|
| 1 | +{ |
| 2 | + "cells": [ |
| 3 | + { |
| 4 | + "cell_type": "code", |
| 5 | + "execution_count": 1, |
| 6 | + "metadata": {}, |
| 7 | + "outputs": [], |
| 8 | + "source": [ |
| 9 | + "import numpy\n", |
| 10 | + "import cv2\n", |
| 11 | + "import matplotlib.pyplot as plt" |
| 12 | + ] |
| 13 | + }, |
| 14 | + { |
| 15 | + "cell_type": "code", |
| 16 | + "execution_count": 2, |
| 17 | + "metadata": {}, |
| 18 | + "outputs": [ |
| 19 | + { |
| 20 | + "data": { |
| 21 | + "image/png": 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\n", |
| 22 | + "text/plain": [ |
| 23 | + "<Figure size 432x288 with 1 Axes>" |
| 24 | + ] |
| 25 | + }, |
| 26 | + "metadata": { |
| 27 | + "needs_background": "light" |
| 28 | + }, |
| 29 | + "output_type": "display_data" |
| 30 | + } |
| 31 | + ], |
| 32 | + "source": [ |
| 33 | + "image_path = '/Users/vijendra1125/Desktop/mask_speaker_cup/dataset/Annotations/image1.png'\n", |
| 34 | + "image = cv2.imread(image_path)\n", |
| 35 | + "plt.imshow(image)\n", |
| 36 | + "plt.show()" |
| 37 | + ] |
| 38 | + }, |
| 39 | + { |
| 40 | + "cell_type": "code", |
| 41 | + "execution_count": 3, |
| 42 | + "metadata": {}, |
| 43 | + "outputs": [ |
| 44 | + { |
| 45 | + "name": "stdout", |
| 46 | + "output_type": "stream", |
| 47 | + "text": [ |
| 48 | + "PIXEL VALUES:\n", |
| 49 | + "speaker 76 \n", |
| 50 | + "cup 26\n" |
| 51 | + ] |
| 52 | + } |
| 53 | + ], |
| 54 | + "source": [ |
| 55 | + "image_gray = cv2.imread(image_path,0)\n", |
| 56 | + "print \"PIXEL VALUES:\\n\", \"speaker\", image_gray[100, 150], \"\\ncup\", image_gray[150, 350]" |
| 57 | + ] |
| 58 | + }, |
| 59 | + { |
| 60 | + "cell_type": "code", |
| 61 | + "execution_count": null, |
| 62 | + "metadata": {}, |
| 63 | + "outputs": [], |
| 64 | + "source": [] |
| 65 | + } |
| 66 | + ], |
| 67 | + "metadata": { |
| 68 | + "kernelspec": { |
| 69 | + "display_name": "Python 2", |
| 70 | + "language": "python", |
| 71 | + "name": "python2" |
| 72 | + }, |
| 73 | + "language_info": { |
| 74 | + "codemirror_mode": { |
| 75 | + "name": "ipython", |
| 76 | + "version": 2 |
| 77 | + }, |
| 78 | + "file_extension": ".py", |
| 79 | + "mimetype": "text/x-python", |
| 80 | + "name": "python", |
| 81 | + "nbconvert_exporter": "python", |
| 82 | + "pygments_lexer": "ipython2", |
| 83 | + "version": "2.7.15" |
| 84 | + } |
| 85 | + }, |
| 86 | + "nbformat": 4, |
| 87 | + "nbformat_minor": 2 |
| 88 | +} |
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