audio-separator", file_path, "-m", f"{full_roformer_model}", f"--output_dir={path_output}", f"--output_format={output_format}", "--normalization=0.9", f"--mdxc_overlap={overlap}", f"--mdxc_segment_size={segment_size}"]
logs.append(f"Processing file: {audio_files}")
yield "\n".join(logs)
subprocess.run(prompt)
logs.append(f"File: {audio_files} processed!")
yield "\n".join(logs)
def mdx23c_batch(path_input, path_output, model, output_format, overlap, segment_size, denoise):
found_files = []
logs = []
logs.clear()
extensions = (".mp3", ".wav", ".flac")
for audio_files in os.listdir(path_input):
if audio_files.endswith(extensions):
found_files.append(audio_files)
total_files = len(found_files)
if total_files == 0:
logs.append("No valid audio files.")
yield "\n".join(logs)
else:
logs.append(f"{total_files} audio files found")
found_files.sort()
for audio_files in found_files:
file_path = os.path.join(path_input, audio_files)
prompt = ["audio-separator", file_path, "-m", f"{model}", f"--output_dir={path_output}", f"--output_format={output_format}", "--normalization=0.9", f"--mdxc_overlap={overlap}", f"--mdxc_segment_size={segment_size}"]
if denoise:
prompt.append("--mdx_enable_denoise")
logs.append(f"Processing file: {audio_files}")
yield "\n".join(logs)
subprocess.run(prompt)
logs.append(f"File: {audio_files} processed!")
yield "\n".join(logs)
def mdxnet_batch(path_input, path_output, model, output_format, overlap, segment_size, denoise):
found_files = []
logs = []
logs.clear()
extensions = (".mp3", ".wav", ".flac")
for audio_files in os.listdir(path_input):
if audio_files.endswith(extensions):
found_files.append(audio_files)
total_files = len(found_files)
if total_files == 0:
logs.append("No valid audio files.")
yield "\n".join(logs)
else:
logs.append(f"{total_files} audio files found")
found_files.sort()
for audio_files in found_files:
file_path = os.path.join(path_input, audio_files)
prompt = ["audio-separator", file_path, "-m", f"{model}", f"--output_dir={path_output}", f"--output_format={output_format}", "--normalization=0.9", f"--mdx_overlap={overlap}", f"--mdx_segment_size={segment_size}"]
if denoise:
prompt.append("--mdx_enable_denoise")
logs.append(f"Processing file: {audio_files}")
yield "\n".join(logs)
subprocess.run(prompt)
logs.append(f"File: {audio_files} processed!")
yield "\n".join(logs)
def vrarch_batch(path_input, path_output, model, output_format, window_size, agression, tta, high_end_process):
found_files = []
logs = []
logs.clear()
extensions = (".mp3", ".wav", ".flac")
for audio_files in os.listdir(path_input):
if audio_files.endswith(extensions):
found_files.append(audio_files)
total_files = len(found_files)
if total_files == 0:
logs.append("No valid audio files.")
yield "\n".join(logs)
else:
logs.append(f"{total_files} audio files found")
found_files.sort()
for audio_files in found_files:
file_path = os.path.join(path_input, audio_files)
prompt = ["audio-separator", file_path, "-m", f"{model}", f"--output_dir={path_output}", f"--output_format={output_format}", "--normalization=0.9", f"--vr_window_size={window_size}", f"--vr_aggression={agression}"]
if tta:
prompt.append("--vr_enable_tta")
if high_end_process:
prompt.append("--vr_high_end_process")
logs.append(f"Processing file: {audio_files}")
yield "\n".join(logs)
subprocess.run(prompt)
logs.append(f"File: {audio_files} processed!")
yield "\n".join(logs)
def demucs_batch(path_input, path_output, model, output_format, shifts, overlap):
found_files = []
logs = []
logs.clear()
extensions = (".mp3", ".wav", ".flac")
for audio_files in os.listdir(path_input):
if audio_files.endswith(extensions):
found_files.append(audio_files)
total_files = len(found_files)
if total_files == 0:
logs.append("No valid audio files.")
yield "\n".join(logs)
else:
logs.append(f"{total_files} audio files found")
found_files.sort()
for audio_files in found_files:
file_path = os.path.join(path_input, audio_files)
prompt = ["audio-separator", file_path, "-m", f"{model}", f"--output_dir={path_output}", f"--output_format={output_format}", "--normalization=0.9", f"--demucs_shifts={shifts}", f"--demucs_overlap={overlap}"]
logs.append(f"Processing file: {audio_files}")
yield "\n".join(logs)
subprocess.run(prompt)
logs.append(f"File: {audio_files} processed!")
yield "\n".join(logs)
with gr.Blocks(theme="NoCrypt/[email protected]", title="🎵 UVR5 UI 🎵") as app:
gr.Markdown("<h1> 🎵 UVR5 UI 🎵 </h1>")
gr.Markdown("If you liked this HF Space you can give me a ❤️")
gr.Markdown("Try UVR5 UI using Colab [here](https://colab.research.google.com/github/Eddycrack864/UVR5-UI/blob/main/UVR_UI.ipynb)")
with gr.Tabs():
with gr.TabItem("BS/Mel Roformer"):
with gr.Row():
roformer_model = gr.Dropdown(
label = "Select the Model",
choices=list(roformer_models.keys()),
interactive = True
)
roformer_output_format = gr.Dropdown(
label = "Select the Output Format",
choices = output_format,
interactive = True
)
with gr.Row():
roformer_overlap = gr.Slider(
minimum = 2,
maximum = 4,
step = 1,
label = "Overlap",
info = "Amount of overlap between prediction windows.",
value = 4,
interactive = True
)
roformer_segment_size = gr.Slider(
minimum = 32,
maximum = 4000,
step = 32,
label = "Segment Size",
info = "Larger consumes more resources, but may give better results.",
value = 256,
interactive = True
)
with gr.Row():
roformer_audio = gr.Audio(
label = "Input Audio",
type = "numpy",
interactive = True
)
with gr.Accordion("Separation by Link", open = False):
with gr.Row():
roformer_link = gr.Textbox(
label = "Link",
placeholder = "Paste the link here",
interactive = True
)
with gr.Row():
gr.Markdown("You can paste the link to the video/audio from many sites, check the complete list [here](https://github.com/yt-dlp/yt-dlp/blob/master/supportedsites.md)")
with gr.Row():
roformer_download_button = gr.Button(
"Download!",
variant = "primary"
)
roformer_download_button.click(download_audio, [roformer_link], [roformer_audio])
with gr.Accordion("Batch Separation", open = False):
with gr.Row():
roformer_input_path = gr.Textbox(
label = "Input Path",
placeholder = "Place the input path here",
interactive = True
)
roformer_output_path = gr.Textbox(
label = "Output Path",
placeholder = "Place the output path here",
interactive = True
)
with gr.Row():
roformer_bath_button = gr.Button("Separate!", variant = "primary")
with gr.Row():
roformer_info = gr.Textbox(
label = "Output Information",
interactive = False
)
roformer_bath_button.click(roformer_batch, [roformer_input_path, roformer_output_path, roformer_model, roformer_output_format, roformer_overlap, roformer_segment_size], [roformer_info])
with gr.Row():
roformer_button = gr.Button("Separate!", variant = "primary")
with gr.Row():
roformer_stem1 = gr.Audio(
show_download_button = True,
interactive = False,
label = "Stem 1",
type = "filepath"
)
roformer_stem2 = gr.Audio(
show_download_button = True,
interactive = False,
label = "Stem 2",
type = "filepath"
)
roformer_button.click(roformer_separator, [roformer_audio, roformer_model, roformer_output_format, roformer_overlap, roformer_segment_size], [roformer_stem1, roformer_stem2])
with gr.TabItem("MDX23C"):
with gr.Row():
mdx23c_model = gr.Dropdown(
label = "Select the Model",
choices = mdx23c_models,
interactive = True
)
mdx23c_output_format = gr.Dropdown(
label = "Select the Output Format",
choices = output_format,
interactive = True
)
with gr.Row():
mdx23c_segment_size = gr.Slider(
minimum = 32,
maximum = 4000,
step = 32,
label = "Segment Size",
info = "Larger consumes more resources, but may give better results.",
value = 256,
interactive = True
)
mdx23c_overlap = gr.Slider(
minimum = 2,
maximum = 50,
step = 1,
label = "Overlap",
info = "Amount of overlap between prediction windows.",
value = 8,
interactive = True
)
mdx23c_denoise = gr.Checkbox(
label = "Denoise",
info = "Enable denoising during separation.",
value = False,
interactive = True
)
with gr.Row():
mdx23c_audio = gr.Audio(
label = "Input Audio",
type = "numpy",
interactive = True
)
with gr.Accordion("Separation by Link", open = False):
with gr.Row():
mdx23c_link = gr.Textbox(
label = "Link",
placeholder = "Paste the link here",
interactive = True
)
with gr.Row():
gr.Markdown("You can paste the link to the video/audio from many sites, check the complete list [here](https://github.com/yt-dlp/yt-dlp/blob/master/supportedsites.md)")
with gr.Row():
mdx23c_download_button = gr.Button(
"Download!",
variant = "primary"
)
mdx23c_download_button.click(download_audio, [mdx23c_link], [mdx23c_audio])
with gr.Accordion("Batch Separation", open = False):
with gr.Row():
mdx23c_input_path = gr.Textbox(
label = "Input Path",
placeholder = "Place the input path here",
interactive = True
)
mdx23c_output_path = gr.Textbox(
label = "Output Path",
placeholder = "Place the output path here",
interactive = True
)
with gr.Row():
mdx23c_bath_button = gr.Button("Separate!", variant = "primary")
with gr.Row():
mdx23c_info = gr.Textbox(
label = "Output Information",
interactive = False
)
mdx23c_bath_button.click(mdx23c_batch, [mdx23c_input_path, mdx23c_output_path, mdx23c_model, mdx23c_output_format, mdx23c_overlap, mdx23c_segment_size, mdx23c_denoise], [mdx23c_info])
with gr.Row():
mdx23c_button = gr.Button("Separate!", variant = "primary")
with gr.Row():
mdx23c_stem1 = gr.Audio(
show_download_button = True,
interactive = False,
label = "Stem 1",
type = "filepath"
)
mdx23c_stem2 = gr.Audio(
show_download_button = True,
interactive = False,
label = "Stem 2",
type = "filepath"
)
mdx23c_button.click(mdxc_separator, [mdx23c_audio, mdx23c_model, mdx23c_output_format, mdx23c_segment_size, mdx23c_overlap, mdx23c_denoise], [mdx23c_stem1, mdx23c_stem2])
with gr.TabItem("MDX-NET"):
with gr.Row():
mdxnet_model = gr.Dropdown(
label = "Select the Model",
choices = mdxnet_models,
interactive = True
)
mdxnet_output_format = gr.Dropdown(
label = "Select the Output Format",
choices = output_format,
interactive = True
)
with gr.Row():
mdxnet_segment_size = gr.Slider(
minimum = 32,
maximum = 4000,
step = 32,
label = "Segment Size",
info = "Larger consumes more resources, but may give better results.",
value = 256,
interactive = True
)
mdxnet_overlap = gr.Dropdown(
label = "Overlap",
choices = mdxnet_overlap_values,
value = mdxnet_overlap_values[0],
interactive = True
)
mdxnet_denoise = gr.Checkbox(
label = "Denoise",
info = "Enable denoising during separation.",
value = True,
interactive = True
)
with gr.Row():
mdxnet_audio = gr.Audio(
label = "Input Audio",
type = "numpy",
interactive = True
)
with gr.Accordion("Separation by Link", open = False):
with gr.Row():
mdxnet_link = gr.Textbox(
label = "Link",
placeholder = "Paste the link here",
interactive = True
)
with gr.Row():
gr.Markdown("You can paste the link to the video/audio from many sites, check the complete list [here](https://github.com/yt-dlp/yt-dlp/blob/master/supportedsites.md)")
with gr.Row():
mdxnet_download_button = gr.Button(
"Download!",
variant = "primary"
)
mdxnet_download_button.click(download_audio, [mdxnet_link], [mdxnet_audio])
with gr.Accordion("Batch Separation", open = False):
with gr.Row():
mdxnet_input_path = gr.Textbox(
label = "Input Path",
placeholder = "Place the input path here",
interactive = True
)
mdxnet_output_path = gr.Textbox(
label = "Output Path",
placeholder = "Place the output path here",
interactive = True
)
with gr.Row():
mdxnet_bath_button = gr.Button("Separate!", variant = "primary")
with gr.Row():
mdxnet_info = gr.Textbox(
label = "Output Information",
interactive = False
)
mdxnet_bath_button.click(mdxnet_batch, [mdxnet_input_path, mdxnet_output_path, mdxnet_model, mdxnet_output_format, mdxnet_overlap, mdxnet_segment_size, mdxnet_denoise], [mdxnet_info])
with gr.Row():
mdxnet_button = gr.Button("Separate!", variant = "primary")
with gr.Row():
mdxnet_stem1 = gr.Audio(
show_download_button = True,
interactive = False,
label = "Stem 1",
type = "filepath"
)
mdxnet_stem2 = gr.Audio(
show_download_button = True,
interactive = False,
label = "Stem 2",
type = "filepath"
)
mdxnet_button.click(mdxnet_separator, [mdxnet_audio, mdxnet_model, mdxnet_output_format, mdxnet_segment_size, mdxnet_overlap, mdxnet_denoise], [mdxnet_stem1, mdxnet_stem2])
with gr.TabItem("VR ARCH"):
with gr.Row():
vrarch_model = gr.Dropdown(
label = "Select the Model",
choices = vrarch_models,
interactive = True
)
vrarch_output_format = gr.Dropdown(
label = "Select the Output Format",
choices = output_format,
interactive = True
)
with gr.Row():
vrarch_window_size = gr.Dropdown(
label = "Window Size",
choices = vrarch_window_size_values,
value = vrarch_window_size_values[0],
interactive = True
)
vrarch_agression = gr.Slider(
minimum = 1,
maximum = 50,
step = 1,
label = "Agression",
info = "Intensity of primary stem extraction.",
value = 5,
interactive = True
)
vrarch_tta = gr.Checkbox(
label = "TTA",
info = "Enable Test-Time-Augmentation; slow but improves quality.",
value = True,
visible = True,
interactive = True,
)
vrarch_high_end_process = gr.Checkbox(
label = "High End Process",
info = "Mirror the missing frequency range of the output.",
value = False,
visible = True,
interactive = True,
)
with gr.Row():
vrarch_audio = gr.Audio(
label = "Input Audio",
type = "numpy",
interactive = True
)
with gr.Accordion("Separation by Link", open = False):
with gr.Row():
vrarch_link = gr.Textbox(
label = "Link",
placeholder = "Paste the link here",
interactive = True
)
with gr.Row():
gr.Markdown("You can paste the link to the video/audio from many sites, check the complete list [here](https://github.com/yt-dlp/yt-dlp/blob/master/supportedsites.md)")
with gr.Row():
vrarch_download_button = gr.Button(
"Download!",
variant = "primary"
)
vrarch_download_button.click(download_audio, [vrarch_link], [vrarch_audio])
with gr.Accordion("Batch Separation", open = False):
with gr.Row():
vrarch_input_path = gr.Textbox(
label = "Input Path",
placeholder = "Place the input path here",
interactive = True
)
vrarch_output_path = gr.Textbox(
label = "Output Path",
placeholder = "Place the output path here",
interactive = True
)
with gr.Row():
vrarch_bath_button = gr.Button("Separate!", variant = "primary")
with gr.Row():
vrarch_info = gr.Textbox(
label = "Output Information",
interactive = False
)
vrarch_bath_button.click(vrarch_batch, [vrarch_input_path, vrarch_output_path, vrarch_model, vrarch_output_format, vrarch_window_size, vrarch_agression, vrarch_tta, vrarch_high_end_process], [vrarch_info])
with gr.Row():
vrarch_button = gr.Button("Separate!", variant = "primary")
with gr.Row():
vrarch_stem1 = gr.Audio(
show_download_button = True,
interactive = False,
type = "filepath",
label = "Stem 1"
)
vrarch_stem2 = gr.Audio(
show_download_button = True,
interactive = False,
type = "filepath",
label = "Stem 2"
)
vrarch_button.click(vrarch_separator, [vrarch_audio, vrarch_model, vrarch_output_format, vrarch_window_size, vrarch_agression, vrarch_tta, vrarch_high_end_process], [vrarch_stem1, vrarch_stem2])
with gr.TabItem("Demucs"):
with gr.Row():
demucs_model = gr.Dropdown(
label = "Select the Model",
choices = demucs_models,
interactive = True
)
demucs_output_format = gr.Dropdown(
label = "Select the Output Format",
choices = output_format,
interactive = True
)
with gr.Row():
demucs_shifts = gr.Slider(
minimum = 1,
maximum = 20,
step = 1,
label = "Shifts",
info = "Number of predictions with random shifts, higher = slower but better quality.",
value = 2,
interactive = True
)
demucs_overlap = gr.Dropdown(
label = "Overlap",
choices = demucs_overlap_values,
value = demucs_overlap_values[0],
interactive = True
)
with gr.Row():
demucs_audio = gr.Audio(
label = "Input Audio",
type = "numpy",
interactive = True
)
with gr.Accordion("Separation by Link", open = False):
with gr.Row():
demucs_link = gr.Textbox(
label = "Link",
placeholder = "Paste the link here",
interactive = True
)
with gr.Row():
gr.Markdown("You can paste the link to the video/audio from many sites, check the complete list [here](https://github.com/yt-dlp/yt-dlp/blob/master/supportedsites.md)")
with gr.Row():
demucs_download_button = gr.Button(
"Download!",
variant = "primary"
)
demucs_download_button.click(download_audio, [demucs_link], [demucs_audio])
with gr.Accordion("Batch Separation", open = False):
with gr.Row():
demucs_input_path = gr.Textbox(
label = "Input Path",
placeholder = "Place the input path here",
interactive = True
)
demucs_output_path = gr.Textbox(
label = "Output Path",
placeholder = "Place the output path here",
interactive = True
)
with gr.Row():
demucs_bath_button = gr.Button("Separate!", variant = "primary")
with gr.Row():
demucs_info = gr.Textbox(
label = "Output Information",
interactive = False
)
demucs_bath_button.click(demucs_batch, [demucs_input_path, demucs_output_path, demucs_model, demucs_output_format, demucs_shifts, demucs_overlap], [demucs_info])
with gr.Row():
demucs_button = gr.Button("Separate!", variant = "primary")
with gr.Row():
demucs_stem1 = gr.Audio(
show_download_button = True,
interactive = False,
type = "filepath",
label = "Stem 1"
)
demucs_stem2 = gr.Audio(
show_download_button = True,
interactive = False,
type = "filepath",
label = "Stem 2"
)
with gr.Row():
demucs_stem3 = gr.Audio(
show_download_button = True,
interactive = False,
type = "filepath",
label = "Stem 3"
)
demucs_stem4 = gr.Audio(
show_download_button = True,
interactive = False,
type = "filepath",
label = "Stem 4"
)
demucs_button.click(demucs_separator, [demucs_audio, demucs_model, demucs_output_format, demucs_shifts, demucs_overlap], [demucs_stem1, demucs_stem2, demucs_stem3, demucs_stem4])
with gr.TabItem("Credits"):
gr.Markdown(
"""
UVR5 UI created by **[Eddycrack 864](https://github.com/Eddycrack864).** Join **[AI HUB](https://discord.gg/aihub)** community.
* python-audio-separator by [beveradb](https://github.com/beveradb).
* Special thanks to [Ilaria](https://github.com/TheStingerX) for hosting this space and help.
* Thanks to [Mikus](https://github.com/cappuch) for the help with the code.
* Thanks to [Nick088](https://huggingface.co/Nick088) for the help to fix roformers.
* Thanks to [yt_dlp](https://github.com/yt-dlp/yt-dlp) devs.
* Separation by link source code and improvements by [Blane187](https://huggingface.co/Blane187).
You can donate to the original UVR5 project here:
[!["Buy Me A Coffee"](https://www.buymeacoffee.com/assets/img/custom_images/orange_img.png)](https://www.buymeacoffee.com/uvr5)
"""
)
app.queue()
app.launch()