Update app.py

app.py

@@ -1,26 +1,555 @@
 import os
-import spaces
-import gradio as gr
+import re
+import random
 from scipy.io.wavfile import write
+import gradio as gr
+import spaces
+
+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',
+]
+
+@spaces.GPU(duration=300)
+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
+
+@spaces.GPU(duration=300)
+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
+
+@spaces.GPU(duration=300)    
+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
+
+@spaces.GPU(duration=300)
+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
+
+@spaces.GPU(duration=300)
+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="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
+                )
+            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 **[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.
+              * Improvements by [Blane187](https://github.com/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)
+              """
+           )
 
-@spaces.GPU()
-def inference(audio):
-  os.makedirs("out", exist_ok=True)
-  write('test.wav', audio[0], audio[1])
-  os.system("python3 -m demucs.separate -n htdemucs --two-stems=vocals -d cpu test.wav -o out")
-  return "./out/htdemucs/test/vocals.wav","./out/htdemucs/test/no_vocals.wav"
-    
-title = "Ilaria UVR 💖"
-description = "Drag and drop an audio file to easily separate it! [Join AI Hub Discord Server](https://discord.gg/aihub).</p>"
-article = "Made with 💖 by Ilaria"
-
-examples=[['test.mp3']]
-gr.Interface(
-    inference, 
-    gr.Audio(type="numpy", label="Song"),
-    [gr.Audio(type="filepath", label="Vocals"),gr.Audio(type="filepath", label="Instrumentals")],
-    title=title,
-    description=description,
-    article=article,
-    examples=examples
-    ).launch()
+app.queue()
+app.launch()