從切片重建 2D 影像#

sklearn.feature_extraction.image.reconstruct_from_patches_2d(patches, image_size)[來源]#

從所有切片重建影像。

假設切片重疊，影像的建構方式是從左到右、從上到下填入切片，並平均重疊區域。

在使用者指南中閱讀更多。

參數:
patches形狀為 (n_patches, patch_height, patch_width) 或 (n_patches, patch_height, patch_width, n_channels) 的 ndarray

完整的切片集合。 如果切片包含色彩資訊，則通道會沿著最後一個維度索引：RGB 切片將具有 n_channels=3。

image_size整數元組 (image_height, image_width) 或 (image_height, image_width, n_channels)

將重建的影像大小。

返回:
image形狀為 image_size 的 ndarray

重建的影像。

範例

>>> from sklearn.datasets import load_sample_image
>>> from sklearn.feature_extraction import image
>>> one_image = load_sample_image("china.jpg")
>>> print('Image shape: {}'.format(one_image.shape))
Image shape: (427, 640, 3)
>>> image_patches = image.extract_patches_2d(image=one_image, patch_size=(10, 10))
>>> print('Patches shape: {}'.format(image_patches.shape))
Patches shape: (263758, 10, 10, 3)
>>> image_reconstructed = image.reconstruct_from_patches_2d(
...     patches=image_patches,
...     image_size=one_image.shape
... )
>>> print(f"Reconstructed shape: {image_reconstructed.shape}")
Reconstructed shape: (427, 640, 3)