change ui
This commit is contained in:
AIFSH
+3
-3
@@ -1,5 +1,5 @@
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WEB_DIRECTORY = "./web"
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from .nodes import LoadAudio, UVR5,PlayAudio
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from .nodes import LoadAudio, UVR5,PreViewAudio
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# Set the web directory, any .js file in that directory will be loaded by the frontend as a frontend extension
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# WEB_DIRECTORY = "./somejs"
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@@ -9,12 +9,12 @@ from .nodes import LoadAudio, UVR5,PlayAudio
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NODE_CLASS_MAPPINGS = {
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"UVR5_Node": UVR5,
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"LoadAudio": LoadAudio,
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"PlayAudio": PlayAudio
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"PreViewAudio": PreViewAudio
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}
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# A dictionary that contains the friendly/humanly readable titles for the nodes
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NODE_DISPLAY_NAME_MAPPINGS = {
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"UVR5_Node": "UVR5 Node",
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"LoadAudio": "AudioLoader",
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"PlayAudio": "PlayAudio"
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"PreViewAudio": "PreView Audio"
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}
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@@ -17,7 +17,8 @@ weights_path = os.path.join(node_path, "uvr5")
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device= "cuda" if cuda_malloc_supported() else "cpu"
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is_half=True
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class PlayAudio:
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class PreViewAudio:
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@classmethod
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def INPUT_TYPES(s):
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return {"required":
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@@ -53,7 +54,7 @@ class LoadAudio:
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@classmethod
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def INPUT_TYPES(s):
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input_dir = input_path
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files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f)) and f.split('.')[-1] in ["wav", "mp3"]]
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files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f)) and f.split('.')[-1] in ["wav", "mp3","WAV","flac","m4a"]]
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return {"required":
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{"audio": (sorted(files),)},
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}
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@@ -142,7 +143,7 @@ class UVR5:
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"display": "slider"
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}),
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"format0":(["wav", "flac", "mp3", "m4a"],{
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"default": "flac"
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"default": "wav"
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})
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},
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}
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@@ -1,261 +0,0 @@
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import os
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import logging
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logger = logging.getLogger(__name__)
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import librosa
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import numpy as np
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import soundfile as sf
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import torch
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from tqdm import tqdm
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from cuda_malloc import cuda_malloc_supported
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cpu = torch.device("cpu" if not cuda_malloc_supported() else "cuda")
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class ConvTDFNetTrim:
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def __init__(
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self, device, model_name, target_name, L, dim_f, dim_t, n_fft, hop=1024
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):
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super(ConvTDFNetTrim, self).__init__()
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self.dim_f = dim_f
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self.dim_t = 2**dim_t
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self.n_fft = n_fft
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self.hop = hop
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self.n_bins = self.n_fft // 2 + 1
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self.chunk_size = hop * (self.dim_t - 1)
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self.window = torch.hann_window(window_length=self.n_fft, periodic=True).to(
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device
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)
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self.target_name = target_name
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self.blender = "blender" in model_name
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self.dim_c = 4
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out_c = self.dim_c * 4 if target_name == "*" else self.dim_c
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self.freq_pad = torch.zeros(
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[1, out_c, self.n_bins - self.dim_f, self.dim_t]
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).to(device)
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self.n = L // 2
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def stft(self, x):
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x = x.reshape([-1, self.chunk_size])
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x = torch.stft(
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x,
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n_fft=self.n_fft,
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hop_length=self.hop,
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window=self.window,
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center=True,
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return_complex=True,
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)
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x = torch.view_as_real(x)
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x = x.permute([0, 3, 1, 2])
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x = x.reshape([-1, 2, 2, self.n_bins, self.dim_t]).reshape(
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[-1, self.dim_c, self.n_bins, self.dim_t]
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)
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return x[:, :, : self.dim_f]
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def istft(self, x, freq_pad=None):
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freq_pad = (
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self.freq_pad.repeat([x.shape[0], 1, 1, 1])
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if freq_pad is None
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else freq_pad
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)
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x = torch.cat([x, freq_pad], -2)
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c = 4 * 2 if self.target_name == "*" else 2
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x = x.reshape([-1, c, 2, self.n_bins, self.dim_t]).reshape(
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[-1, 2, self.n_bins, self.dim_t]
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)
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x = x.permute([0, 2, 3, 1])
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x = x.contiguous()
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x = torch.view_as_complex(x)
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x = torch.istft(
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x, n_fft=self.n_fft, hop_length=self.hop, window=self.window, center=True
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)
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return x.reshape([-1, c, self.chunk_size])
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def get_models(device, dim_f, dim_t, n_fft):
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return ConvTDFNetTrim(
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device=device,
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model_name="Conv-TDF",
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target_name="vocals",
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L=11,
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dim_f=dim_f,
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dim_t=dim_t,
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n_fft=n_fft,
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)
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class Predictor:
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def __init__(self, args):
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import onnxruntime as ort
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logger.info(ort.get_available_providers())
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self.args = args
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self.model_ = get_models(
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device=cpu, dim_f=args.dim_f, dim_t=args.dim_t, n_fft=args.n_fft
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)
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self.model = ort.InferenceSession(
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os.path.join(args.onnx, self.model_.target_name + ".onnx"),
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providers=[
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"CUDAExecutionProvider",
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"DmlExecutionProvider",
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"CPUExecutionProvider",
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],
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)
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logger.info("ONNX load done")
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def demix(self, mix):
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samples = mix.shape[-1]
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margin = self.args.margin
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chunk_size = self.args.chunks * 44100
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assert not margin == 0, "margin cannot be zero!"
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if margin > chunk_size:
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margin = chunk_size
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segmented_mix = {}
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if self.args.chunks == 0 or samples < chunk_size:
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chunk_size = samples
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counter = -1
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for skip in range(0, samples, chunk_size):
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counter += 1
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s_margin = 0 if counter == 0 else margin
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end = min(skip + chunk_size + margin, samples)
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start = skip - s_margin
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segmented_mix[skip] = mix[:, start:end].copy()
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if end == samples:
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break
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sources = self.demix_base(segmented_mix, margin_size=margin)
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"""
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mix:(2,big_sample)
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segmented_mix:offset->(2,small_sample)
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sources:(1,2,big_sample)
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"""
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return sources
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def demix_base(self, mixes, margin_size):
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chunked_sources = []
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progress_bar = tqdm(total=len(mixes))
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progress_bar.set_description("Processing")
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for mix in mixes:
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cmix = mixes[mix]
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sources = []
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n_sample = cmix.shape[1]
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model = self.model_
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trim = model.n_fft // 2
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gen_size = model.chunk_size - 2 * trim
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pad = gen_size - n_sample % gen_size
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mix_p = np.concatenate(
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(np.zeros((2, trim)), cmix, np.zeros((2, pad)), np.zeros((2, trim))), 1
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)
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mix_waves = []
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i = 0
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while i < n_sample + pad:
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waves = np.array(mix_p[:, i : i + model.chunk_size])
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mix_waves.append(waves)
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i += gen_size
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mix_waves = torch.tensor(mix_waves, dtype=torch.float32).to(cpu)
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with torch.no_grad():
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_ort = self.model
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spek = model.stft(mix_waves)
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if self.args.denoise:
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spec_pred = (
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-_ort.run(None, {"input": -spek.cpu().numpy()})[0] * 0.5
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+ _ort.run(None, {"input": spek.cpu().numpy()})[0] * 0.5
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)
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tar_waves = model.istft(torch.tensor(spec_pred).to(cpu))
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else:
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tar_waves = model.istft(
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torch.tensor(_ort.run(None, {"input": spek.cpu().numpy()})[0]).to(cpu)
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)
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tar_signal = (
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tar_waves[:, :, trim:-trim]
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.transpose(0, 1)
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.reshape(2, -1)
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.cpu()
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.numpy()[:, :-pad]
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)
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start = 0 if mix == 0 else margin_size
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end = None if mix == list(mixes.keys())[::-1][0] else -margin_size
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if margin_size == 0:
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end = None
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sources.append(tar_signal[:, start:end])
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progress_bar.update(1)
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chunked_sources.append(sources)
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_sources = np.concatenate(chunked_sources, axis=-1)
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# del self.model
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progress_bar.close()
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return _sources
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def prediction(self, m, vocal_root, others_root, format):
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os.makedirs(vocal_root, exist_ok=True)
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os.makedirs(others_root, exist_ok=True)
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basename = os.path.basename(m)
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mix, rate = librosa.load(m, mono=False, sr=44100)
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if mix.ndim == 1:
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mix = np.asfortranarray([mix, mix])
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mix = mix.T
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sources = self.demix(mix.T)
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opt = sources[0].T
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if format in ["wav", "flac"]:
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vocal_AUDIO = "%s/%s_main_vocal.%s" % (vocal_root, basename, format)
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sf.write(
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vocal_AUDIO, mix - opt, rate
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)
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bgm_AUDIO = "%s/%s_others.%s" % (others_root, basename, format)
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sf.write(bgm_AUDIO, opt, rate)
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else:
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vocal_AUDIO = "%s/%s_main_vocal.wav" % (vocal_root, basename)
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bgm_AUDIO = "%s/%s_others.wav" % (others_root, basename)
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sf.write(vocal_AUDIO, mix - opt, rate)
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sf.write(bgm_AUDIO, opt, rate)
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opt_path_vocal = vocal_AUDIO[:-4] + ".%s" % format
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opt_path_other = bgm_AUDIO[:-4] + ".%s" % format
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if os.path.exists(vocal_AUDIO):
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os.system(
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"ffmpeg -i %s -vn %s -q:a 2 -y" % (vocal_AUDIO, opt_path_vocal)
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)
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if os.path.exists(opt_path_vocal):
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try:
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os.remove(vocal_AUDIO)
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except:
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pass
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if os.path.exists(bgm_AUDIO):
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os.system(
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"ffmpeg -i %s -vn %s -q:a 2 -y" % (bgm_AUDIO, opt_path_other)
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)
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if os.path.exists(opt_path_other):
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try:
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os.remove(bgm_AUDIO)
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except:
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pass
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return vocal_AUDIO,bgm_AUDIO
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class MDXNetDereverb:
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def __init__(self, chunks):
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self.onnx = "%s/uvr5_weights/onnx_dereverb_By_FoxJoy"%os.path.dirname(os.path.abspath(__file__))
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self.shifts = 10 # 'Predict with randomised equivariant stabilisation'
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self.mixing = "min_mag" # ['default','min_mag','max_mag']
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self.chunks = chunks
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self.margin = 44100
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self.dim_t = 9
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self.dim_f = 3072
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self.n_fft = 6144
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self.denoise = True
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self.pred = Predictor(self)
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self.device = cpu
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def _path_audio_(self, input, others_root, vocal_root, format, is_hp3=False):
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return self.pred.prediction(input, vocal_root, others_root, format)
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@@ -1,378 +0,0 @@
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import os,sys
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parent_directory = os.path.dirname(os.path.abspath(__file__))
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import logging,pdb
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logger = logging.getLogger(__name__)
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import librosa
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import numpy as np
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import soundfile as sf
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import torch
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from .lib.lib_v5 import nets_61968KB as Nets
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from .lib.lib_v5 import spec_utils
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from .lib.lib_v5.model_param_init import ModelParameters
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from .lib.lib_v5.nets_new import CascadedNet
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from .lib.utils import inference
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class AudioPre:
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def __init__(self, agg, model_path, device, is_half, tta=False):
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self.model_path = model_path
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self.device = device
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self.data = {
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# Processing Options
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"postprocess": False,
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"tta": tta,
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# Constants
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"window_size": 512,
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"agg": agg,
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"high_end_process": "mirroring",
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}
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mp = ModelParameters("%s/lib/lib_v5/modelparams/4band_v2.json"%parent_directory)
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model = Nets.CascadedASPPNet(mp.param["bins"] * 2)
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cpk = torch.load(model_path, map_location="cpu")
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model.load_state_dict(cpk)
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model.eval()
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if is_half:
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model = model.half().to(device)
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else:
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model = model.to(device)
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self.mp = mp
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self.model = model
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def _path_audio_(
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self, music_file, ins_root=None, vocal_root=None, format="flac", is_hp3=False
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):
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if ins_root is None and vocal_root is None:
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return "No save root."
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name = os.path.basename(music_file)
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if ins_root is not None:
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os.makedirs(ins_root, exist_ok=True)
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if vocal_root is not None:
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os.makedirs(vocal_root, exist_ok=True)
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X_wave, y_wave, X_spec_s, y_spec_s = {}, {}, {}, {}
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bands_n = len(self.mp.param["band"])
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# print(bands_n)
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for d in range(bands_n, 0, -1):
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bp = self.mp.param["band"][d]
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if d == bands_n: # high-end band
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(
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X_wave[d],
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_,
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) = librosa.core.load( # 理论上librosa读取可能对某些音频有bug，应该上ffmpeg读取，但是太麻烦了弃坑
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music_file,
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sr = bp["sr"],
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mono = False,
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dtype = np.float32,
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res_type = bp["res_type"],
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)
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if X_wave[d].ndim == 1:
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X_wave[d] = np.asfortranarray([X_wave[d], X_wave[d]])
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else: # lower bands
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X_wave[d] = librosa.core.resample(
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X_wave[d + 1],
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orig_sr = self.mp.param["band"][d + 1]["sr"],
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target_sr = bp["sr"],
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res_type = bp["res_type"],
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)
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# Stft of wave source
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X_spec_s[d] = spec_utils.wave_to_spectrogram_mt(
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X_wave[d],
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bp["hl"],
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bp["n_fft"],
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self.mp.param["mid_side"],
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self.mp.param["mid_side_b2"],
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self.mp.param["reverse"],
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)
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# pdb.set_trace()
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if d == bands_n and self.data["high_end_process"] != "none":
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input_high_end_h = (bp["n_fft"] // 2 - bp["crop_stop"]) + (
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self.mp.param["pre_filter_stop"] - self.mp.param["pre_filter_start"]
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)
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input_high_end = X_spec_s[d][
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:, bp["n_fft"] // 2 - input_high_end_h : bp["n_fft"] // 2, :
|
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]
|
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|
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X_spec_m = spec_utils.combine_spectrograms(X_spec_s, self.mp)
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aggresive_set = float(self.data["agg"] / 100)
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aggressiveness = {
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"value": aggresive_set,
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"split_bin": self.mp.param["band"][1]["crop_stop"],
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}
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with torch.no_grad():
|
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pred, X_mag, X_phase = inference(
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X_spec_m, self.device, self.model, aggressiveness, self.data
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)
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# Postprocess
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if self.data["postprocess"]:
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pred_inv = np.clip(X_mag - pred, 0, np.inf)
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pred = spec_utils.mask_silence(pred, pred_inv)
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y_spec_m = pred * X_phase
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v_spec_m = X_spec_m - y_spec_m
|
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|
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if is_hp3 == True:
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ins_root,vocal_root = vocal_root,ins_root
|
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|
||||
if ins_root is not None:
|
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if self.data["high_end_process"].startswith("mirroring"):
|
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input_high_end_ = spec_utils.mirroring(
|
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self.data["high_end_process"], y_spec_m, input_high_end, self.mp
|
||||
)
|
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wav_instrument = spec_utils.cmb_spectrogram_to_wave(
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y_spec_m, self.mp, input_high_end_h, input_high_end_
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)
|
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else:
|
||||
wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp)
|
||||
logger.info("%s instruments done" % name)
|
||||
if is_hp3 == True:
|
||||
head = "vocal_"
|
||||
else:
|
||||
head = "instrument_"
|
||||
if format in ["wav", "flac"]:
|
||||
bgm_AUDIO = os.path.join(
|
||||
ins_root,
|
||||
head + "{}_{}.{}".format(name, self.data["agg"], format),
|
||||
)
|
||||
sf.write(
|
||||
bgm_AUDIO,
|
||||
(np.array(wav_instrument) * 32768).astype("int16"),
|
||||
self.mp.param["sr"],
|
||||
) #
|
||||
else:
|
||||
bgm_AUDIO = os.path.join(
|
||||
ins_root, head + "{}_{}.wav".format(name, self.data["agg"])
|
||||
)
|
||||
sf.write(
|
||||
bgm_AUDIO,
|
||||
(np.array(wav_instrument) * 32768).astype("int16"),
|
||||
self.mp.param["sr"],
|
||||
)
|
||||
if os.path.exists(bgm_AUDIO):
|
||||
opt_format_path = bgm_AUDIO[:-4] + ".%s" % format
|
||||
os.system("ffmpeg -i %s -vn %s -q:a 2 -y" % (bgm_AUDIO, opt_format_path))
|
||||
if os.path.exists(opt_format_path):
|
||||
try:
|
||||
os.remove(bgm_AUDIO)
|
||||
except:
|
||||
pass
|
||||
if vocal_root is not None:
|
||||
if is_hp3 == True:
|
||||
head = "instrument_"
|
||||
else:
|
||||
head = "vocal_"
|
||||
if self.data["high_end_process"].startswith("mirroring"):
|
||||
input_high_end_ = spec_utils.mirroring(
|
||||
self.data["high_end_process"], v_spec_m, input_high_end, self.mp
|
||||
)
|
||||
wav_vocals = spec_utils.cmb_spectrogram_to_wave(
|
||||
v_spec_m, self.mp, input_high_end_h, input_high_end_
|
||||
)
|
||||
else:
|
||||
wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp)
|
||||
logger.info("%s vocals done" % name)
|
||||
if format in ["wav", "flac"]:
|
||||
vocal_AUDIO = os.path.join(
|
||||
vocal_root,
|
||||
head + "{}_{}.{}".format(name, self.data["agg"], format),
|
||||
)
|
||||
sf.write(
|
||||
vocal_AUDIO,
|
||||
(np.array(wav_vocals) * 32768).astype("int16"),
|
||||
self.mp.param["sr"],
|
||||
)
|
||||
else:
|
||||
vocal_AUDIO = os.path.join(
|
||||
vocal_root, head + "{}_{}.wav".format(name, self.data["agg"])
|
||||
)
|
||||
sf.write(
|
||||
vocal_AUDIO,
|
||||
(np.array(wav_vocals) * 32768).astype("int16"),
|
||||
self.mp.param["sr"],
|
||||
)
|
||||
if os.path.exists(vocal_AUDIO):
|
||||
opt_format_path = vocal_AUDIO[:-4] + ".%s" % format
|
||||
os.system("ffmpeg -i %s -vn %s -q:a 2 -y" % (vocal_AUDIO, opt_format_path))
|
||||
if os.path.exists(opt_format_path):
|
||||
try:
|
||||
os.remove(vocal_AUDIO)
|
||||
except:
|
||||
pass
|
||||
if is_hp3 == True:
|
||||
return bgm_AUDIO,vocal_AUDIO
|
||||
return vocal_AUDIO, bgm_AUDIO
|
||||
|
||||
|
||||
class AudioPreDeEcho:
|
||||
def __init__(self, agg, model_path, device, is_half, tta=False):
|
||||
self.model_path = model_path
|
||||
self.device = device
|
||||
self.data = {
|
||||
# Processing Options
|
||||
"postprocess": False,
|
||||
"tta": tta,
|
||||
# Constants
|
||||
"window_size": 512,
|
||||
"agg": agg,
|
||||
"high_end_process": "mirroring",
|
||||
}
|
||||
mp = ModelParameters("%s/lib/lib_v5/modelparams/4band_v3.json"%parent_directory)
|
||||
nout = 64 if "DeReverb" in model_path else 48
|
||||
model = CascadedNet(mp.param["bins"] * 2, nout)
|
||||
cpk = torch.load(model_path, map_location="cpu")
|
||||
model.load_state_dict(cpk)
|
||||
model.eval()
|
||||
if is_half:
|
||||
model = model.half().to(device)
|
||||
else:
|
||||
model = model.to(device)
|
||||
|
||||
self.mp = mp
|
||||
self.model = model
|
||||
|
||||
def _path_audio_(
|
||||
self, music_file, vocal_root=None, ins_root=None, format="flac", is_hp3=False
|
||||
): # 3个VR模型vocal和ins是反的
|
||||
if ins_root is None and vocal_root is None:
|
||||
return "No save root."
|
||||
name = os.path.basename(music_file)
|
||||
if ins_root is not None:
|
||||
os.makedirs(ins_root, exist_ok=True)
|
||||
if vocal_root is not None:
|
||||
os.makedirs(vocal_root, exist_ok=True)
|
||||
X_wave, y_wave, X_spec_s, y_spec_s = {}, {}, {}, {}
|
||||
bands_n = len(self.mp.param["band"])
|
||||
# print(bands_n)
|
||||
for d in range(bands_n, 0, -1):
|
||||
bp = self.mp.param["band"][d]
|
||||
if d == bands_n: # high-end band
|
||||
(
|
||||
X_wave[d],
|
||||
_,
|
||||
) = librosa.core.load( # 理论上librosa读取可能对某些音频有bug，应该上ffmpeg读取，但是太麻烦了弃坑
|
||||
music_file,
|
||||
sr = bp["sr"],
|
||||
mono = False,
|
||||
dtype = np.float32,
|
||||
res_type = bp["res_type"],
|
||||
)
|
||||
if X_wave[d].ndim == 1:
|
||||
X_wave[d] = np.asfortranarray([X_wave[d], X_wave[d]])
|
||||
else: # lower bands
|
||||
X_wave[d] = librosa.core.resample(
|
||||
X_wave[d + 1],
|
||||
orig_sr = self.mp.param["band"][d + 1]["sr"],
|
||||
target_sr = bp["sr"],
|
||||
res_type = bp["res_type"],
|
||||
)
|
||||
# Stft of wave source
|
||||
X_spec_s[d] = spec_utils.wave_to_spectrogram_mt(
|
||||
X_wave[d],
|
||||
bp["hl"],
|
||||
bp["n_fft"],
|
||||
self.mp.param["mid_side"],
|
||||
self.mp.param["mid_side_b2"],
|
||||
self.mp.param["reverse"],
|
||||
)
|
||||
# pdb.set_trace()
|
||||
if d == bands_n and self.data["high_end_process"] != "none":
|
||||
input_high_end_h = (bp["n_fft"] // 2 - bp["crop_stop"]) + (
|
||||
self.mp.param["pre_filter_stop"] - self.mp.param["pre_filter_start"]
|
||||
)
|
||||
input_high_end = X_spec_s[d][
|
||||
:, bp["n_fft"] // 2 - input_high_end_h : bp["n_fft"] // 2, :
|
||||
]
|
||||
|
||||
X_spec_m = spec_utils.combine_spectrograms(X_spec_s, self.mp)
|
||||
aggresive_set = float(self.data["agg"] / 100)
|
||||
aggressiveness = {
|
||||
"value": aggresive_set,
|
||||
"split_bin": self.mp.param["band"][1]["crop_stop"],
|
||||
}
|
||||
with torch.no_grad():
|
||||
pred, X_mag, X_phase = inference(
|
||||
X_spec_m, self.device, self.model, aggressiveness, self.data
|
||||
)
|
||||
# Postprocess
|
||||
if self.data["postprocess"]:
|
||||
pred_inv = np.clip(X_mag - pred, 0, np.inf)
|
||||
pred = spec_utils.mask_silence(pred, pred_inv)
|
||||
y_spec_m = pred * X_phase
|
||||
v_spec_m = X_spec_m - y_spec_m
|
||||
|
||||
if ins_root is not None:
|
||||
if self.data["high_end_process"].startswith("mirroring"):
|
||||
input_high_end_ = spec_utils.mirroring(
|
||||
self.data["high_end_process"], y_spec_m, input_high_end, self.mp
|
||||
)
|
||||
wav_instrument = spec_utils.cmb_spectrogram_to_wave(
|
||||
y_spec_m, self.mp, input_high_end_h, input_high_end_
|
||||
)
|
||||
else:
|
||||
wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp)
|
||||
logger.info("%s instruments done" % name)
|
||||
if format in ["wav", "flac"]:
|
||||
bgm_AUDIO = os.path.join(
|
||||
ins_root,
|
||||
"vocal_{}_{}.{}".format(name, self.data["agg"], format),
|
||||
)
|
||||
sf.write(
|
||||
bgm_AUDIO,
|
||||
(np.array(wav_instrument) * 32768).astype("int16"),
|
||||
self.mp.param["sr"],
|
||||
) #
|
||||
else:
|
||||
bgm_AUDIO = os.path.join(
|
||||
ins_root, "vocal_{}_{}.wav".format(name, self.data["agg"])
|
||||
)
|
||||
sf.write(
|
||||
bgm_AUDIO,
|
||||
(np.array(wav_instrument) * 32768).astype("int16"),
|
||||
self.mp.param["sr"],
|
||||
)
|
||||
if os.path.exists(bgm_AUDIO):
|
||||
opt_format_path = bgm_AUDIO[:-4] + ".%s" % format
|
||||
os.system("ffmpeg -i %s -vn %s -q:a 2 -y" % (bgm_AUDIO, opt_format_path))
|
||||
if os.path.exists(opt_format_path):
|
||||
try:
|
||||
os.remove(bgm_AUDIO)
|
||||
except:
|
||||
pass
|
||||
if vocal_root is not None:
|
||||
if self.data["high_end_process"].startswith("mirroring"):
|
||||
input_high_end_ = spec_utils.mirroring(
|
||||
self.data["high_end_process"], v_spec_m, input_high_end, self.mp
|
||||
)
|
||||
wav_vocals = spec_utils.cmb_spectrogram_to_wave(
|
||||
v_spec_m, self.mp, input_high_end_h, input_high_end_
|
||||
)
|
||||
else:
|
||||
wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp)
|
||||
logger.info("%s vocals done" % name)
|
||||
if format in ["wav", "flac"]:
|
||||
vocal_AUDIO = os.path.join(
|
||||
vocal_root,
|
||||
"instrument_{}_{}.{}".format(name, self.data["agg"], format),
|
||||
)
|
||||
sf.write(
|
||||
vocal_AUDIO,
|
||||
(np.array(wav_vocals) * 32768).astype("int16"),
|
||||
self.mp.param["sr"],
|
||||
)
|
||||
else:
|
||||
vocal_AUDIO = os.path.join(
|
||||
vocal_root, "instrument_{}_{}.wav".format(name, self.data["agg"])
|
||||
)
|
||||
sf.write(
|
||||
vocal_AUDIO,
|
||||
(np.array(wav_vocals) * 32768).astype("int16"),
|
||||
self.mp.param["sr"],
|
||||
)
|
||||
if os.path.exists(vocal_AUDIO):
|
||||
opt_format_path = vocal_AUDIO[:-4] + ".%s" % format
|
||||
os.system("ffmpeg -i %s -vn %s -q:a 2 -y" % (vocal_AUDIO, opt_format_path))
|
||||
if os.path.exists(opt_format_path):
|
||||
try:
|
||||
os.remove(vocal_AUDIO)
|
||||
except:
|
||||
pass
|
||||
return bgm_AUDIO,vocal_AUDIO
|
||||
Binary file not shown.
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Binary file not shown.
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Binary file not shown.
@@ -1,171 +0,0 @@
|
||||
import { app } from "../../../scripts/app.js";
|
||||
import { api } from '../../../scripts/api.js'
|
||||
import { ComfyWidgets } from "../../../scripts/widgets.js"
|
||||
|
||||
function audioUpload(node, inputName, inputData, app) {
|
||||
const audioWidget = node.widgets.find((w) => w.name === "audio");
|
||||
let uploadWidget;
|
||||
/*
|
||||
A method that returns the required style for the html
|
||||
*/
|
||||
function playAudio(node, name) {
|
||||
let url = `/view?filename=${encodeURIComponent(name)}&type=input&subfolder=${app.getPreviewFormatParam()}${app.getRandParam()}`
|
||||
|
||||
while (node.widgets.length > 2){
|
||||
node.widgets.pop()
|
||||
}
|
||||
|
||||
let isTick = true;
|
||||
const audio = new Audio(url);
|
||||
const slider = node.addWidget(
|
||||
"slider",
|
||||
"loading",
|
||||
0,
|
||||
(v) => {
|
||||
if (!isTick) {
|
||||
audio.currentTime = v;
|
||||
}
|
||||
isTick = false;
|
||||
},
|
||||
{
|
||||
min: 0,
|
||||
max: 0,
|
||||
}
|
||||
);
|
||||
|
||||
const button = node.addWidget("button", `Play ${name}`, "play", () => {
|
||||
try {
|
||||
if (audio.paused) {
|
||||
audio.play();
|
||||
button.name = `Pause ${name}`;
|
||||
} else {
|
||||
audio.pause();
|
||||
button.name = `Play ${name}`;
|
||||
}
|
||||
} catch (error) {
|
||||
alert(error);
|
||||
}
|
||||
app.canvas.setDirty(true);
|
||||
});
|
||||
audio.addEventListener("timeupdate", () => {
|
||||
isTick = true;
|
||||
slider.value = audio.currentTime;
|
||||
app.canvas.setDirty(true);
|
||||
});
|
||||
audio.addEventListener("ended", () => {
|
||||
button.name = `Play ${name}`;
|
||||
app.canvas.setDirty(true);
|
||||
});
|
||||
audio.addEventListener("loadedmetadata", () => {
|
||||
slider.options.max = audio.duration;
|
||||
slider.name = `(${audio.duration})`;
|
||||
app.canvas.setDirty(true);
|
||||
});
|
||||
}
|
||||
|
||||
var default_value = audioWidget.value;
|
||||
Object.defineProperty(audioWidget, "value", {
|
||||
set : function(value) {
|
||||
this._real_value = value;
|
||||
},
|
||||
|
||||
get : function() {
|
||||
let value = "";
|
||||
if (this._real_value) {
|
||||
value = this._real_value;
|
||||
} else {
|
||||
return default_value;
|
||||
}
|
||||
|
||||
if (value.filename) {
|
||||
let real_value = value;
|
||||
value = "";
|
||||
if (real_value.subfolder) {
|
||||
value = real_value.subfolder + "/";
|
||||
}
|
||||
|
||||
value += real_value.filename;
|
||||
|
||||
if(real_value.type && real_value.type !== "input")
|
||||
value += ` [${real_value.type}]`;
|
||||
}
|
||||
return value;
|
||||
}
|
||||
});
|
||||
async function uploadFile(file, updateNode, pasted = false) {
|
||||
try {
|
||||
// Wrap file in formdata so it includes filename
|
||||
const body = new FormData();
|
||||
body.append("image", file);
|
||||
if (pasted) body.append("subfolder", "pasted");
|
||||
const resp = await api.fetchApi("/upload/image", {
|
||||
method: "POST",
|
||||
body,
|
||||
});
|
||||
|
||||
if (resp.status === 200) {
|
||||
const data = await resp.json();
|
||||
// Add the file to the dropdown list and update the widget value
|
||||
let path = data.name;
|
||||
if (data.subfolder) path = data.subfolder + "/" + path;
|
||||
|
||||
if (!audioWidget.options.values.includes(path)) {
|
||||
audioWidget.options.values.push(path);
|
||||
}
|
||||
|
||||
if (updateNode) {
|
||||
audioWidget.value = path;
|
||||
// showAudio(path)
|
||||
playAudio(node, path);
|
||||
}
|
||||
} else {
|
||||
alert(resp.status + " - " + resp.statusText);
|
||||
}
|
||||
} catch (error) {
|
||||
alert(error);
|
||||
}
|
||||
}
|
||||
|
||||
const fileInput = document.createElement("input");
|
||||
Object.assign(fileInput, {
|
||||
type: "file",
|
||||
accept: "audio/mp3,audio/wav,audio/flac,audio/m4a",
|
||||
style: "display: none",
|
||||
onchange: async () => {
|
||||
if (fileInput.files.length) {
|
||||
await uploadFile(fileInput.files[0], true);
|
||||
}
|
||||
},
|
||||
});
|
||||
document.body.append(fileInput);
|
||||
|
||||
// Create the button widget for selecting the files
|
||||
uploadWidget = node.addWidget("button", "choose audio file to upload", "Audio", () => {
|
||||
fileInput.click();
|
||||
});
|
||||
|
||||
uploadWidget.serialize = false;
|
||||
playAudio(node, audioWidget.value);
|
||||
|
||||
const cb = node.callback;
|
||||
audioWidget.callback = function () {
|
||||
playAudio(node, audioWidget.value);
|
||||
if (cb) {
|
||||
return cb.apply(this, arguments);
|
||||
}
|
||||
};
|
||||
|
||||
return { widget: uploadWidget };
|
||||
}
|
||||
|
||||
ComfyWidgets.AUDIOUPLOAD = audioUpload;
|
||||
|
||||
app.registerExtension({
|
||||
name: "UVR5.UploadAudio",
|
||||
async beforeRegisterNodeDef(nodeType, nodeData, app) {
|
||||
if (nodeData?.name == "LoadAudio") {
|
||||
nodeData.input.required.upload = ["AUDIOUPLOAD"];
|
||||
}
|
||||
},
|
||||
});
|
||||
|
||||
@@ -1,85 +0,0 @@
|
||||
/**
|
||||
* File: playAudio.js
|
||||
* Project: comfyui_jags_audiotools
|
||||
* Author: jags111
|
||||
*
|
||||
* Copyright (c) 2023 jags111
|
||||
*
|
||||
*/
|
||||
import { app } from "../../../scripts/app.js";
|
||||
import { api } from '../../../scripts/api.js'
|
||||
import { ComfyWidgets } from "../../../scripts/widgets.js"
|
||||
|
||||
|
||||
/*
|
||||
A method that returns the required style for the html
|
||||
*/
|
||||
function addPlaybackWidget(node, name, root) {
|
||||
|
||||
try {
|
||||
while (node.widgets.length > 0){
|
||||
node.widgets.pop()
|
||||
}
|
||||
} catch (error) {
|
||||
//console.log(error);
|
||||
}
|
||||
let url = `/view?filename=${encodeURIComponent(name)}&type=${root}&subfolder=${app.getPreviewFormatParam()}${app.getRandParam()}`;
|
||||
let isTick = true;
|
||||
const audio = new Audio(url);
|
||||
const slider = node.addWidget(
|
||||
"slider",
|
||||
"loading",
|
||||
0,
|
||||
(v) => {
|
||||
if (!isTick) {
|
||||
audio.currentTime = v;
|
||||
}
|
||||
isTick = false;
|
||||
},
|
||||
{
|
||||
min: 0,
|
||||
max: 0,
|
||||
}
|
||||
);
|
||||
|
||||
const button = node.addWidget("button", `Play ${name}`, "play", () => {
|
||||
try {
|
||||
if (audio.paused) {
|
||||
audio.play();
|
||||
button.name = `Pause ${name}`;
|
||||
} else {
|
||||
audio.pause();
|
||||
button.name = `Play ${name}`;
|
||||
}
|
||||
} catch (error) {
|
||||
alert(error);
|
||||
}
|
||||
app.canvas.setDirty(true);
|
||||
});
|
||||
|
||||
audio.addEventListener("timeupdate", () => {
|
||||
isTick = true;
|
||||
slider.value = audio.currentTime;
|
||||
app.canvas.setDirty(true);
|
||||
});
|
||||
audio.addEventListener("ended", () => {
|
||||
button.name = `Play ${name}`;
|
||||
app.canvas.setDirty(true);
|
||||
});
|
||||
audio.addEventListener("loadedmetadata", () => {
|
||||
slider.options.max = audio.duration;
|
||||
slider.name = `(${audio.duration})`;
|
||||
app.canvas.setDirty(true);
|
||||
});
|
||||
}
|
||||
|
||||
app.registerExtension({
|
||||
name: "UVR5.AudioPlayer",
|
||||
async beforeRegisterNodeDef(nodeType, nodeData, app) {
|
||||
if (nodeData?.name == "PlayAudio") {
|
||||
nodeType.prototype.onExecuted = function (data) {
|
||||
addPlaybackWidget(this, data.audio[0], data.audio[1]);
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
@@ -0,0 +1,155 @@
|
||||
import { app } from "../../../scripts/app.js";
|
||||
import { api } from '../../../scripts/api.js'
|
||||
|
||||
function fitHeight(node) {
|
||||
node.setSize([node.size[0], node.computeSize([node.size[0], node.size[1]])[1]])
|
||||
node?.graph?.setDirtyCanvas(true);
|
||||
}
|
||||
function chainCallback(object, property, callback) {
|
||||
if (object == undefined) {
|
||||
//This should not happen.
|
||||
console.error("Tried to add callback to non-existant object")
|
||||
return;
|
||||
}
|
||||
if (property in object) {
|
||||
const callback_orig = object[property]
|
||||
object[property] = function () {
|
||||
const r = callback_orig.apply(this, arguments);
|
||||
callback.apply(this, arguments);
|
||||
return r
|
||||
};
|
||||
} else {
|
||||
object[property] = callback;
|
||||
}
|
||||
}
|
||||
|
||||
function addPreviewOptions(nodeType) {
|
||||
chainCallback(nodeType.prototype, "getExtraMenuOptions", function(_, options) {
|
||||
// The intended way of appending options is returning a list of extra options,
|
||||
// but this isn't used in widgetInputs.js and would require
|
||||
// less generalization of chainCallback
|
||||
let optNew = []
|
||||
try {
|
||||
const previewWidget = this.widgets.find((w) => w.name === "audiopreview");
|
||||
|
||||
let url = null
|
||||
if (previewWidget.audioEl?.hidden == false && previewWidget.audioEl.src) {
|
||||
//Use full quality audio
|
||||
//url = api.apiURL('/view?' + new URLSearchParams(previewWidget.value.params));
|
||||
url = previewWidget.audioEl.src
|
||||
}
|
||||
if (url) {
|
||||
optNew.push(
|
||||
{
|
||||
content: "Open preview",
|
||||
callback: () => {
|
||||
window.open(url, "_blank")
|
||||
},
|
||||
},
|
||||
{
|
||||
content: "Save preview",
|
||||
callback: () => {
|
||||
const a = document.createElement("a");
|
||||
a.href = url;
|
||||
a.setAttribute("download", new URLSearchParams(previewWidget.value.params).get("filename"));
|
||||
document.body.append(a);
|
||||
a.click();
|
||||
requestAnimationFrame(() => a.remove());
|
||||
},
|
||||
}
|
||||
);
|
||||
}
|
||||
if(options.length > 0 && options[0] != null && optNew.length > 0) {
|
||||
optNew.push(null);
|
||||
}
|
||||
options.unshift(...optNew);
|
||||
|
||||
} catch (error) {
|
||||
console.log(error);
|
||||
}
|
||||
|
||||
});
|
||||
}
|
||||
function previewAudio(node,file,type){
|
||||
var element = document.createElement("div");
|
||||
const previewNode = node;
|
||||
var previewWidget = node.addDOMWidget("audiopreview", "preview", element, {
|
||||
serialize: false,
|
||||
hideOnZoom: false,
|
||||
getValue() {
|
||||
return element.value;
|
||||
},
|
||||
setValue(v) {
|
||||
element.value = v;
|
||||
},
|
||||
});
|
||||
previewWidget.computeSize = function(width) {
|
||||
if (this.aspectRatio && !this.parentEl.hidden) {
|
||||
let height = (previewNode.size[0]-20)/ this.aspectRatio + 10;
|
||||
if (!(height > 0)) {
|
||||
height = 0;
|
||||
}
|
||||
this.computedHeight = height + 10;
|
||||
return [width, height];
|
||||
}
|
||||
return [width, -4];//no loaded src, widget should not display
|
||||
}
|
||||
// element.style['pointer-events'] = "none"
|
||||
previewWidget.value = {hidden: false, paused: false, params: {}}
|
||||
previewWidget.parentEl = document.createElement("div");
|
||||
previewWidget.parentEl.className = "audio_preview";
|
||||
previewWidget.parentEl.style['width'] = "100%"
|
||||
element.appendChild(previewWidget.parentEl);
|
||||
previewWidget.audioEl = document.createElement("audio");
|
||||
previewWidget.audioEl.controls = true;
|
||||
previewWidget.audioEl.loop = false;
|
||||
previewWidget.audioEl.muted = false;
|
||||
previewWidget.audioEl.style['width'] = "100%"
|
||||
previewWidget.audioEl.addEventListener("loadedmetadata", () => {
|
||||
|
||||
previewWidget.aspectRatio = previewWidget.audioEl.audioWidth / previewWidget.audioEl.audioHeight;
|
||||
fitHeight(this);
|
||||
});
|
||||
previewWidget.audioEl.addEventListener("error", () => {
|
||||
//TODO: consider a way to properly notify the user why a preview isn't shown.
|
||||
previewWidget.parentEl.hidden = true;
|
||||
fitHeight(this);
|
||||
});
|
||||
|
||||
let params = {
|
||||
"filename": file,
|
||||
"type": type,
|
||||
}
|
||||
|
||||
previewWidget.parentEl.hidden = previewWidget.value.hidden;
|
||||
previewWidget.audioEl.autoplay = !previewWidget.value.paused && !previewWidget.value.hidden;
|
||||
let target_width = 256
|
||||
if (element.style?.width) {
|
||||
//overscale to allow scrolling. Endpoint won't return higher than native
|
||||
target_width = element.style.width.slice(0,-2)*2;
|
||||
}
|
||||
if (!params.force_size || params.force_size.includes("?") || params.force_size == "Disabled") {
|
||||
params.force_size = target_width+"x?"
|
||||
} else {
|
||||
let size = params.force_size.split("x")
|
||||
let ar = parseInt(size[0])/parseInt(size[1])
|
||||
params.force_size = target_width+"x"+(target_width/ar)
|
||||
}
|
||||
|
||||
previewWidget.audioEl.src = api.apiURL('/view?' + new URLSearchParams(params));
|
||||
|
||||
previewWidget.audioEl.hidden = false;
|
||||
previewWidget.parentEl.appendChild(previewWidget.audioEl)
|
||||
}
|
||||
|
||||
app.registerExtension({
|
||||
name: "UVR5.AudioPreviewer",
|
||||
async beforeRegisterNodeDef(nodeType, nodeData, app) {
|
||||
if (nodeData?.name == "PreViewAudio") {
|
||||
nodeType.prototype.onExecuted = function (data) {
|
||||
previewAudio(this, data.audio[0], data.audio[1]);
|
||||
}
|
||||
addPreviewOptions(nodeType)
|
||||
}
|
||||
}
|
||||
});
|
||||
@@ -0,0 +1,203 @@
|
||||
import { app } from "../../../scripts/app.js";
|
||||
import { api } from '../../../scripts/api.js'
|
||||
import { ComfyWidgets } from "../../../scripts/widgets.js"
|
||||
|
||||
function fitHeight(node) {
|
||||
node.setSize([node.size[0], node.computeSize([node.size[0], node.size[1]])[1]])
|
||||
node?.graph?.setDirtyCanvas(true);
|
||||
}
|
||||
|
||||
function previewAudio(node,file){
|
||||
while (node.widgets.length > 2){
|
||||
node.widgets.pop();
|
||||
}
|
||||
try {
|
||||
var el = document.getElementById("uploadAudio");
|
||||
el.remove();
|
||||
} catch (error) {
|
||||
console.log(error);
|
||||
}
|
||||
var element = document.createElement("div");
|
||||
element.id = "uploadAudio";
|
||||
const previewNode = node;
|
||||
var previewWidget = node.addDOMWidget("audiopreview", "preview", element, {
|
||||
serialize: false,
|
||||
hideOnZoom: false,
|
||||
getValue() {
|
||||
return element.value;
|
||||
},
|
||||
setValue(v) {
|
||||
element.value = v;
|
||||
},
|
||||
});
|
||||
previewWidget.computeSize = function(width) {
|
||||
if (this.aspectRatio && !this.parentEl.hidden) {
|
||||
let height = (previewNode.size[0]-20)/ this.aspectRatio + 10;
|
||||
if (!(height > 0)) {
|
||||
height = 0;
|
||||
}
|
||||
this.computedHeight = height + 10;
|
||||
return [width, height];
|
||||
}
|
||||
return [width, -4];//no loaded src, widget should not display
|
||||
}
|
||||
// element.style['pointer-events'] = "none"
|
||||
previewWidget.value = {hidden: false, paused: false, params: {}}
|
||||
previewWidget.parentEl = document.createElement("div");
|
||||
previewWidget.parentEl.className = "audio_preview";
|
||||
previewWidget.parentEl.style['width'] = "100%"
|
||||
element.appendChild(previewWidget.parentEl);
|
||||
previewWidget.audioEl = document.createElement("audio");
|
||||
previewWidget.audioEl.controls = true;
|
||||
previewWidget.audioEl.loop = false;
|
||||
previewWidget.audioEl.muted = false;
|
||||
previewWidget.audioEl.style['width'] = "100%"
|
||||
previewWidget.audioEl.addEventListener("loadedmetadata", () => {
|
||||
|
||||
previewWidget.aspectRatio = previewWidget.audioEl.audioWidth / previewWidget.audioEl.audioHeight;
|
||||
fitHeight(this);
|
||||
});
|
||||
previewWidget.audioEl.addEventListener("error", () => {
|
||||
//TODO: consider a way to properly notify the user why a preview isn't shown.
|
||||
previewWidget.parentEl.hidden = true;
|
||||
fitHeight(this);
|
||||
});
|
||||
|
||||
let params = {
|
||||
"filename": file,
|
||||
"type": "input",
|
||||
}
|
||||
|
||||
previewWidget.parentEl.hidden = previewWidget.value.hidden;
|
||||
previewWidget.audioEl.autoplay = !previewWidget.value.paused && !previewWidget.value.hidden;
|
||||
let target_width = 256
|
||||
if (element.style?.width) {
|
||||
//overscale to allow scrolling. Endpoint won't return higher than native
|
||||
target_width = element.style.width.slice(0,-2)*2;
|
||||
}
|
||||
if (!params.force_size || params.force_size.includes("?") || params.force_size == "Disabled") {
|
||||
params.force_size = target_width+"x?"
|
||||
} else {
|
||||
let size = params.force_size.split("x")
|
||||
let ar = parseInt(size[0])/parseInt(size[1])
|
||||
params.force_size = target_width+"x"+(target_width/ar)
|
||||
}
|
||||
|
||||
previewWidget.audioEl.src = api.apiURL('/view?' + new URLSearchParams(params));
|
||||
|
||||
previewWidget.audioEl.hidden = false;
|
||||
previewWidget.parentEl.appendChild(previewWidget.audioEl)
|
||||
}
|
||||
|
||||
function audioUpload(node, inputName, inputData, app) {
|
||||
const audioWidget = node.widgets.find((w) => w.name === "audio");
|
||||
let uploadWidget;
|
||||
/*
|
||||
A method that returns the required style for the html
|
||||
*/
|
||||
var default_value = audioWidget.value;
|
||||
Object.defineProperty(audioWidget, "value", {
|
||||
set : function(value) {
|
||||
this._real_value = value;
|
||||
},
|
||||
|
||||
get : function() {
|
||||
let value = "";
|
||||
if (this._real_value) {
|
||||
value = this._real_value;
|
||||
} else {
|
||||
return default_value;
|
||||
}
|
||||
|
||||
if (value.filename) {
|
||||
let real_value = value;
|
||||
value = "";
|
||||
if (real_value.subfolder) {
|
||||
value = real_value.subfolder + "/";
|
||||
}
|
||||
|
||||
value += real_value.filename;
|
||||
|
||||
if(real_value.type && real_value.type !== "input")
|
||||
value += ` [${real_value.type}]`;
|
||||
}
|
||||
return value;
|
||||
}
|
||||
});
|
||||
async function uploadFile(file, updateNode, pasted = false) {
|
||||
try {
|
||||
// Wrap file in formdata so it includes filename
|
||||
const body = new FormData();
|
||||
body.append("image", file);
|
||||
if (pasted) body.append("subfolder", "pasted");
|
||||
const resp = await api.fetchApi("/upload/image", {
|
||||
method: "POST",
|
||||
body,
|
||||
});
|
||||
|
||||
if (resp.status === 200) {
|
||||
const data = await resp.json();
|
||||
// Add the file to the dropdown list and update the widget value
|
||||
let path = data.name;
|
||||
if (data.subfolder) path = data.subfolder + "/" + path;
|
||||
|
||||
if (!audioWidget.options.values.includes(path)) {
|
||||
audioWidget.options.values.push(path);
|
||||
}
|
||||
|
||||
if (updateNode) {
|
||||
audioWidget.value = path;
|
||||
previewAudio(node,path)
|
||||
|
||||
}
|
||||
} else {
|
||||
alert(resp.status + " - " + resp.statusText);
|
||||
}
|
||||
} catch (error) {
|
||||
alert(error);
|
||||
}
|
||||
}
|
||||
|
||||
const fileInput = document.createElement("input");
|
||||
Object.assign(fileInput, {
|
||||
type: "file",
|
||||
accept: "audio/mp3,audio/wav,audio/flac,audio/m4a",
|
||||
style: "display: none",
|
||||
onchange: async () => {
|
||||
if (fileInput.files.length) {
|
||||
await uploadFile(fileInput.files[0], true);
|
||||
}
|
||||
},
|
||||
});
|
||||
document.body.append(fileInput);
|
||||
|
||||
// Create the button widget for selecting the files
|
||||
uploadWidget = node.addWidget("button", "choose audio file to upload", "Audio", () => {
|
||||
fileInput.click();
|
||||
});
|
||||
|
||||
uploadWidget.serialize = false;
|
||||
|
||||
previewAudio(node, audioWidget.value);
|
||||
const cb = node.callback;
|
||||
audioWidget.callback = function () {
|
||||
previewAudio(node,audioWidget.value);
|
||||
if (cb) {
|
||||
return cb.apply(this, arguments);
|
||||
}
|
||||
};
|
||||
|
||||
return { widget: uploadWidget };
|
||||
}
|
||||
|
||||
ComfyWidgets.AUDIOPLOAD = audioUpload;
|
||||
|
||||
app.registerExtension({
|
||||
name: "UVR5.UploadAudio",
|
||||
async beforeRegisterNodeDef(nodeType, nodeData, app) {
|
||||
if (nodeData?.name == "LoadAudio") {
|
||||
nodeData.input.required.upload = ["AUDIOPLOAD"];
|
||||
}
|
||||
},
|
||||
});
|
||||
|
||||
Reference in New Issue
Block a user