import numpy as np def hist_match ( source , template ): """ Adjust the pixel values of a grayscale image such that its histogram matches that of a target image Arguments: ----------- source: np.ndarray Image to transform; the histogram is computed over the flattened array template: np.ndarray Template image; can have different dimensions to source Returns: ----------- matched: np.ndarray The transformed output image """ oldshape = source . shape source = source . ravel () template = template . ravel () # get the set of unique pixel values and their corresponding indices and # counts s_values , bin_idx , s_counts = np . unique ( source , return_inverse = True , return_counts = True ) t_values , t_counts = np . unique ( template , return_counts = True ) ...
본노이만 컴퓨터 구조랑 닮았다. 그러나 컴퓨터는 보상이 없고 환경묘사가 복잡.
답글삭제동전 던지기는 현상태와 다음 상태가 독립적이다. 로또 복권도 마찬가지
답글삭제그러나 복권예언가들 생각은 다르지...