data module

class data.DataProcessor(image_dir, dir_type='image', target_size=(512, 512), image_suffix='tif')[source]

Bases: Generic[torch.utils.data.dataset.T_co]

to_uint8(image)[source]
transform(image)[source]
Parameters

  • image – Stacked image eg (71, 1200, 1200)

  • mask – Stacked mask eg (71, 1200, 1200)

Returns

Transformed images that have been randomly cropped, flipped, and resized to the target size.

data.convertScaleAbs(src[, dst[, alpha[, beta]]]) → dst

. @brief Scales, calculates absolute values, and converts the result to 8-bit. . . On each element of the input array, the function convertScaleAbs . performs three operations sequentially: scaling, taking an absolute . value, conversion to an unsigned 8-bit type: . f[texttt{dst} (I)= texttt{saturate_cast<uchar>} (| texttt{src} (I)* texttt{alpha} + texttt{beta} |)f] . In case of multi-channel arrays, the function processes each channel . independently. When the output is not 8-bit, the operation can be . emulated by calling the Mat::convertTo method (or by using matrix . expressions) and then by calculating an absolute value of the result. . For example: . @code{.cpp} . Mat_<float> A(30,30); . randu(A, Scalar(-100), Scalar(100)); . Mat_<float> B = A*5 + 3; . B = abs(B); . // Mat_<float> B = abs(A*5+3) will also do the job, . // but it will allocate a temporary matrix . @endcode . @param src input array. . @param dst output array. . @param alpha optional scale factor. . @param beta optional delta added to the scaled values. . @sa Mat::convertTo, cv::abs(const Mat&)