import numpy as np
import rasterio
from rasterio.plot import show

import cv2

def read_pansharpened_rgb(file_path):
    with rasterio.open(file_path) as src:
        # Read all bands
        image = src.read()
        
        # Check the number of bands
        num_bands = image.shape[0]
        
        if num_bands >= 3:
            # If we have 3 or more bands, use the first three as RGB
            rgb_image = image[:3]
        else:
            raise ValueError(f"The image has only {num_bands} bands. At least 3 bands are required for RGB.")
        
        # Transpose the image to have the bands as the last dimension
        rgb_image = np.transpose(rgb_image, (1, 2, 0))
        
        # Normalize each band separately
        r = normalize_band(rgb_image[:,:,0])
        g = normalize_band(rgb_image[:,:,1])
        b = normalize_band(rgb_image[:,:,2])
        
        # Combine the normalized bands
        rgb_normalized = np.dstack((r, g, b))
        
    return rgb_normalized

def normalize_band(band):
    """Normalize a single band to 0-255 range."""
    min_val = np.min(band)
    max_val = np.max(band)
    if max_val > min_val:
        normalized = ((band - min_val) / (max_val - min_val) * 255).astype(np.uint8)
    else:
        normalized = np.zeros_like(band, dtype=np.uint8)
    return normalized

# Example usage

# Display the image using matplotlib