Generic Optimization by Genetically Evolved Operation Trees

Create easy-to-use Query objects that can apply on NumPy structured arrays, astropy Table, and Pandas DataFrame

Get the difference between 2 images

faster image quality metrics than skimage (PSNR, SSIM, MS-SSIM)

Locate RGB values in a picture! 40x faster than PIL, 5x faster than numpy

Fast multitemplate matching with support for different sizes using numexpr / cupy / fftw / scipy / multiprocessing

Calculate overlapping values between two arrays and return the results as a DataFrame

Up to 25 times faster than df.loc by combining np.select and numexpr.evaluate (works with utf-8)

Counts the unique colors in an image and returns a DataFrame with color counts and optional color coordinates.

finds sequences [3, 4, 5] in NumPy arrays [1, 2, 3, 4, 5, 1, 2, 3, 4, 5] - result: [2 7]

Converts an image to ASCII art using numpy / numexpr / cv2

Splits the elements in a Series using a common separator character and returns a DataFrame.

Uses pandas/numpy/numexpr for operations on pictures - very fast

Finds rectangle intersections

Pandas DataFrame/Series operations 8 times faster (or even more)

Um projeto de calculadora desenvolvido em Python utilizando a biblioteca PySide6 para criar uma interface gráfica intuitiva. A calculadora oferece funcionalidades básicas de cálculo, como adição, subtração, multiplicação e divisão.