det_lesion.py 文件源码

def preprocess_labels(label):
    """Preprocess the labels to adapt them to the loss computation requirements
    Args:
    Label corresponding to the input image (W,H) numpy array
    Returns:
    Label ready to compute the loss (1,W,H,1)
    """
    labels = [[] for i in range(np.array(label).shape[0])]  

    for j in range(np.array(label).shape[0]):
        if type(label) is not np.ndarray:
            for i in range(3):
                aux = np.array(Image.open(label[j][i]), dtype=np.uint8)
                crop = aux[int(float(x_bb[j])):int((float(x_bb[j])+80)), int(float(y_bb[j])): int((float(y_bb[j])+80))]
                labels[j].append(crop)

    label = np.array(labels[0])
    label = label.transpose((1,2,0))
    label = label[:, :, ::-1]
    max_mask = np.max(label) * 0.5
    label = np.greater(label, max_mask)
    label = np.expand_dims(label, axis=0)

    return label