kjanko
Remove redundant np.array() conversion for better efficiency
https://github.com/kjanko/python-fingerprint-recognition/blob/65a6ceba509469f3f838fb91e59eb0c5ee1d0a0a/app.py#L12
In the current code:
temp0 = numpy.array(invertThin[:]) temp0 = numpy.array(temp0)
the second np.array() call is redundant and introduces unnecessary memory allocation and processing overhead. Since temp0 is already a NumPy array after the first line, wrapping it again with numpy.array() simply creates a copy of the same array, which is not needed here and may degrade performance, especially when dealing with large datasets.
If the goal is simply to ensure the data is a NumPy array, a single numpy.array() call is sufficient. Even better, numpy.asarray() can be used to avoid copying if invertThin is already an array:
temp0 = numpy.asarray(invertThin)
This improves performance while preserving the same functionality. Removing the redundant line would make the code cleaner and more efficient.
