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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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from scipy.io.wavfile import read |
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import numpy as np |
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import gradio as gr |
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import yt_dlp |
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import subprocess |
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|
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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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|
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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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|
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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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|
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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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|
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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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|
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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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|
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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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|
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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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|
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def download_audio(url): |
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ydl_opts = { |
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'format': 'bestaudio/best', |
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'outtmpl': 'ytdl/%(title)s.%(ext)s', |
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'postprocessors': [{ |
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'key': 'FFmpegExtractAudio', |
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'preferredcodec': 'wav', |
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'preferredquality': '192', |
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}], |
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} |
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|
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with yt_dlp.YoutubeDL(ydl_opts) as ydl: |
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info_dict = ydl.extract_info(url, download=True) |
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file_path = ydl.prepare_filename(info_dict).rsplit('.', 1)[0] + '.wav' |
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sample_rate, audio_data = read(file_path) |
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audio_array = np.asarray(audio_data, dtype=np.int16) |
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return sample_rate, audio_array |
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|
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def roformer_separator(roformer_audio, roformer_model, roformer_output_format, roformer_overlap, roformer_segment_size): |
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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} --mdxc_segment_size={roformer_segment_size}" |
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os.system(prompt) |
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|
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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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|
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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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|
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def mdxc_separator(mdx23c_audio, mdx23c_model, mdx23c_output_format, mdx23c_segment_size, mdx23c_overlap, mdx23c_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', 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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|
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if mdx23c_denoise: |
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prompt += " --mdx_enable_denoise" |
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|
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os.system(prompt) |
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|
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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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|
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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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|
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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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|
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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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|
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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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|
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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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|
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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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|
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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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|
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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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|
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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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|
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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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|
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os.system(prompt) |
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|
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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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|
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return stem1_file, stem2_file, stem3_file, stem4_file |
|
|
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def roformer_batch(path_input, path_output, model, output_format, overlap, segment_size): |
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found_files = [] |
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logs = [] |
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logs.clear() |
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|
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extensions = (".mp3", ".wav", ".flac") |
|
|
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full_roformer_model = roformer_models[model] |
|
|
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for audio_files in os.listdir(path_input): |
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if audio_files.endswith(extensions): |
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found_files.append(audio_files) |
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total_files = len(found_files) |
|
|
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if total_files == 0: |
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logs.append("No valid audio files.") |
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yield "\n".join(logs) |
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else: |
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logs.append(f"{total_files} audio files found") |
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found_files.sort() |
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|
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for audio_files in found_files: |
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file_path = os.path.join(path_input, audio_files) |
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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}"] |
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logs.append(f"Processing file: {audio_files}") |
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yield "\n".join(logs) |
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subprocess.run(prompt) |
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logs.append(f"File: {audio_files} processed!") |
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yield "\n".join(logs) |
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|
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def mdx23c_batch(path_input, path_output, model, output_format, overlap, segment_size, denoise): |
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found_files = [] |
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logs = [] |
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logs.clear() |
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|
|
extensions = (".mp3", ".wav", ".flac") |
|
|
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for audio_files in os.listdir(path_input): |
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if audio_files.endswith(extensions): |
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found_files.append(audio_files) |
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total_files = len(found_files) |
|
|
|
if total_files == 0: |
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logs.append("No valid audio files.") |
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yield "\n".join(logs) |
|
else: |
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logs.append(f"{total_files} audio files found") |
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found_files.sort() |
|
|
|
for audio_files in found_files: |
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file_path = os.path.join(path_input, audio_files) |
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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: |
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prompt.append("--mdx_enable_denoise") |
|
|
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logs.append(f"Processing file: {audio_files}") |
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yield "\n".join(logs) |
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subprocess.run(prompt) |
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logs.append(f"File: {audio_files} processed!") |
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yield "\n".join(logs) |
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|
|
def mdxnet_batch(path_input, path_output, model, output_format, overlap, segment_size, denoise): |
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found_files = [] |
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logs = [] |
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logs.clear() |
|
|
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extensions = (".mp3", ".wav", ".flac") |
|
|
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for audio_files in os.listdir(path_input): |
|
if audio_files.endswith(extensions): |
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found_files.append(audio_files) |
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total_files = len(found_files) |
|
|
|
if total_files == 0: |
|
logs.append("No valid audio files.") |
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yield "\n".join(logs) |
|
else: |
|
logs.append(f"{total_files} audio files found") |
|
found_files.sort() |
|
|
|
for audio_files in found_files: |
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file_path = os.path.join(path_input, audio_files) |
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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: |
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prompt.append("--mdx_enable_denoise") |
|
|
|
logs.append(f"Processing file: {audio_files}") |
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yield "\n".join(logs) |
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subprocess.run(prompt) |
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logs.append(f"File: {audio_files} processed!") |
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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() |