only led

     # Import libraries
import cv2
import numpy as np
import matplotlib.pyplot as plt
from google.colab.patches import cv2_imshow

# Load image
image = cv2.imread('image.jpg')

# Show original image
cv2_imshow(image)

# ------------------------------------------------
# 1. Observe image size (dimensions)
# ------------------------------------------------
height, width, channels = image.shape

print("Width =", width)
print("Height =", height)
print("Channels =", channels)

# Resolution
print("Resolution =", width, "X", height)

# Total pixels
total_pixels = width * height
print("Total Pixels =", total_pixels)

# ------------------------------------------------
# 2. Scaleup image by factor 2
# ------------------------------------------------
scaled_image = cv2.resize(image, None, fx=2, fy=2)

print("Scaled Image Created")

# ------------------------------------------------
# 3. Median Filter (Denoise)
# ------------------------------------------------
median = cv2.medianBlur(image, 5)

print("Median Filter Applied")

# ------------------------------------------------
# 4. Sharpen the image
# ------------------------------------------------
kernel = np.array([[0, -1, 0],
                   [-1, 5, -1],
                   [0, -1, 0]])

sharpened = cv2.filter2D(image, -1, kernel)

print("Sharpening Applied")

# ------------------------------------------------
# 5. Invert image colors
# ------------------------------------------------
inverse_image = 255 - image

print("Inverse Image Created")

# ------------------------------------------------
# Display all images
# ------------------------------------------------
plt.figure(figsize=(12,8))

# Original
plt.subplot(2,3,1)
plt.title("Original")
plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
plt.axis('off')

# Scaled
plt.subplot(2,3,2)
plt.title("Scaled x2")
plt.imshow(cv2.cvtColor(scaled_image, cv2.COLOR_BGR2RGB))
plt.axis('off')

# Median Filter
plt.subplot(2,3,3)
plt.title("Median Filter")
plt.imshow(cv2.cvtColor(median, cv2.COLOR_BGR2RGB))
plt.axis('off')

# Sharpened
plt.subplot(2,3,4)
plt.title("Sharpened")
plt.imshow(cv2.cvtColor(sharpened, cv2.COLOR_BGR2RGB))
plt.axis('off')

# Inverse
plt.subplot(2,3,5)
plt.title("Inverse")
plt.imshow(cv2.cvtColor(inverse_image, cv2.COLOR_BGR2RGB))
plt.axis('off')

plt.tight_layout()
plt.show()







        import cv2
import numpy as np
from google.colab.patches import cv2_imshow

image = cv2.imread('/content/image.jpg')

print("Original Image:")
cv2_imshow(image)

height, width, channels = image.shape

print("Image Width :", width)
print("Image Height:", height)
print("Channels    :", channels)

scaled_image = cv2.resize(image, None, fx=2, fy=2)

print("Scaled Image:")
cv2_imshow(scaled_image)

median_filtered = cv2.medianBlur(scaled_image, 5)

print("Median Filter Applied:")
cv2_imshow(median_filtered)

kernel = np.array([[0, -1, 0],
                   [-1, 5,-1],
                   [0, -1, 0]])

sharpened_image = cv2.filter2D(median_filtered, -1, kernel)

print("Sharpened Image:")
cv2_imshow(sharpened_image)

inverted_image = cv2.bitwise_not(sharpened_image)

print("Inverted Color Image:")
cv2_imshow(inverted_image)