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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/miku@1.2.2", 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() |