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| a | b/BleedingImageClassification.ipynb | ||
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| 1 | { |
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| 2 | "nbformat": 4, |
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| 3 | "nbformat_minor": 0, |
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| 4 | "metadata": { |
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| 5 | "colab": { |
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| 6 | "name": "BleedingImageClassification.ipynb", |
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| 7 | "provenance": [], |
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| 8 | "collapsed_sections": [] |
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| 9 | }, |
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| 10 | "kernelspec": { |
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| 11 | "name": "python3", |
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| 12 | "display_name": "Python 3" |
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| 13 | }, |
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| 14 | "language_info": { |
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| 15 | "name": "python" |
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| 16 | } |
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| 17 | }, |
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| 18 | "cells": [ |
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| 19 | { |
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| 20 | "cell_type": "code", |
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| 21 | "metadata": { |
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| 22 | "id": "tGZBwBkjWevk" |
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| 23 | }, |
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| 24 | "source": [ |
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| 25 | "!pip install tensorflow\n", |
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| 26 | "!pip install opencv-python\n", |
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| 27 | "!pip install numpy" |
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| 28 | ], |
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| 29 | "execution_count": null, |
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| 30 | "outputs": [] |
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| 31 | }, |
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| 32 | { |
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| 33 | "cell_type": "code", |
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| 34 | "metadata": { |
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| 35 | "id": "L7taERIgXXH6" |
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| 36 | }, |
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| 37 | "source": [ |
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| 38 | "import tensorflow.keras\n", |
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| 39 | "import numpy as np\n", |
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| 40 | "import cv2\n", |
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| 41 | "import os\n", |
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| 42 | "np.set_printoptions(suppress=True)" |
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| 43 | ], |
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| 44 | "execution_count": null, |
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| 45 | "outputs": [] |
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| 46 | }, |
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| 47 | { |
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| 48 | "cell_type": "code", |
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| 49 | "metadata": { |
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| 50 | "colab": { |
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| 51 | "base_uri": "https://localhost:8080/" |
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| 52 | }, |
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| 53 | "id": "87r5fH7FaDta", |
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| 54 | "outputId": "95ace021-e41f-4eeb-db35-ae25082e64fe" |
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| 55 | }, |
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| 56 | "source": [ |
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| 57 | "model = tensorflow.keras.models.load_model('keras_model.h5')" |
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| 58 | ], |
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| 59 | "execution_count": null, |
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| 60 | "outputs": [ |
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| 61 | { |
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| 62 | "output_type": "stream", |
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| 63 | "text": [ |
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| 64 | "WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.\n" |
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| 65 | ], |
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| 66 | "name": "stdout" |
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| 67 | } |
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| 68 | ] |
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| 69 | }, |
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| 70 | { |
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| 71 | "cell_type": "code", |
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| 72 | "metadata": { |
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| 73 | "id": "0wGpjGSBa0Ga" |
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| 74 | }, |
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| 75 | "source": [ |
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| 76 | "data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)" |
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| 77 | ], |
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| 78 | "execution_count": null, |
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| 79 | "outputs": [] |
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| 80 | }, |
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| 81 | { |
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| 82 | "cell_type": "code", |
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| 83 | "metadata": { |
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| 84 | "id": "YsDvM6oga0Rp" |
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| 85 | }, |
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| 86 | "source": [ |
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| 87 | "image = cv2.imread('/content/Capture.jpg')\n", |
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| 88 | "\n", |
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| 89 | "#resizing the image to be at least 224x224 and then cropping from the center\n", |
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| 90 | "size = (224, 224)\n", |
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| 91 | "\n", |
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| 92 | "image = cv2.resize(image, size, fx=0.5, fy=0.5, interpolation = cv2.INTER_AREA)\n", |
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| 93 | "#turn the image into a numpy array\n", |
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| 94 | "image_array = np.asarray(image)" |
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| 95 | ], |
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| 96 | "execution_count": null, |
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| 97 | "outputs": [] |
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| 98 | }, |
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| 99 | { |
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| 100 | "cell_type": "code", |
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| 101 | "metadata": { |
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| 102 | "id": "oP537pQFa9Sq" |
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| 103 | }, |
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| 104 | "source": [ |
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| 105 | "normalized_image_array = (image_array.astype(np.float32) / 127.0) - 1" |
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| 106 | ], |
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| 107 | "execution_count": null, |
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| 108 | "outputs": [] |
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| 109 | }, |
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| 110 | { |
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| 111 | "cell_type": "code", |
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| 112 | "metadata": { |
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| 113 | "id": "d6V-tVTha-dS" |
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| 114 | }, |
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| 115 | "source": [ |
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| 116 | "data[0] = normalized_image_array" |
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| 117 | ], |
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| 118 | "execution_count": null, |
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| 119 | "outputs": [] |
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| 120 | }, |
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| 121 | { |
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| 122 | "cell_type": "code", |
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| 123 | "metadata": { |
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| 124 | "colab": { |
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| 125 | "base_uri": "https://localhost:8080/" |
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| 126 | }, |
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| 127 | "id": "LWzMOv2pbBPC", |
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| 128 | "outputId": "7f04c9f2-6785-4158-e0cc-2f1856a9a6bb" |
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| 129 | }, |
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| 130 | "source": [ |
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| 131 | "prediction = model.predict(data)\n", |
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| 132 | "print(prediction)" |
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| 133 | ], |
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| 134 | "execution_count": null, |
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| 135 | "outputs": [ |
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| 136 | { |
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| 137 | "output_type": "stream", |
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| 138 | "text": [ |
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| 139 | "[[0.00362582 0.9963742 ]]\n" |
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| 140 | ], |
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| 141 | "name": "stdout" |
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| 142 | } |
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| 143 | ] |
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| 144 | }, |
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| 145 | { |
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| 146 | "cell_type": "code", |
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| 147 | "metadata": { |
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| 148 | "colab": { |
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| 149 | "base_uri": "https://localhost:8080/" |
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| 150 | }, |
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| 151 | "id": "tuV4H65bZtT6", |
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| 152 | "outputId": "73aafe0a-ffb6-48cb-f099-d34e6d8cca7a" |
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| 153 | }, |
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| 154 | "source": [ |
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| 155 | "if prediction[0][0] > 0.7 and prediction[0][0] > prediction[0][1]:\n", |
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| 156 | " print(\"Bleeding Brain\")\n", |
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| 157 | "else:\n", |
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| 158 | " print(\"Non Bleeding Brain\")" |
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| 159 | ], |
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| 160 | "execution_count": null, |
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| 161 | "outputs": [ |
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| 162 | { |
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| 163 | "output_type": "stream", |
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| 164 | "text": [ |
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| 165 | "Non Bleeding Brain\n" |
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| 166 | ], |
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| 167 | "name": "stdout" |
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| 168 | } |
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| 169 | ] |
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| 170 | }, |
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| 171 | { |
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| 172 | "cell_type": "code", |
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| 173 | "metadata": { |
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| 174 | "id": "b74k8FzlbL8h" |
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| 175 | }, |
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| 176 | "source": [ |
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| 177 | "" |
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| 178 | ], |
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| 179 | "execution_count": null, |
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| 180 | "outputs": [] |
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| 181 | } |
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| 182 | ] |
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| 183 | } |