parent
7325bfa143
commit
6b02e98e35
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@ -20,6 +20,21 @@ def render_audio_to_audio() -> None:
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"""
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)
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with st.expander("Help", False):
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st.write(
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"""
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This tool allows you to upload an audio file of arbitrary length and modify it with
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a text prompt. It does this by sweeping over the audio in overlapping clips, doing
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img2img style transfer with riffusion, then stitching the clips back together with
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cross fading to eliminate seams.
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Try a denoising strength of 0.4 for light modification and 0.55 for more heavy
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modification. The best specific denoising depends on how different the prompt is
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from the source audio. You can play with the seed to get infinite variations.
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Currently the same seed is used for all clips along the track.
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"""
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)
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device = streamlit_util.select_device(st.sidebar)
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audio_file = st.file_uploader(
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@ -18,6 +18,16 @@ def render_image_to_audio() -> None:
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"""
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)
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with st.expander("Help", False):
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st.write(
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"""
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This tool takes an existing spectrogram image and reconstructs it into an audio
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waveform. It also displays the EXIF metadata stored inside the image, which can
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contain the parameters used to create the spectrogram image. If no EXIF is contained,
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assumes default parameters.
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"""
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)
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device = streamlit_util.select_device(st.sidebar)
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image_file = st.file_uploader(
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@ -17,6 +17,15 @@ def render_sample_clips() -> None:
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"""
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)
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with st.expander("Help", False):
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st.write(
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"""
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This tool simply allows uploading an audio file and randomly sampling short clips
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from it. It's useful for generating a large number of short clips from a single
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audio file. Outputs can be saved to a given directory with a given audio extension.
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"""
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)
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audio_file = st.file_uploader(
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"Upload a file",
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type=["wav", "mp3", "ogg"],
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@ -15,6 +15,19 @@ def render_split_audio() -> None:
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"""
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)
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with st.expander("Help", False):
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st.write(
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"""
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This tool allows uploading an audio file of arbitrary length and splits it into
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stems of vocals, drums, bass, and other. It does this using a deep network that
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sweeps over the audio in clips, extracts the stems, and then cross fades the clips
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back together to construct the full length stems. It's particularly useful in
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combination with audio_to_audio, for example to split and preserve vocals while
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modifying the rest of the track with a prompt. Or, to pull out drums to add later
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in a DAW.
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"""
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)
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device = streamlit_util.select_device(st.sidebar)
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audio_file = st.file_uploader(
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@ -12,11 +12,20 @@ def render_text_to_audio() -> None:
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st.subheader(":pencil2: Text to Audio")
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st.write(
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"""
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Generate audio from text prompts. \nRuns the model directly without a seed image or
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interpolation.
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Generate audio from text prompts.
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"""
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)
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with st.expander("Help", False):
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st.write(
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"""
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This tool runs riffusion in the simplest text to image form to generate an audio
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clip from a text prompt. There is no seed image or interpolation here. This mode
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allows more diversity and creativity than when using a seed image, but it also
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leads to having less control. Play with the seed to get infinite variations.
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"""
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)
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device = streamlit_util.select_device(st.sidebar)
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prompt = st.text_input("Prompt")
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@ -38,11 +38,20 @@ def render_text_to_audio_batch() -> None:
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st.subheader(":scroll: Text to Audio Batch")
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st.write(
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"""
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Generate audio in batch from a JSON file of text prompts. \nThe input
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file contains a global params block and a list of entries with positive and negative
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prompts.
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Generate audio in batch from a JSON file of text prompts.
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"""
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)
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with st.expander("Help", False):
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st.write(
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"""
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This tool is a batch form of text_to_audio, where the inputs are read in from a JSON
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file. The input file contains a global params block and a list of entries with positive
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and negative prompts. It's useful for automating a larger set of generations. See the
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example inputs below for the format of the file.
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"""
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)
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device = streamlit_util.select_device(st.sidebar)
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# Upload a JSON file
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