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PhotoFF Documentation

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PhotoFF is a high-performance image processing library that uses CUDA to achieve exceptional processing speeds. Designed to maximize performance through efficient GPU memory management.

Basic Example

from photoff.operations.filters import apply_gaussian_blur, apply_corner_radius
from photoff.io import save_image, load_image
from photoff import CudaImage

# Load the image in GPU memory
src_image: CudaImage = load_image("./assets/stock.jpg")

# Apply filters
apply_gaussian_blur(src_image, radius=5.0)
apply_corner_radius(src_image, size=200)

# Save the result
save_image(src_image, "./assets/gaussian_blur_test.png")

# Free the image from GPU memory
src_image.free()

Gaussian Blur Test

Key Features

  • Pythonic Interface: Clean, intuitive API designed for both beginners and advanced users
  • Robust Image Manipulation: Comprehensive suite of operations including filters, transforms, and compositing
  • Seamless Integration: Works with common image formats through PIL interoperability
  • CUDA-Accelerated Processing: Harness the power of your GPU for blazing-fast image operations
  • Memory-Efficient Design: Optional advanced memory management for optimized buffer management

Next Steps

Now that you understand the basics, you can:

  • Explore the Basic Operations to learn about loading, saving, and manipulating images
  • Dive into the Advanced Operations to discover more complex image processing techniques
  • Check out the API Reference for detailed documentation on all available functions and classes