import cv2
import numpy as np

# Load an image in color (default)
img_color = cv2.imread('path/to/your/image.jpg', cv2.IMREAD_COLOR)

# Load an image in grayscale
img_gray = cv2.imread('path/to/your/image.jpg', cv2.IMREAD_GRAYSCALE)

# Load an image with an alpha channel (if available)
img_alpha = cv2.imread('path/to/your/image.png', cv2.IMREAD_UNCHANGED)

# Check if the image was loaded successfully
if img_color is None:
    print("Error: Could not load image.")
else:
    print("Image loaded successfully.")
    # img_color is a NumPy array representing the image
    print(f"Image shape (color): {img_color.shape}") # (height, width, channels)
    print(f"Image data type: {img_color.dtype}")

import cv2

# Assuming img_color is a loaded OpenCV image
if img_color is not None:
    cv2.imshow('Color Image', img_color)
    cv2.imshow('Grayscale Image', img_gray) # Assuming img_gray is also loaded

    # Wait indefinitely until a key is pressed
    cv2.waitKey(0)

    # Destroy all OpenCV windows
    cv2.destroyAllWindows()

import cv2

# Assuming img_color is a loaded OpenCV image
if img_color is not None:
    # Save the image in JPEG format
    cv2.imwrite('output_color_image.jpg', img_color)

    # Save the image in PNG format (good for lossless compression and transparency)
    cv2.imwrite('output_grayscale_image.png', img_gray)

    print("Images saved successfully.")

from PIL import Image
import numpy as np

try:
    # Load an image
    img_pil = Image.open('path/to/your/image.jpg')

    print("Image loaded successfully with PIL.")
    print(f"Image format: {img_pil.format}")
    print(f"Image mode: {img_pil.mode}") # e.g., 'RGB', 'L' (grayscale), 'RGBA'
    print(f"Image size: {img_pil.size}") # (width, height)

    # Convert to NumPy array if needed for further processing with libraries like OpenCV
    img_np = np.array(img_pil)
    print(f"NumPy array shape: {img_np.shape}") # (height, width, channels) for RGB

except FileNotFoundError:
    print("Error: Image file not found.")
except Exception as e:
    print(f"An error occurred: {e}")

from PIL import Image

try:
    # Assuming img_pil is a loaded PIL Image object
    img_pil.show()
    # This typically opens the image in your system's default image viewer.
except Exception as e:
    print(f"An error occurred: {e}")

from PIL import Image

try:
    # Assuming img_pil is a loaded PIL Image object
    # Save the image in a different format (e.g., PNG)
    img_pil.save('output_image_pil.png')

    # You can also specify compression levels for formats like JPEG
    # img_pil.save('output_image_pil_compressed.jpg', quality=85)

    print("Image saved successfully with PIL.")
except Exception as e:
    print(f"An error occurred: {e}")

import cv2
import os

# Define input and output file paths
input_image_path = 'path/to/your/color_image.jpg'
output_gray_path = 'output_grayscale_opencv.jpg'

# --- 1. Load the image in color ---
img_color = cv2.imread(input_image_path, cv2.IMREAD_COLOR)

if img_color is None:
    print(f"Error: Could not load image from {input_image_path}")
else:
    print(f"Successfully loaded color image: {input_image_path}")

    # --- 2. Convert the image to grayscale ---
    img_gray = cv2.cvtColor(img_color, cv2.COLOR_BGR2GRAY)
    print("Converted image to grayscale.")

    # --- 3. Display the original and grayscale images ---
    cv2.imshow('Original Color Image', img_color)
    cv2.imshow('Grayscale Image', img_gray)
    print("Displaying images. Press any key to continue...")

    # Wait for a key press to close the windows
    cv2.waitKey(0)
    cv2.destroyAllWindows()

    # --- 4. Save the grayscale image ---
    success = cv2.imwrite(output_gray_path, img_gray)
    if success:
        print(f"Grayscale image saved successfully to: {output_gray_path}")
    else:
        print(f"Error: Failed to save grayscale image to {output_gray_path}")

from PIL import Image
import os

# Define input and output file paths
input_image_path = 'path/to/your/image.png'
output_resized_path = 'output_resized_pil.png'
new_width = 300
new_height = 200 # Or calculate based on aspect ratio

# --- 1. Load the image using PIL ---
try:
    img_pil = Image.open(input_image_path)
    print(f"Successfully loaded image with PIL: {input_image_path}")
    print(f"Original size: {img_pil.size}")

    # --- 2. Resize the image ---
    # PIL uses (width, height) for size
    resized_img_pil = img_pil.resize((new_width, new_height))
    print(f"Resized image to: {resized_img_pil.size}")

    # --- 3. Display the resized image (optional, opens in default viewer) ---
    # resized_img_pil.show()

    # --- 4. Save the resized image ---
    resized_img_pil.save(output_resized_path)
    print(f"Resized image saved successfully to: {output_resized_path}")

except FileNotFoundError:
    print(f"Error: Image file not found at {input_image_path}")
except Exception as e:
    print(f"An error occurred: {e}")