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Jupyter_Notes/images_page_2.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "993a08d6-a5eb-4a28-8225-d50103d116a5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: opencv-python in c:\\users\\laksh\\anaconda3\\lib\\site-packages (4.10.0.84)\n",
+      "Requirement already satisfied: numpy>=1.21.2 in c:\\users\\laksh\\anaconda3\\lib\\site-packages (from opencv-python) (1.26.4)\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install opencv-python"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "3938dd1a-aa2e-41c4-849f-d7a9c063650b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "4.10.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "import cv2\n",
+    "print(cv2.__version__)  # This will display the installed OpenCV version"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b3f9476e-c1e5-4a28-9850-bba69c81575e",
+   "metadata": {},
+   "source": [
+    "### Reading and Converting Image to array using imread()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "eb59dd6a-4b16-4160-8a97-4cddd762e615",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "img = cv2.imread(r\"C:\\Users\\laksh\\Downloads\\mickey_mouse.jpeg\")  # by default it will give 3d-array"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "682f8850-d44d-4540-9708-ad6fae826323",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[[221, 210, 206],\n",
+       "        [255, 255, 251],\n",
+       "        [253, 255, 254],\n",
+       "        ...,\n",
+       "        [252, 255, 251],\n",
+       "        [255, 255, 249],\n",
+       "        [219, 209, 215]],\n",
+       "\n",
+       "       [[219, 212, 209],\n",
+       "        [254, 252, 251],\n",
+       "        [247, 255, 255],\n",
+       "        ...,\n",
+       "        [251, 255, 255],\n",
+       "        [255, 253, 248],\n",
+       "        [215, 208, 211]],\n",
+       "\n",
+       "       [[211, 213, 213],\n",
+       "        [245, 252, 255],\n",
+       "        [239, 254, 255],\n",
+       "        ...,\n",
+       "        [244, 255, 255],\n",
+       "        [252, 255, 253],\n",
+       "        [213, 208, 210]],\n",
+       "\n",
+       "       ...,\n",
+       "\n",
+       "       [[207, 211, 200],\n",
+       "        [252, 255, 250],\n",
+       "        [248, 255, 255],\n",
+       "        ...,\n",
+       "        [245, 254, 255],\n",
+       "        [247, 254, 251],\n",
+       "        [212, 214, 214]],\n",
+       "\n",
+       "       [[219, 220, 216],\n",
+       "        [243, 246, 244],\n",
+       "        [248, 254, 253],\n",
+       "        ...,\n",
+       "        [251, 255, 255],\n",
+       "        [245, 249, 244],\n",
+       "        [214, 216, 216]],\n",
+       "\n",
+       "       [[238, 239, 237],\n",
+       "        [232, 235, 233],\n",
+       "        [224, 228, 229],\n",
+       "        ...,\n",
+       "        [227, 228, 226],\n",
+       "        [233, 234, 230],\n",
+       "        [244, 246, 246]]], dtype=uint8)"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "img"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "0b5d38d6-0535-4d07-8c3b-af89b7ebbb93",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(732, 551, 3)"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "img.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "9dbec1f6-7141-4900-80dc-16ca8e13c0c4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dtype('uint8')"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "img.dtype"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "9da3dac3-40b7-4287-83ad-0d0d77fa962d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "img1 = cv2.imread(r\"P:\\IMG_5723.JPG\",flags = 0)   # using flags = 0 we can convert it into 2d-array"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "d4fc6f2f-c8e1-4240-ab4e-eaf1bdfb8ae7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(4032, 3024)"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "img1.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "8e006b49-1fd7-4494-a074-53dfef43e933",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[183, 183, 182, ..., 186, 186, 186],\n",
+       "       [182, 182, 182, ..., 186, 186, 186],\n",
+       "       [181, 181, 181, ..., 185, 185, 185],\n",
+       "       ...,\n",
+       "       [ 54,  57,  59, ..., 104,  96,  92],\n",
+       "       [ 56,  60,  63, ..., 109, 104,  99],\n",
+       "       [ 53,  58,  64, ..., 114, 109, 102]], dtype=uint8)"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "img1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "d2b36743-dea0-4243-bae5-52a012a43c1b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "### Displaying the Images"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "2533d99d-4ada-402c-b2f9-b0301ac01ae2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cv2.imshow(\"White\",img)\n",
+    "\n",
+    "cv2.waitKey(0)   # 0 and no values means infinite delay to close X button\n",
+    "\n",
+    "cv2.destroyAllWindows()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "69f195df-1baa-4848-a63d-be90dd0ee676",
+   "metadata": {},
+   "source": [
+    "### Saving an Image"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "dac06ce8-ef18-42e5-8e87-d6a948d3387a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cv2.imwrite(r\"H:\\innomatics\\ML\\ML Class\\white_Img.jpg\",img)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "29690e46-6202-4ff5-8e53-7993c5bb61e6",
+   "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": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

Jupyter_Notes/images_page_3.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "8ded0138-8e45-4a67-a25c-c47eeda71e97",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "42d75506-dffc-48f5-9824-6fb53daddb27",
+   "metadata": {},
+   "source": [
+    "### creating black and white Images in 2d array --- Gray scale color space"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "3bb9760b-8001-48fa-ad8a-2273ded579c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "white_img = np.full((500,500),255,dtype = np.uint8)\n",
+    "black_img = np.zeros((500,500),dtype = np.uint8)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "9407730f-d563-412b-bcd3-8d8e85d465b9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cv2.imshow(\"White\",white_img)\n",
+    "cv2.imshow(\"Black\",black_img)\n",
+    "\n",
+    "cv2.waitKey(0)   # 0 and no values means infinite delay to close X button\n",
+    "\n",
+    "cv2.destroyAllWindows()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f1ff81c9-23f9-4c73-9b91-7d07fa6dc5cf",
+   "metadata": {},
+   "source": [
+    "### creating Gray-scale Images in 2d array --- Gray scale color space"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "6a94f960-8c92-4a3e-85d5-9cfaff6027a9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gray1_img = np.full((500,500),55,dtype = np.uint8)\n",
+    "gray2_img = np.full((500,500),155,dtype = np.uint8)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "bdb0452a-d756-4dc6-bec9-91d5573fcee6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cv2.imshow(\"gray1\",gray1_img)\n",
+    "cv2.imshow(\"gray2\",gray2_img)\n",
+    "\n",
+    "cv2.waitKey(0)\n",
+    "\n",
+    "cv2.destroyAllWindows()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7b37b480-6a61-4a82-8f55-11e3c634c346",
+   "metadata": {},
+   "source": [
+    "### Creating rgb Image by creating three channels and merging those channels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "db62b81b-45b6-493c-bd9d-8873ee3c0c9f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# creating images\n",
+    "\n",
+    "b = np.full((300,300),255,dtype = np.uint8)\n",
+    "g = np.zeros((300,300),dtype = np.uint8)\n",
+    "r = np.zeros((300,300),dtype = np.uint8)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "016a110a-237e-4448-af59-72506e0638d4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Merging all images to get rgb image\n",
+    "\n",
+    "b_img = cv2.merge([b,g,r])\n",
+    "g_img = cv2.merge([g,b,r])\n",
+    "r_img = cv2.merge([r,g,b])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "226d1940-e94e-4d9c-9673-c4b0bfa650b7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Dispalying the Image\n",
+    "\n",
+    "cv2.imshow(\"Blue\",b_img)\n",
+    "cv2.imshow(\"Green\",g_img)\n",
+    "cv2.imshow(\"Red\",r_img)\n",
+    "\n",
+    "cv2.waitKey(0)\n",
+    "\n",
+    "cv2.destroyAllWindows()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3e0cd1b1-8061-42ab-a9b1-8cfed67b4c14",
+   "metadata": {},
+   "source": [
+    "### Splitting an RGB Image into red,blue and green channels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "624fca87-a42b-4bc8-b7cc-fae9ca7d9809",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "img = cv2.imread(r\"C:\\Users\\laksh\\Downloads\\mickey_mouse.jpeg\")   # reading Image"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "be66eb3c-9281-4049-89f9-d25734660e22",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "b,g,r = cv2.split(img)   # splitting into three channels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "3f7a1355-499e-41c5-bb1b-6df0302144b1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "zeros = np.zeros(img.shape[:-1],dtype = np.uint8)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "423544d7-6e79-4e2f-a06b-d126e6bcde17",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "blue_channel = cv2.merge([b,zeros,zeros])\n",
+    "green_channel = cv2.merge([zeros,g,zeros])\n",
+    "red_channel = cv2.merge([zeros,zeros,r])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "d5582183-6691-46da-9b29-2654da2f796b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cv2.imshow(\"Blue_channel\",blue_channel)\n",
+    "cv2.imshow(\"Green_channel\",green_channel)\n",
+    "cv2.imshow(\"Red_channel\",red_channel)\n",
+    "cv2.imshow(\"Original_img\", cv2.merge([b,g,r]))\n",
+    "\n",
+    "cv2.waitKey(0)\n",
+    "\n",
+    "cv2.destroyAllWindows()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ad020dc8-41f7-45c2-9097-1c32aff47579",
+   "metadata": {},
+   "source": [
+    "### Converting Image to color Spaces"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "044cf632-626f-4765-95a4-07eecad62096",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "img = cv2.imread(r\"C:\\Users\\laksh\\Downloads\\mickey_mouse.jpeg\")   # reading Image"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "4645b06d-6e6f-4790-8e2b-f615a8c007c0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[210, 254, 254, ..., 253, 253, 212],\n",
+       "       [212, 252, 254, ..., 255, 252, 210],\n",
+       "       [213, 252, 253, ..., 254, 254, 209],\n",
+       "       ...,\n",
+       "       [207, 253, 254, ..., 253, 252, 214],\n",
+       "       [219, 245, 253, ..., 255, 247, 216],\n",
+       "       [238, 234, 228, ..., 227, 233, 246]], dtype=uint8)"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
+    "gray_img"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "54112f92-06fc-422a-bc54-b7dfe8119fe7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cv2.imshow(\"gray_scale_img\",gray_img)\n",
+    "\n",
+    "cv2.waitKey(0)\n",
+    "\n",
+    "cv2.destroyAllWindows()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d50754b0-32d2-4682-97ea-b34445cb3d60",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04752c4d-1cb0-48a7-b413-d681afeab2b5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "678cb559-e266-4018-a7bf-14fbc6b3d431",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "83b6071a-8b63-469f-89de-145678bec93d",
+   "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": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}