PhotoFF Documentation
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()
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