docs: Correct docstrings for Blob tasks
@@ -28,7 +28,7 @@ class BlobTask(EOTask):
determinant of the Hessian (DoH).
The output is a FeatureType.DATA where the radius of each blob is stored in his center.
- ie : If blob[date, i, j, 0] = 5 then a blob of radius 5 is present at he coordinate (i, j)
+ ie : If blob[date, i, j, 0] = 5 then a blob of radius 5 is present at the coordinate (i, j)
The task uses skimage.feature.blob_log or skimage.feature.blob_dog or skimage.feature.blob_doh to extract the blobs.
@@ -41,13 +41,13 @@ class BlobTask(EOTask):
:type feature: (FeatureType, str) or (FeatureType, str, str)
:param blob_object: Name of the blob method to use
- :type blob_object: skimage.features.blob_*
+ :type blob_object: skimage.feature.blob_*
:param blob_parameters: List of parameters to be passed to the blob function. Below a list of such parameters.
:type blob_paramters: dict
:param min_sigma: The minimum standard deviation for Gaussian Kernel. Keep this low to detect smaller blobs
:type min_sigma: float
:param max_sigma: The maximum standard deviation for Gaussian Kernel. Keep this high to detect larger blobs
- :type float
+ :type max_sigma: float
:param threshold: The absolute lower bound for scale space maxima. Local maxima smaller than thresh are ignored.
Reduce this to detect blobs with less intensity
:type threshold: float
@@ -108,7 +108,7 @@ class DoGBlobTask(BlobTask):
class DoHBlobTask(BlobTask):
- """ Task to compute blobs with Laplacian of Gaussian (LoG) method
+ """ Task to compute blobs with Determinant of the Hessian (DoH) method
"""
def __init__(self, feature, *, num_sigma=10, log_scale=False, min_sigma=1, max_sigma=30, threshold=0.1, overlap=0.5,
**kwargs):
