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
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.
Links
- Repository: https://github.com/sync-dev-org/pixtreme
Project details
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