Question

我正在编写一个自定义损失函数，其中损失= y_true-conv2D（y_pred，filter_matrix）。滤镜矩阵的大小与y_pred相同，我想将y_pred中的第一幅图像与矩阵中的第一个滤镜进行卷积。我需要帮助弄清楚如何传递此矩阵并正确执行卷积（图像卷积而不是图层）。

我发现这篇帖子conv2d in custom Keras loss function中，用户仅对所有图像使用一个内核。

我正在使用MNIST数据集，因此是数据的宽度和高度的大小。这是我的损失函数。文件train1只有一行，但理想情况下，我希望它的大小与y_true和y_pred相同。

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当然，当我选择包含更多条目的文件时，就会出现此错误。

def custom_loss(y_true, y_pred):
    filename = 'train1.csv'
    raw_data = open(filename, 'rt')
    filters_train = np.loadtxt(raw_data, delimiter=",")
    filters_train = filters_train.astype('float32')
    filters_train = np.reshape(filters_train, (28, 28, 1, 1))
    predlap = k.conv2d(y_pred, filters_train)
    predlap = (predlap-k.min(predlap))/(k.max(predlap)-k.min(predlap))
    loss = losses.mean_squared_error(y_true, predlap)
    return loss

如果您知道更好的方法，请告诉我。

conv2d用于自定义Keras损失函数中的多个滤波器

0 个答案: