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{
"cells": [
{
"cell_type": "code",
"execution_count": 5,
"id": "2a48ed33-0649-440a-a672-366eccecc595",
"metadata": {},
"outputs": [],
"source": [
"import cv2\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "79e94481-02c5-41df-b243-b5ab9d6215cf",
"metadata": {},
"outputs": [],
"source": [
"white_img=np.full((400,500),255,dtype=np.uint8) # Create a white image (400x500 pixels) with all values set to 255."
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "dafbe73b-1c9a-4ecd-a97b-273066fa722b",
"metadata": {},
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{
"data": {
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"True"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cv2.imwrite(r\"C:\\Users\\Singh\\Downloads\\flower_photos\\white.jpg\",white_img) # Save the white image as \"white.jpg\" in the specified directory."
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "84e50e23-dcac-4d6a-b1b9-a3cf10d4e4f0",
"metadata": {},
"outputs": [],
"source": [
"img=cv2.imread(r\"C:\\Users\\Singh\\Downloads\\flower_photos\\tulips\\54895006_55b49052dc.jpg\") # Load the image \"tulips\" from the specified directory."
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "2f465e89-1151-4e14-ad1d-14208ee8ba43",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(333, 500, 3)"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"img.shape # Get the shape of the image (height, width, and color channels)."
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "0b34448d-47eb-45be-8595-b08f1a17716d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(333, 500)"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"img.shape[:-1] # Get only the height and width of the image by excluding the color channels."
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "39a4831e-4415-4699-a0ae-24222370e0c3",
"metadata": {},
"outputs": [],
"source": [
"b,g,r=cv2.split(img) # Split the image into its blue (b), green (g), and red (r) channels."
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "d56c4865-f80f-4cd7-af69-1b3437cb8315",
"metadata": {},
"outputs": [],
"source": [
"zeros=np.zeros(img.shape[:-1],dtype=np.uint8) # Create a zero matrix with the same height and width as the image for masking."
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "cd625553-7992-4706-aae7-4bbaaf9daee6",
"metadata": {},
"outputs": [],
"source": [
"blue_channel=cv2.merge([b,zeros,zeros]) # Create the blue channel by combining the blue channel and zero matrices for other channels.\n",
"green_channel=cv2.merge([zeros,b,zeros]) # Create the green channel by combining the green channel and zero matrices for other channels.\n",
"red_channel=cv2.merge([zeros,zeros,r]) # Create the red channel by combining the red channel and zero matrices for other channels."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3c896f79-ec7d-4bcf-8db6-2e09d1551b6b",
"metadata": {},
"outputs": [],
"source": [
"cv2.imshow(\"blue_channel\",blue_channel) # Display the blue channel image in a window.\n",
"cv2.imshow(\"green_channel\",green_channel) # Display the green channel image in a window.\n",
"cv2.imshow(\"red_channel\",red_channel) # Display the red channel image in a window.\n",
"cv2.imshow(\"original_channel\",cv2.merge([b,g,r])) # Display the original image by merging the blue, green, and red channels back together.\n",
"\n",
"cv2.waitKey() # Wait indefinitely until a key is pressed.\n",
"cv2.destroyAllWindows() # Close all OpenCV windows."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "12381df8-94f1-4523-bbd3-d6d26052c5da",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
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},
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