| import os |
| import re |
| import random |
| from scipy.io.wavfile import write |
| import gradio as gr |
| from Applio import * |
| from uvrmodel import * |
|
|
| def roformer_separator(roformer_audio, roformer_model, roformer_output_format, roformer_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', 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}" |
| 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): |
| 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}" |
| 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 |
|
|
| with gr.Blocks(theme=applio, 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 with GPU 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 |
| ) |
| with gr.Row(): |
| roformer_audio = gr.Audio( |
| label = "Input Audio", |
| type = "numpy", |
| interactive = True |
| ) |
| 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_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 |
| ) |
| with gr.Row(): |
| mdx23c_audio = gr.Audio( |
| label = "Input Audio", |
| type = "numpy", |
| interactive = True |
| ) |
| 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_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.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.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.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 **[Not Eddy (Spanish Mod)](http://discord.com/users/274566299349155851)** in **[AI HUB](https://discord.gg/aihub)** community. |
| |
| * python-audio-separator by [beveradb](https://github.com/beveradb). |
| * Thanks to [Ilaria](https://github.com/TheStingerX) and [Mikus](https://github.com/cappuch) for the help with the code. |
| * Improvements by [Blane187](https://github.com/Blane187). |
| |
| You can donate to the original UVR5 project here: |
| [](https://www.buymeacoffee.com/uvr5) |
| """ |
| ) |
|
|
| app.queue() |
| app.launch(show_api=False) |
