Downloads provided by UsageCounts
imea is an open source Python package for extracting 2D and 3D shape measurements from images. The current version of imea enables the extraction of 53 different 2D shape measurements, covering macrodescriptors such as minimal bounding boxes, mesodescriptors such as the numbers of erosion to erase a binary image, microdescriptors such as the fractal dimension as well as statistical lengths like Feret, Martin or Nassenstein diameters. Furthermore, 13 different 3D shape measurements ranging from volume and minimal 3D bounding boxes to 3D Feret diameters and maximum dimensions can be extracted. Both 2D shapes, represented as 2D binary images, as well as 3D shapes, represented as grayscale images where the grayvalue of each pixel represents its height, can be analyzed automatically with a single function call. Extracted shape measurements are returned as a pandas dataframe and by specifying the spatial resolution of inserted images, results are automatically converted into metric units for further quantitative analysis.
Image processing, Shape measurements, Python
Image processing, Shape measurements, Python
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 13 | |
| downloads | 2 |

Views provided by UsageCounts
Downloads provided by UsageCounts