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GPU-accelerated image filtering operations for pixtreme

Project description

pixtreme-filter

GPU-accelerated image filtering operations for pixtreme

Overview

pixtreme-filter provides high-performance image filtering operations running on CUDA-enabled GPUs. All operations are optimized for real-time performance and work directly on GPU memory.

Features

  • Gaussian Blur: GPU-accelerated Gaussian blur with separable kernels
  • Zero-Copy Operations: Direct GPU memory processing via CuPy
  • Flexible Interface: Functional API and class-based API

Installation

Requirements:

  • Python >= 3.12
  • CUDA Toolkit 12.x
  • NVIDIA GPU with compute capability >= 6.0
pip install pixtreme-filter

Requires pixtreme-core and CUDA Toolkit 12.x.

Quick Start

import pixtreme_filter as pf
import pixtreme_core as px

# Read image
img = px.imread("input.jpg")

# Apply Gaussian blur
blurred = pf.gaussian_blur(img, ksize=15, sigma=3.0)

# Save result
px.imwrite("output.jpg", blurred)

API

Gaussian Blur

# Functional API
blurred = pf.gaussian_blur(image, ksize=15, sigma=3.0)

# Class-based API (for repeated operations with same parameters)
blur = pf.GaussianBlur()
blurred = blur.get(image, ksize=15, sigma=3.0)

# Get kernel for custom operations
kernel = pf.get_gaussian_kernel(ksize=15, sigma=3.0)

License

MIT License - see LICENSE file for details.

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