ComfyUI Node: (deforum) ExtractDominantNoteAmplitude

(deforum) ExtractDominantNoteAmplitude:

The ExtractDominantNoteAmplitude node is designed to analyze audio data and identify the dominant note's amplitude and phase within a specified frequency range. This node processes the Fast Fourier Transform (FFT) data of the audio signal to extract the magnitudes and phases of the frequencies within the given range. By applying optional smoothing and a magnitude threshold, it ensures that only significant frequencies are considered. This node is particularly useful for applications that require precise audio analysis, such as music visualization, audio-reactive animations, and other creative AI-driven audio projects.

(deforum) ExtractDominantNoteAmplitude Input Parameters:

audio_fft

This parameter represents the Fast Fourier Transform (FFT) data of the audio signal. The FFT data is a complex array that contains information about the frequency components of the audio signal. The node uses this data to identify the dominant frequencies within the specified range.

min_frequency

This parameter defines the minimum frequency of the range within which the node will search for the dominant note. It helps to focus the analysis on a specific part of the audio spectrum. The value should be a positive integer representing the frequency in Hertz (Hz).

max_frequency

This parameter defines the maximum frequency of the range within which the node will search for the dominant note. It sets the upper limit of the frequency range for analysis. The value should be a positive integer representing the frequency in Hertz (Hz).

magnitude_threshold

This parameter sets a threshold for the magnitude of the frequencies. Only frequencies with magnitudes above this threshold will be considered in the analysis. This helps to filter out noise and insignificant frequencies. The value should be a positive number.

smoothing_window_size

This optional parameter defines the size of the window used for smoothing the magnitudes of the frequencies. Smoothing can help to reduce noise and make the dominant frequencies more apparent. The value should be a positive integer, and a larger window size will result in more smoothing.

(deforum) ExtractDominantNoteAmplitude Output Parameters:

dominant_frequencies_amplitude

This output parameter is an array containing the amplitudes of the dominant frequencies identified within the specified range. Each value in the array corresponds to the amplitude of a dominant frequency at a specific point in time. This information can be used to understand the intensity of the dominant notes in the audio signal.

dominant_frequencies_phase

This output parameter is an array containing the phases of the dominant frequencies identified within the specified range. Each value in the array corresponds to the phase of a dominant frequency at a specific point in time. This information can be used to understand the phase relationship of the dominant notes in the audio signal.

(deforum) ExtractDominantNoteAmplitude Usage Tips:

• To achieve the best results, ensure that the min_frequency and max_frequency parameters are set to focus on the relevant part of the audio spectrum for your application.
• Use the magnitude_threshold parameter to filter out noise and insignificant frequencies, which can improve the accuracy of the dominant note detection.
• If the audio signal is noisy, consider using a larger smoothing_window_size to smooth the magnitudes and make the dominant frequencies more apparent.

(deforum) ExtractDominantNoteAmplitude Common Errors and Solutions:

ValueError: If the smoothing window size is inappropriate for the data length

• Explanation: This error occurs when the smoothing_window_size is too large for the length of the magnitudes array.
• Solution: Reduce the smoothing_window_size to a value that is appropriate for the length of the magnitudes array.

No dominant frequency found

• Explanation: This error occurs when no frequencies within the specified range have magnitudes above the magnitude_threshold.
• Solution: Lower the magnitude_threshold to include more frequencies in the analysis, or check if the min_frequency and max_frequency parameters are set correctly.