我正在尝试通过scikit-image提取球体特征,但出现错误The parameter image must be a 2-dimensional array
。我将其转换为灰度,因此图像实际上是二维的。
from skimage.feature import ORB
from skimage.color import rgb2gray
def find_orb(img, n_keypoints=2000, **kwargs):
descriptor_extractor = ORB(n_keypoints, **kwargs)
descriptor_extractor.detect_and_extract(rgb2gray(img))
return descriptor_extractor.keypoints, descriptor_extractor.descriptors
pano_image_collection = io.ImageCollection('jpeg/lowres/8_*.jpg',
load_func=lambda f:io.imread(f).astype(np.float32) / 255)
img = pano_image_collection[0]
keypoints, descriptors = find_orb(img)
这是错误
ValueError Traceback (most recent call last)
<ipython-input-5-5dce31f8d3f4> in <module>()
----> 7 keypoints, descriptors = find_orb(img)
<ipython-input-4-26e09ccf38ce> in find_orb(img, n_keypoints, **kwargs)
14 descriptor_extractor = ORB(n_keypoints, **kwargs)
---> 15 descriptor_extractor.detect_and_extract(rgb2gray(img))
16 return descriptor_extractor.keypoints, descriptor_extractor.descriptors
/usr/local/lib/python3.6/site-packages/skimage/feature/orb.py in detect_and_extract(self, image)
302
303 keypoints, orientations, responses = \
--> 304 self._detect_octave(octave_image)
305
306 if len(keypoints) == 0:
/usr/local/lib/python3.6/site-packages/skimage/feature/orb.py in _detect_octave(self, octave_image)
139 # Extract keypoints for current octave
140 fast_response = corner_fast(octave_image, self.fast_n,
--> 141 self.fast_threshold)
142 keypoints = corner_peaks(fast_response, min_distance=1)
143
/usr/local/lib/python3.6/site-packages/skimage/feature/corner.py in corner_fast(image, n, threshold)
745
746 """
--> 747 image = _prepare_grayscale_input_2D(image)
748
749 image = np.ascontiguousarray(image)
/usr/local/lib/python3.6/site-packages/skimage/feature/util.py in _prepare_grayscale_input_2D(image)
140 def _prepare_grayscale_input_2D(image):
141 image = np.squeeze(image)
--> 142 assert_nD(image, 2)
143 return img_as_float(image)
144
/usr/local/lib/python3.6/site-packages/skimage/_shared/utils.py in assert_nD(array, ndim, arg_name)
176 raise ValueError(msg_empty_array % (arg_name))
177 if not array.ndim in ndim:
--> 178 raise ValueError(msg_incorrect_dim % (arg_name, '-or-'.join([str(n) for n in ndim])))
179
180
ValueError: The parameter `image` must be a 2-dimensional array
答案 0 :(得分:1)
恐怕我无能为力了:
我使用调试器运行它,并且在ORB内部创建的金字塔第二层上的图像只有一个条目和形状为(1, 1)
,它将在随后的{{1 }}。
更新:Op(Daria Musatkina)找到了解决此问题的方法,并引用:
这里的问题是orb的第一个参数是降采样而不是n_keypoints。这就是创建形状为np.squeeze
的八度音阶的原因。
我的最初答案不正确(请参见下面的评论):
我假设您的图像是RGB,可能是作为2D +通道(总共3D)导入的,(1, 1)
有numpy.ndarray
个条目。 uint8
不会更改图像的尺寸,只会更改数据类型。现在,您有了一个ndarray.astype
的3D数组,而不是uint8
的3D数组,它们的值相同(此处未考虑任何数字误差)。因此,您没有转换为灰度空间,只是更改了数组的数据类型。例如,您可以尝试沿通道轴使用np.mean
。