Traffic_Sign_Recognition_Model.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "gpuClass": "standard",
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y7q0s-gfTkbS",
        "outputId": "e8eaf56d-efbd-485b-bb0a-8cfdf1c21937"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/gdrive\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import tensorflow as tf\n",
        "from PIL import Image\n",
        "import os\n",
        "\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "from keras.utils import to_categorical\n",
        "\n",
        "from keras.models import Sequential\n",
        "\n",
        "from keras.layers import Conv2D, MaxPool2D, Dense, Flatten, Dropout\n",
        "\n",
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')\n",
        "\n",
        "data = []\n",
        "labels = []\n",
        "classes = 43\n",
        "cur_path = '/content/gdrive/MyDrive/ML Mini Project/TrafficDataset'\n",
        "for i in range(classes):\n",
        "  path = os.path.join(cur_path,'Train', str(i))\n",
        "  images = os.listdir(path)\n",
        "  for a in images:\n",
        "     try:\n",
        "       image = Image.open(path + '/'+ a)\n",
        "       image = image.resize((30,30))\n",
        "       image = np.array(image)\n",
        "       data.append(image)\n",
        "       labels.append(i)\n",
        "     except:\n",
        "       print(\"Error loading image\")\n",
        "data = np.array(data)\n",
        "labels = np.array(labels)\n",
        "# print(labels)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# create a figure and axes object\n",
        "fig, axs = plt.subplots(1, 6, figsize=(10, 5))\n",
        "\n",
        "# display each image in a different subplot\n",
        "for i in range(6):\n",
        "  axs[i].imshow(data[i])\n",
        "\n",
        "\n",
        "# remove the axis ticks and labels\n",
        "for ax in axs:\n",
        "    ax.set_xticks([])\n",
        "    ax.set_yticks([])\n",
        "    ax.set_xlabel('')\n",
        "    ax.set_ylabel('')\n",
        "\n",
        "# display the plot\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 147
        },
        "id": "TyEFXMJRGqpT",
        "outputId": "875fe5cd-ec8d-4106-9ea1-4345f4bb7edc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 6 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(data.shape, labels.shape)\n",
        "#Splitting training and testing dataset\n",
        "X_train, X_test, y_train, y_test = train_test_split(data, labels, test_size=0.2, random_state=42)\n",
        "print(X_train.shape, X_test.shape, y_train.shape, y_test.shape)\n",
        "#Converting the labels into one hot encoding\n",
        "y_train = to_categorical(y_train, 43)\n",
        "y_test = to_categorical(y_test, 43)\n",
        "print(X_train.shape[1:])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3aGywHVMHHmh",
        "outputId": "df2ce269-d3e2-491e-eb22-b3d8b6e49904"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(39208, 30, 30, 3) (39208,)\n",
            "(31366, 30, 30, 3) (7842, 30, 30, 3) (31366,) (7842,)\n",
            "(30, 30, 3)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Building the model\n",
        "model = Sequential()\n",
        "model.add(Conv2D(filters=32, kernel_size=(5,5), activation='relu', input_shape=X_train.shape[1:]))\n",
        "model.add(Conv2D(filters=32, kernel_size=(5,5), activation='relu'))\n",
        "model.add(MaxPool2D(pool_size=(2, 2)))\n",
        "model.add(Dropout(rate=0.25))\n",
        "model.add(Conv2D(filters=64, kernel_size=(3, 3), activation='relu'))\n",
        "model.add(Conv2D(filters=64, kernel_size=(3, 3), activation='relu'))\n",
        "model.add(MaxPool2D(pool_size=(2, 2)))\n",
        "model.add(Dropout(rate=0.25))\n",
        "model.add(Flatten())\n",
        "model.add(Dense(256, activation='relu'))\n",
        "model.add(Dropout(rate=0.5))\n",
        "model.add(Dense(43, activation='softmax'))\n",
        "#Compilation of the model\n",
        "model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])"
      ],
      "metadata": {
        "id": "b1ofAeW-HctR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P06Od5TCMxe9",
        "outputId": "68438928-7ce2-46f8-fc3a-735d48460657"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d (Conv2D)             (None, 26, 26, 32)        2432      \n",
            "                                                                 \n",
            " conv2d_1 (Conv2D)           (None, 22, 22, 32)        25632     \n",
            "                                                                 \n",
            " max_pooling2d (MaxPooling2D  (None, 11, 11, 32)       0         \n",
            " )                                                               \n",
            "                                                                 \n",
            " dropout (Dropout)           (None, 11, 11, 32)        0         \n",
            "                                                                 \n",
            " conv2d_2 (Conv2D)           (None, 9, 9, 64)          18496     \n",
            "                                                                 \n",
            " conv2d_3 (Conv2D)           (None, 7, 7, 64)          36928     \n",
            "                                                                 \n",
            " max_pooling2d_1 (MaxPooling  (None, 3, 3, 64)         0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " dropout_1 (Dropout)         (None, 3, 3, 64)          0         \n",
            "                                                                 \n",
            " flatten (Flatten)           (None, 576)               0         \n",
            "                                                                 \n",
            " dense (Dense)               (None, 256)               147712    \n",
            "                                                                 \n",
            " dropout_2 (Dropout)         (None, 256)               0         \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 43)                11051     \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 242,251\n",
            "Trainable params: 242,251\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# !pip install visualkeras\n",
        "# !pip install ann_visualizer\n",
        "# !pip install graphviz"
      ],
      "metadata": {
        "id": "Ai8UYtUEZkvU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# from ann_visualizer.visualize import ann_viz\n",
        "# ann_viz(model, view=True, filename='VisualisationOfTrafficSignsCNN', title='CNN for Traffic Sign Recognition')"
      ],
      "metadata": {
        "id": "_fhRHRlealMW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "eps = 15\n",
        "history = model.fit(X_train, y_train, batch_size=32, epochs=eps, validation_data=(X_test, y_test))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YAFkapIcI9Nv",
        "outputId": "09495457-4445-4f4c-c621-26233d030ffd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/15\n",
            "981/981 [==============================] - 27s 10ms/step - loss: 1.8359 - accuracy: 0.5212 - val_loss: 0.6750 - val_accuracy: 0.8426\n",
            "Epoch 2/15\n",
            "981/981 [==============================] - 9s 9ms/step - loss: 0.5910 - accuracy: 0.8283 - val_loss: 0.1966 - val_accuracy: 0.9447\n",
            "Epoch 3/15\n",
            "981/981 [==============================] - 11s 11ms/step - loss: 0.3664 - accuracy: 0.8950 - val_loss: 0.1104 - val_accuracy: 0.9668\n",
            "Epoch 4/15\n",
            "981/981 [==============================] - 8s 9ms/step - loss: 0.3219 - accuracy: 0.9094 - val_loss: 0.1013 - val_accuracy: 0.9736\n",
            "Epoch 5/15\n",
            "981/981 [==============================] - 11s 11ms/step - loss: 0.2643 - accuracy: 0.9265 - val_loss: 0.0728 - val_accuracy: 0.9818\n",
            "Epoch 6/15\n",
            "981/981 [==============================] - 9s 9ms/step - loss: 0.2581 - accuracy: 0.9302 - val_loss: 0.0698 - val_accuracy: 0.9816\n",
            "Epoch 7/15\n",
            "981/981 [==============================] - 9s 9ms/step - loss: 0.2285 - accuracy: 0.9403 - val_loss: 0.0520 - val_accuracy: 0.9848\n",
            "Epoch 8/15\n",
            "981/981 [==============================] - 10s 10ms/step - loss: 0.2476 - accuracy: 0.9337 - val_loss: 0.1355 - val_accuracy: 0.9607\n",
            "Epoch 9/15\n",
            "981/981 [==============================] - 8s 8ms/step - loss: 0.2256 - accuracy: 0.9412 - val_loss: 0.0477 - val_accuracy: 0.9866\n",
            "Epoch 10/15\n",
            "981/981 [==============================] - 10s 10ms/step - loss: 0.2468 - accuracy: 0.9372 - val_loss: 0.0741 - val_accuracy: 0.9799\n",
            "Epoch 11/15\n",
            "981/981 [==============================] - 10s 10ms/step - loss: 0.2443 - accuracy: 0.9383 - val_loss: 0.0758 - val_accuracy: 0.9793\n",
            "Epoch 12/15\n",
            "981/981 [==============================] - 8s 8ms/step - loss: 0.2339 - accuracy: 0.9407 - val_loss: 0.0512 - val_accuracy: 0.9862\n",
            "Epoch 13/15\n",
            "981/981 [==============================] - 9s 9ms/step - loss: 0.2312 - accuracy: 0.9433 - val_loss: 0.0512 - val_accuracy: 0.9848\n",
            "Epoch 14/15\n",
            "981/981 [==============================] - 9s 9ms/step - loss: 0.2313 - accuracy: 0.9434 - val_loss: 0.0652 - val_accuracy: 0.9813\n",
            "Epoch 15/15\n",
            "981/981 [==============================] - 9s 9ms/step - loss: 0.2148 - accuracy: 0.9461 - val_loss: 0.0619 - val_accuracy: 0.9839\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.metrics_names"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "X0OlbRoyNPyI",
        "outputId": "99f9a3f9-1c88-47d8-a5d7-c518df738967"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['loss', 'accuracy']"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.evaluate(X_test,y_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zagyr-pPNS2G",
        "outputId": "b4d9644f-8b8a-4ace-a776-c497c7fae71a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "246/246 [==============================] - 1s 5ms/step - loss: 0.0619 - accuracy: 0.9839\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.061930764466524124, 0.9839326739311218]"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#plotting graphs for accuracy\n",
        "plt.plot(history.history['accuracy'])\n",
        "plt.plot(history.history['val_accuracy'])\n",
        "plt.title('Model Accuracy')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.xlabel('Epoch')\n",
        "plt.legend(['Train', 'Validation'], loc='upper left')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "nLqTRQ7UM5hZ",
        "outputId": "e2709e1e-2ac8-4412-9f3e-4b52b4282377"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#plotting graphs for loss\n",
        "plt.plot(history.history['loss'])\n",
        "plt.plot(history.history['val_loss'])\n",
        "plt.title('Model Loss')\n",
        "plt.ylabel('Loss')\n",
        "plt.xlabel('Epoch')\n",
        "plt.legend(['Train', 'Validation'], loc='upper left')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "yL1TQEg2lkUy",
        "outputId": "242b6dad-158e-4b9a-995d-a1fc4f23e69a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.save('traffic_classifier.h5')"
      ],
      "metadata": {
        "id": "RhyR6ftkM6ID"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "from sklearn.metrics import confusion_matrix\n",
        "\n",
        "# Get the predicted classes from the model\n",
        "y_pred = model.predict(X_test)\n",
        "y_pred_classes = np.argmax(y_pred, axis=1)\n",
        "\n",
        "# Get the true classes for the test set\n",
        "y_true = np.argmax(y_test, axis=1)\n",
        "\n",
        "accuracy = np.sum(y_pred_classes == y_true) / len(y_true)\n",
        "loss = np.sum(y_pred_classes != y_true) / len(y_true)\n",
        "print(\"Accuracy = \",accuracy ,\" Loss = \", loss)\n",
        "\n",
        "# Generate the confusion matrix\n",
        "confusion_mtx = confusion_matrix(y_true, y_pred_classes)\n",
        "\n",
        "# Plot the confusion matrix\n",
        "fig, ax = plt.subplots(1,1,figsize=(10,8))\n",
        "sns.heatmap(confusion_mtx, annot=True, fmt='d', cmap=plt.cm.Blues, cbar=False,ax=ax)\n",
        "# ax.set_xtick()\n",
        "ax.xlabel('Predicted Label')\n",
        "ax.ylabel('True Label')\n",
        "ax.show()\n"
      ],
      "metadata": {
        "id": "wq4OEW0nNaXt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 928
        },
        "outputId": "34dc2566-38da-43aa-e6c6-7b370fa159eb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "246/246 [==============================] - 1s 2ms/step\n",
            "Accuracy =  0.958173935220607  Loss =  0.04182606477939301\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "AttributeError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-12-82e70018ccbb>\u001b[0m in \u001b[0;36m<cell line: 21>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     19\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     20\u001b[0m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mheatmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfusion_mtx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mannot\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfmt\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'd'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcmap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBlues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcbar\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 21\u001b[0;31m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_xtick\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     22\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Predicted Label'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     23\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'True Label'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: 'Axes' object has no attribute 'set_xtick'"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "TLO_RuOC8toH"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}