get_dapi.py

import tifffile as tiff
from pathlib import Path
from typing import Union
import numpy as np
from memory_profiler import profile
import time

@profile
def extract_dapi_channel(reg_path: Union[str, Path], dapi_channel: int) -> np.ndarray:
    """
    Extracts the DAPI channel lazily without loading the entire image into memory.

    Parameters:
    - reg_path (str or Path): Path to the registered image file.
    - dapi_channel (int): Index of the DAPI channel in the image array.

    Returns:
    - np.ndarray: Extracted DAPI image as a NumPy array.

    Raises:
    - FileNotFoundError: If the specified file does not exist at reg_path.
    - ValueError: If the DAPI channel index is out of bounds for the image.
    """
    reg_path = Path(reg_path)
    
    try:
        with tiff.TiffFile(reg_path) as tif:
            # Check the number of channels
            image_shape = tif.series[0].shape  # Shape of the multi-channel image
            print(f"Image shape: {image_shape}")
            
            if dapi_channel < 0 or dapi_channel >= image_shape[0]:
                raise ValueError(f"DAPI channel index {dapi_channel} is out of bounds for the image shape {image_shape}.")
            
            # Extract the desired channel lazily
            #dapi = tif.series[0].levels[0][dapi_channel]
            dapi = tif.series[0].levels[0][dapi_channel].asarray()
            print(f"Extracted DAPI channel. Shape: {dapi.shape}, Data type: {dapi.dtype}")
            return dapi
    
    except FileNotFoundError as e:
        raise FileNotFoundError(f"Could not find the file: {reg_path}") from e
    except Exception as e:
        raise IOError(f"An error occurred while processing the image file: {reg_path}") from e