Particle Picking of Cryo-EM Datasets
Project description
cryoblob
cryoblob is a JAX-based, JIT-compiled, scalable package for detection of amorphous blobs in low SNR cryo-EM images.
Features
- JAX-powered: Leverages JAX for high-performance computing with automatic differentiation
- GPU acceleration: Can utilize both CPUs and GPUs for processing
- Adaptive filtering: Includes adaptive Wiener filtering and thresholding
- Blob detection: Advanced blob detection using Laplacian of Gaussian (LoG) methods
- Batch processing: Memory-optimized batch processing for large datasets
- Validation: Comprehensive parameter validation using Pydantic models
Installation
pip install cryoblob
Quick Start
import cryoblob as cb
# Load an MRC file
mrc_image = cb.load_mrc("your_file.mrc")
# Process a folder of images
results = cb.folder_blobs("path/to/folder/")
# Plot results
cb.plot_mrc(mrc_image)
Package Structure
The cryoblob package is organized into the following modules:
- adapt: Adaptive image processing with gradient descent optimization
- blobs: Core blob detection algorithms and preprocessing
- files: File I/O operations and batch processing
- image: Basic image processing functions (filtering, resizing, etc.)
- plots: Visualization functions for MRC images and results
- types: Type definitions and PyTree structures
- valid: Parameter validation using Pydantic models
Package Organization
- The codes are located in
/src/cryoblob/ - The notebooks are located in
/tutorials/
Documentation
For detailed API documentation and tutorials, visit: https://cryoblob.readthedocs.io
License
This project is licensed under the MIT License - see the LICENSE file for details.
Authors
- Debangshu Mukherjee (mukherjeed@ornl.gov)
- Alexis N. Williams (williamsan@ornl.gov)
Project details
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