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import os
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import re
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import random
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from scipy.io.wavfile import write
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import gradio as gr
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roformer_models = {
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'BS-Roformer-Viperx-1297.ckpt': 'model_bs_roformer_ep_317_sdr_12.9755.ckpt',
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'BS-Roformer-Viperx-1296.ckpt': 'model_bs_roformer_ep_368_sdr_12.9628.ckpt',
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'BS-Roformer-Viperx-1053.ckpt': 'model_bs_roformer_ep_937_sdr_10.5309.ckpt',
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'Mel-Roformer-Viperx-1143.ckpt': 'model_mel_band_roformer_ep_3005_sdr_11.4360.ckpt'
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}
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mdx23c_models = [
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'MDX23C_D1581.ckpt',
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'MDX23C-8KFFT-InstVoc_HQ.ckpt',
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'MDX23C-8KFFT-InstVoc_HQ_2.ckpt',
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]
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mdxnet_models = [
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'UVR-MDX-NET-Inst_full_292.onnx',
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'UVR-MDX-NET_Inst_187_beta.onnx',
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'UVR-MDX-NET_Inst_82_beta.onnx',
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'UVR-MDX-NET_Inst_90_beta.onnx',
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'UVR-MDX-NET_Main_340.onnx',
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'UVR-MDX-NET_Main_390.onnx',
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'UVR-MDX-NET_Main_406.onnx',
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'UVR-MDX-NET_Main_427.onnx',
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'UVR-MDX-NET_Main_438.onnx',
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'UVR-MDX-NET-Inst_HQ_1.onnx',
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'UVR-MDX-NET-Inst_HQ_2.onnx',
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'UVR-MDX-NET-Inst_HQ_3.onnx',
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'UVR-MDX-NET-Inst_HQ_4.onnx',
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'UVR_MDXNET_Main.onnx',
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'UVR-MDX-NET-Inst_Main.onnx',
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'UVR_MDXNET_1_9703.onnx',
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'UVR_MDXNET_2_9682.onnx',
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'UVR_MDXNET_3_9662.onnx',
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'UVR-MDX-NET-Inst_1.onnx',
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'UVR-MDX-NET-Inst_2.onnx',
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'UVR-MDX-NET-Inst_3.onnx',
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'UVR_MDXNET_KARA.onnx',
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'UVR_MDXNET_KARA_2.onnx',
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'UVR_MDXNET_9482.onnx',
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'UVR-MDX-NET-Voc_FT.onnx',
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'Kim_Vocal_1.onnx',
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'Kim_Vocal_2.onnx',
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'Kim_Inst.onnx',
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'Reverb_HQ_By_FoxJoy.onnx',
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'UVR-MDX-NET_Crowd_HQ_1.onnx',
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'kuielab_a_vocals.onnx',
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'kuielab_a_other.onnx',
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'kuielab_a_bass.onnx',
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'kuielab_a_drums.onnx',
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'kuielab_b_vocals.onnx',
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'kuielab_b_other.onnx',
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'kuielab_b_bass.onnx',
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'kuielab_b_drums.onnx',
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]
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vrarch_models = [
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'1_HP-UVR.pth',
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'2_HP-UVR.pth',
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'3_HP-Vocal-UVR.pth',
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'4_HP-Vocal-UVR.pth',
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'5_HP-Karaoke-UVR.pth',
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'6_HP-Karaoke-UVR.pth',
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'7_HP2-UVR.pth',
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'8_HP2-UVR.pth',
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'9_HP2-UVR.pth',
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'10_SP-UVR-2B-32000-1.pth',
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'11_SP-UVR-2B-32000-2.pth',
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'12_SP-UVR-3B-44100.pth',
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'13_SP-UVR-4B-44100-1.pth',
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'14_SP-UVR-4B-44100-2.pth',
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'15_SP-UVR-MID-44100-1.pth',
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'16_SP-UVR-MID-44100-2.pth',
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'17_HP-Wind_Inst-UVR.pth',
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'UVR-De-Echo-Aggressive.pth',
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'UVR-De-Echo-Normal.pth',
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'UVR-DeEcho-DeReverb.pth',
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'UVR-DeNoise-Lite.pth',
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'UVR-DeNoise.pth',
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'UVR-BVE-4B_SN-44100-1.pth',
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'MGM_HIGHEND_v4.pth',
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'MGM_LOWEND_A_v4.pth',
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'MGM_LOWEND_B_v4.pth',
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'MGM_MAIN_v4.pth',
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]
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demucs_models = [
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'htdemucs_ft.yaml',
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'htdemucs.yaml',
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'hdemucs_mmi.yaml',
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]
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output_format = [
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'wav',
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'flac',
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'mp3',
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]
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mdxnet_overlap_values = [
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'0.25',
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'0.5',
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'0.75',
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'0.99',
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]
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vrarch_window_size_values = [
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'320',
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'512',
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'1024',
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]
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demucs_overlap_values = [
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'0.25',
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'0.50',
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'0.75',
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'0.99',
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]
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def roformer_separator(roformer_audio, roformer_model, roformer_output_format, roformer_overlap):
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files_list = []
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files_list.clear()
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directory = "./outputs"
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random_id = str(random.randint(10000, 99999))
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pattern = f"{random_id}"
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os.makedirs("outputs", exist_ok=True)
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write(f'{random_id}.wav', roformer_audio[0], roformer_audio[1])
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full_roformer_model = roformer_models[roformer_model]
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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}"
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os.system(prompt)
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for file in os.listdir(directory):
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if re.search(pattern, file):
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files_list.append(os.path.join(directory, file))
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stem1_file = files_list[0]
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stem2_file = files_list[1]
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return stem1_file, stem2_file
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def mdxc_separator(mdx23c_audio, mdx23c_model, mdx23c_output_format, mdx23c_segment_size, mdx23c_overlap):
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files_list = []
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files_list.clear()
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directory = "./outputs"
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random_id = str(random.randint(10000, 99999))
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pattern = f"{random_id}"
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os.makedirs("outputs", exist_ok=True)
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write(f'{random_id}.wav', mdx23c_audio[0], mdx23c_audio[1])
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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}"
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os.system(prompt)
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for file in os.listdir(directory):
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if re.search(pattern, file):
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files_list.append(os.path.join(directory, file))
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stem1_file = files_list[0]
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stem2_file = files_list[1]
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return stem1_file, stem2_file
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def mdxnet_separator(mdxnet_audio, mdxnet_model, mdxnet_output_format, mdxnet_segment_size, mdxnet_overlap, mdxnet_denoise):
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files_list = []
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files_list.clear()
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directory = "./outputs"
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random_id = str(random.randint(10000, 99999))
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pattern = f"{random_id}"
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os.makedirs("outputs", exist_ok=True)
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write(f'{random_id}.wav', mdxnet_audio[0], mdxnet_audio[1])
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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}"
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if mdxnet_denoise:
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prompt += " --mdx_enable_denoise"
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os.system(prompt)
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for file in os.listdir(directory):
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if re.search(pattern, file):
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files_list.append(os.path.join(directory, file))
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stem1_file = files_list[0]
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stem2_file = files_list[1]
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return stem1_file, stem2_file
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def vrarch_separator(vrarch_audio, vrarch_model, vrarch_output_format, vrarch_window_size, vrarch_agression, vrarch_tta, vrarch_high_end_process):
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files_list = []
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files_list.clear()
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directory = "./outputs"
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random_id = str(random.randint(10000, 99999))
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pattern = f"{random_id}"
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os.makedirs("outputs", exist_ok=True)
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write(f'{random_id}.wav', vrarch_audio[0], vrarch_audio[1])
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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}"
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if vrarch_tta:
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prompt += " --vr_enable_tta"
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if vrarch_high_end_process:
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prompt += " --vr_high_end_process"
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os.system(prompt)
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for file in os.listdir(directory):
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if re.search(pattern, file):
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files_list.append(os.path.join(directory, file))
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stem1_file = files_list[0]
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stem2_file = files_list[1]
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return stem1_file, stem2_file
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def demucs_separator(demucs_audio, demucs_model, demucs_output_format, demucs_shifts, demucs_overlap):
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files_list = []
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files_list.clear()
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directory = "./outputs"
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random_id = str(random.randint(10000, 99999))
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pattern = f"{random_id}"
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os.makedirs("outputs", exist_ok=True)
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write(f'{random_id}.wav', demucs_audio[0], demucs_audio[1])
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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}"
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os.system(prompt)
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for file in os.listdir(directory):
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if re.search(pattern, file):
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files_list.append(os.path.join(directory, file))
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stem1_file = files_list[0]
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stem2_file = files_list[1]
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stem3_file = files_list[2]
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stem4_file = files_list[3]
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return stem1_file, stem2_file, stem3_file, stem4_file
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|
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with gr.Blocks(theme="NoCrypt/miku@1.2.2", title="🎵 UVR5 UI 🎵") as app:
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gr.Markdown("<h1> 🎵 UVR5 UI 🎵 </h1>")
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with gr.Tabs():
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with gr.TabItem("BS/Mel Roformer"):
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with gr.Row():
|
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roformer_model = gr.Dropdown(
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label = "Select the Model",
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choices=list(roformer_models.keys()),
|
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interactive = True
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)
|
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roformer_output_format = gr.Dropdown(
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label = "Select the Output Format",
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choices = output_format,
|
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interactive = True
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)
|
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with gr.Row():
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roformer_overlap = gr.Slider(
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minimum = 2,
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maximum = 4,
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step = 1,
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|
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",
|
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interactive = True
|
|
)
|
|
with gr.Row():
|
|
roformer_button = gr.Button("Separate!", variant = "primary")
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with gr.Row():
|
|
roformer_stem1 = gr.Audio(
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|
show_download_button = True,
|
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interactive = False,
|
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label = "Stem 1",
|
|
type = "filepath"
|
|
)
|
|
roformer_stem2 = gr.Audio(
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|
show_download_button = True,
|
|
interactive = False,
|
|
label = "Stem 2",
|
|
type = "filepath"
|
|
)
|
|
|
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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])
|
|
|
|
app.launch() |