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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,174 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 16, | ||
| "id": "83bb7943", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import cv2\n", | ||
| "import numpy as np\n", | ||
| "\n", | ||
| "def selective_blur(image_path, outputPath, blur_strength=10, focus_area_fraction=1):\n", | ||
| " # Load the image\n", | ||
| " image = cv2.imread(image_path)\n", | ||
| " \n", | ||
| " if image is None:\n", | ||
| " print(\"Error loading image\")\n", | ||
| " return\n", | ||
| " \n", | ||
| " # Ensure blur_strength is an odd number\n", | ||
| " if blur_strength % 2 == 0:\n", | ||
| " blur_strength += 1\n", | ||
| "\n", | ||
| " # Dimensions of the image\n", | ||
| " height, width = image.shape[:2]\n", | ||
| " \n", | ||
| " # Calculate the size of the central area to keep in focus\n", | ||
| " central_width = int(width * focus_area_fraction)\n", | ||
| " central_height = int(height * focus_area_fraction)\n", | ||
| " \n", | ||
| " # Calculate the starting point of the central region\n", | ||
| " start_x = (width - central_width) // 2\n", | ||
| " start_y = (height - central_height) // 2\n", | ||
| " \n", | ||
| " # Region of Interest (ROI) in the center of the image\n", | ||
| " center_region = image[start_y:start_y+central_height, start_x:start_x+central_width]\n", | ||
| " \n", | ||
| " # Apply Gaussian Blur to the center region\n", | ||
| " blurred_center = cv2.GaussianBlur(center_region, (blur_strength, blur_strength), 0)\n", | ||
| " \n", | ||
| " # Replace the center region of the original image with blurred version\n", | ||
| " image[start_y:start_y+central_height, start_x:start_x+central_width] = blurred_center\n", | ||
| " # Display the original and modified images\n", | ||
| " #cv2.imshow(\"Blurred Center Image\", image)\n", | ||
| " #cv2.waitKey(0)\n", | ||
| " #cv2.destroyAllWindows()\n", | ||
| " \n", | ||
| " # Save the result if desired\n", | ||
| " cv2.imwrite(outputPath, image)\n", | ||
| "\n", | ||
| "# Usage\n", | ||
| "inputPath = \"/Users/rai/Documents/GitHub/html5up-dimension/images/bg_original.jpg\"\n", | ||
| "outputPath = \"/Users/rai/Documents/GitHub/html5up-dimension/images/bg.jpg\"\n", | ||
| "image = selective_blur(inputPath, outputPath)\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 1, | ||
| "id": "470ebab4", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import cv2\n", | ||
| "import numpy as np\n", | ||
| "\n", | ||
| "def radial_gradient_blur(image_path, outputPath):\n", | ||
| " # Load the image\n", | ||
| " image = cv2.imread(image_path)\n", | ||
| " \n", | ||
| " if image is None:\n", | ||
| " print(\"Error loading image\")\n", | ||
| " return\n", | ||
| "\n", | ||
| " # Dimensions of the image\n", | ||
| " height, width = image.shape[:2]\n", | ||
| " center_x, center_y = width // 2, height // 2\n", | ||
| "\n", | ||
| " # Create an empty output image\n", | ||
| " blurred_image = np.zeros_like(image)\n", | ||
| "\n", | ||
| " # Maximum blur radius\n", | ||
| " max_radius = int(np.sqrt(center_x**2 + center_y**2))\n", | ||
| "\n", | ||
| " # Create radial blur effect\n", | ||
| " for y in range(height):\n", | ||
| " for x in range(width):\n", | ||
| " # Calculate distance to the center\n", | ||
| " distance = int(np.sqrt((center_x - x)**2 + (center_y - y)**2))\n", | ||
| " blur_amount = int(20 * (distance / max_radius)) # Change '20' to adjust max blur strength\n", | ||
| "\n", | ||
| " # Ensure blur_amount is odd and at least 1\n", | ||
| " blur_amount = max(1, blur_amount)\n", | ||
| " if blur_amount % 2 == 0:\n", | ||
| " blur_amount += 1\n", | ||
| "\n", | ||
| " # Blur the pixel based on distance to the center\n", | ||
| " region = image[max(0, y - blur_amount // 2):min(height, y + blur_amount // 2 + 1),\n", | ||
| " max(0, x - blur_amount // 2):min(width, x + blur_amount // 2 + 1)]\n", | ||
| " blurred_pixel = cv2.GaussianBlur(region, (blur_amount, blur_amount), 0)\n", | ||
| " blurred_image[y, x] = blurred_pixel[blur_amount // 2, blur_amount // 2]\n", | ||
| "\n", | ||
| " # Display the original and modified images\n", | ||
| " cv2.imshow(\"Original Image\", image)\n", | ||
| " #cv2.imshow(\"Radially Blurred Image\", blurred_image)\n", | ||
| " #cv2.waitKey(0)\n", | ||
| " #cv2.destroyAllWindows()\n", | ||
| "\n", | ||
| " # Save the result if desired\n", | ||
| " cv2.imwrite(outputPath, image)\n", | ||
| "\n", | ||
| "# Usage\n", | ||
| "inputPath = \"/Users/rai/Documents/GitHub/html5up-dimension/images/bg_original.jpg\"\n", | ||
| "outputPath = \"/Users/rai/Documents/GitHub/html5up-dimension/images/bg.jpg\"\n", | ||
| "image = radial_gradient_blur(inputPath,outputPath)\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 4, | ||
| "id": "6df86bb8", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from PIL import Image\n", | ||
| "\n", | ||
| "inputPath = \"/Users/rai/Documents/GitHub/rs3966.github.io/images/theLabPoster.jpg\"\n", | ||
| "outputPath = \"/Users/rai/Documents/GitHub/rs3966.github.io/images/theLabPoster_sized.jpg\"\n", | ||
| "fraction = 0.5\n", | ||
| "# Open an image file\n", | ||
| "with Image.open(inputPath) as img:\n", | ||
| " # Calculate the new size, 75% of the original size\n", | ||
| " new_width = int(img.width * fraction)\n", | ||
| " new_height = int(img.height * fraction)\n", | ||
| " \n", | ||
| " # Resize the image\n", | ||
| " resized_img = img.resize((new_width, new_height), Image.ANTIALIAS)\n", | ||
| " \n", | ||
| " # Save the resized image\n", | ||
| " resized_img.save(outputPath)\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "4fdcdb95", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3 (ipykernel)", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.9.12" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |
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