deephyp.data.HypImg¶
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class
deephyp.data.HypImg(spectralInput, labels=None, wavelengths=None, bands=None)[source]¶ Class for handling data. Stores meta-data and contains attributes for pre-processing the data. If passed labels, samples with label zero are considered as a background class. This class is not included in numClasses and data samples with this label have a one-hot vector label of all zeros.
Parameters: - spectralInput (np.array float) – Spectral dataset. Shape can be [numRows x numCols x numBands] or [numSamples x numBands].
- wavelengths (np.array float) – Vector of wavelengths that spectralInput wavelengths lie within.
- bands (np.array int) – Wavelength indexes for each band of spectralInput. Shape [numBands].
- labels (np.array int) – Class labels for each spectral sample in spectralInput. Shape can be [numRows x numCols] or [numSamples].
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spectra¶ Un-pre-processed spectral data with shape [numSamples x numBands].
Type: np.array float
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spectraCube¶ If data passed as image - un-pre-processed spectral datacube with shape [numSamples x numBands]. Else None.
Type: np.array float
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spectraPrep¶ Pre-processed spectral data with shape [numSamples x numBands].
Type: np.array float
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numSamples¶ The number of spectra.
Type: int
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numRows¶ If data passed as image - the number of image rows. Else None.
Type: int
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numCols¶ If data passed as image - the number of image columns. Else None.
Type: int
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wavelengths¶ If provided - vector of wavelengths that spectra wavelengths lie within. Else None.
Type: np.array float
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bands¶ If provided - wavelength indexes for each band of spectra with shape [numBands]. Else None.
Type: np.array int
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labels¶ If provided - class labels for each spectral sample with shape [numSamples]. Else None.
Type: np.array int
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labelsOnehot¶ If labels provided - the one-hot label vector for each sample. Samples with label zero (background class) have a one-hot vector of all zeros. Else None.
Type: np.array int