GitHub

cv2.imread() from 16-bit TIFF creates arrays where np.maximum() fails in function context but works directly

Platform: macOS-15.6.1 (arm64) Python 3.14.2 OpenCV: 4.11.0 NumPy: 2.2.6 cv2.imread() with 16-bit TIFF files creates float32 arrays that cause np.maximum() and np.minimum() to behave inconsistently.
marktechpost

This AI Paper Introduces PyVision: A Python-Centric Framework Where AI Writes Tools as It Thinks

Visual reasoning tasks challenge artificial intelligence models to interpret and process visual information using both perception and logical reasoning. These tasks span a wide range of applications, ...
Frontiers

Automatic segmentation and volume measurement of anterior visual pathway in brain 3D-T1WI using deep learning

Objective: Accurate anterior visual pathway (AVP) segmentation is vital for clinical applications, but manual delineation is time-consuming and resource-intensive. We aim to explore the feasibility of ...
IEEE

Legate NumPy: Accelerated and Distributed Array Computing

Abstract: NumPy is a popular Python library used for performing array-based numerical computations. The canonical implementation of NumPy used by most programmers runs on a single CPU core and is ...
GitHub

Arbrea-Labs/3rdparty_pybind_opencv_implicit_conversion

Sub-matrices created from C++ can also be shared to python Sub-matrices created from python will need to be transformed to a contiguous array before being shared to C++ ...
IEEE

Real Time Object Recognition Using OpenCV and Numpy in Python

Abstract: Object recognition is the process of recognizing objects based on their characteristics like color, shape, and with the particular occurrence of the object in digital videos and as well as ...