Search Results for "image steganography code"

LearnOpenCV is a large educational repository that provides practical computer vision and deep learning examples in both Python and C++. The project accompanies the LearnOpenCV blog and contains hundreds of hands-on tutorials covering topics such as object detection, image processing, pose estimation, and neural networks. It is structured as a learning resource where each directory corresponds to a specific article or technical walkthrough. The repository supports beginners and advanced practitioners by offering reproducible code that demonstrates real-world computer vision techniques. Many examples integrate popular frameworks like PyTorch, OpenCV, and ONNX to reflect modern AI workflows. ...

FLUX.2-klein-4B is a compact, high-performance C library implementation of the Flux optimization algorithm — an iterative approach for solving large-scale optimization problems common in scientific computing, machine learning, and numerical simulation. Written with a strong emphasis on simplicity, correctness, and performance, it abstracts the core logic of flux-based optimization into a minimal C API that can be embedded in broader applications without pulling in heavy dependencies. Because...

...Using components like graph-based workflow design, drag-and-drop UI (via TMAN Designer), and reusable extensions such as real-time avatars, RAG (Retrieval-Augmented Generation), and image generation, TEN enables highly customizable, scalable agent development with minimal code.

One more lightweight neural network in C.

QCV is a Qt-based computer vision framework library that provides an easy to use interface to display, analyze and run computer vision algorithms. The library is provided with practical examples to show what you can do with just a few lines of code. OpenCV is used as the supporting computer vision library. QCV provides interfaces for C and C++. The C interface is a set of simple function calls to allow the user to visualize data and obtain events from the system and user input. The...

...Our approach achieves on average 97.0% linkage accuracy across all species and imaging modalities." *Please cite this paper if you use this code for your research

...This is a software toolbox that collects software implementations of the Local Binary Pattern operator in several platforms: - OpenCL for CPU & GPU - OpenCL for GPU (branchless) - C code optimized for ARM - OpenGL ES 2.0 shaders mobile GPUs - C code for TI C64x DSP core (branchless) - C code for TTA processor synthesis If you use the code somewhere, please cite: Bordallo López M., Nieto A., Boutellier J., Hannuksela J., and Silvén O. "Evaluation of real-time LBP computing in multiple architectures," Journal of Real Time Image Processing, 2014