Python bindings for the rawler RAW image processing library
Project description
rawler-py
Python bindings for the rawler Rust crate — high-performance RAW image decoding with NumPy output.
Installation
pip install rawler-py
Usage
import rawler_py
from pathlib import Path
# Use context manager for automatic resource cleanup
with rawler_py.RawImage.open("path_to_raw") as img:
# Basic Metadata
print(f"{img.make} {img.model} | {img.width}x{img.height}")
print(f"Orientation: {img.orientation} | Bits: {img.bps}")
# Sensor Parameters
print(f"CFA Pattern: {img.cfa_pattern}")
print(f"White Balance Coeffs: {img.wb_coeffs}")
print(f"Black Level: {img.blacklevel}") # {'levels': [...], 'width': 6, 'height': 6, 'cpp': 1}
print(f"White Level: {img.whitelevel}")
# Area definitions
if img.crop_area:
print(f"Crop Area: {img.crop_area}") # (x, y, w, h)
# Get raw sensor data as NumPy arrays
data = img.raw_data() # uint16, shape (height, width)
f32_data = img.raw_data_f32() # float32
# Automatically apply sensor crop/active area
cropped = img.cropped_raw_data()
License
LGPL-2.1 — same as the underlying rawler crate.
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