Hand_Gesture_Classification.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "42r6fdhXd-Ms"
   },
   "source": [
    "# Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## A1. Reading the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Matrix:\t(27455, 784)\n",
      "Train Labels:\t(27455,)\n",
      "Test Matrix:\t(7172, 784)\n",
      "Test Labesl:\t(7172,)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import tensorflow.compat.v1 as tf\n",
    "tf.disable_v2_behavior()\n",
    "pass\n",
    "\n",
    "# Reading train file data\n",
    "Q1_train = pd.read_csv('Q1_train.csv')\n",
    "y = Q1_train.to_numpy()[:,0]\n",
    "x = Q1_train.to_numpy()[:,1:]\n",
    "\n",
    "# Reading test file data\n",
    "Q1_test  = pd.read_csv('Q1_test.csv')\n",
    "y_test   = Q1_test.to_numpy()[:,0]\n",
    "x_test   = Q1_test.to_numpy()[:,1:]\n",
    "\n",
    "print('Train Matrix:\\t{}'.format(x.shape))\n",
    "print('Train Labels:\\t{}'.format(y.shape))\n",
    "print('Test Matrix:\\t{}'.format(x_test.shape))\n",
    "print('Test Labesl:\\t{}'.format(y_test.shape))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A2. Plotting some samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 25 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "ref = dict()\n",
    "for i in range(25):\n",
    "    ref[i] = chr(i+65)\n",
    "\n",
    "fig, ax = plt.subplots(5,5,figsize=(15,15))\n",
    "\n",
    "for i in range(5):\n",
    "    for j in range(5):\n",
    "        ax[i,j].imshow(np.reshape(x[5*i+j],(28,28)),cmap='gray')\n",
    "        ax[i,j].set_title(ref[y[5*i+j]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training MLP"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## B. Spliting and one-hotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x_train:\t(21964, 784)\n",
      "y_train:\t(21964,)\n",
      "x_train:\t(5491, 784)\n",
      "y_valid:\t(5491,)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "# Splitting train-valid datasets\n",
    "ratio = 0.2\n",
    "x_train, x_valid, y_train, y_valid = train_test_split(x, y, test_size=ratio, shuffle=True, random_state=0)\n",
    "\n",
    "# Making one-hot labels\n",
    "n_classes = 25\n",
    "with tf.Session() as sess:\n",
    "    y_train_hot = sess.run(tf.one_hot(y_train, n_classes))\n",
    "    y_valid_hot = sess.run(tf.one_hot(y_valid, n_classes))\n",
    "    y_test_hot  = sess.run(tf.one_hot(y_test , n_classes))\n",
    "\n",
    "# normalization\n",
    "scaler  = StandardScaler()\n",
    "x_train = scaler.fit_transform(x_train)\n",
    "x_valid = scaler.transform(x_valid)\n",
    "x_test  = scaler.transform(x_test)\n",
    "\n",
    "print('x_train:\\t{}'.format(x_train.shape))\n",
    "print('y_train:\\t{}'.format(y_train.shape))\n",
    "print('x_train:\\t{}'.format(x_valid.shape))\n",
    "print('y_valid:\\t{}'.format(y_valid.shape))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## B. Examining class labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Samples for class A: 896\n",
      "Samples for class B: 810\n",
      "Samples for class C: 922\n",
      "Samples for class D: 935\n",
      "Samples for class E: 762\n",
      "Samples for class F: 966\n",
      "Samples for class G: 850\n",
      "Samples for class H: 803\n",
      "Samples for class I: 950\n",
      "Samples for class J: 0\n",
      "Samples for class K: 904\n",
      "Samples for class L: 1008\n",
      "Samples for class M: 839\n",
      "Samples for class N: 903\n",
      "Samples for class O: 961\n",
      "Samples for class P: 861\n",
      "Samples for class Q: 1050\n",
      "Samples for class R: 1008\n",
      "Samples for class S: 962\n",
      "Samples for class T: 956\n",
      "Samples for class U: 938\n",
      "Samples for class V: 849\n",
      "Samples for class W: 1001\n",
      "Samples for class X: 931\n",
      "Samples for class Y: 899\n"
     ]
    }
   ],
   "source": [
    "for i in range(np.max(y_train)+1):\n",
    "    print (f'Samples for class {ref[i]}: {len(np.where(y_train==i)[0])}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MLP"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## B. Handful Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorboard import program\n",
    "from sklearn.metrics import accuracy_score, confusion_matrix, classification_report\n",
    "import seaborn as sns\n",
    "\n",
    "def linear(x_in, w, b):\n",
    "    out = tf.matmul(x_in, w) + b\n",
    "    return out\n",
    "\n",
    "def run_tensorboard(log_dir):\n",
    "    from tensorboard import program\n",
    "    tb = program.TensorBoard()\n",
    "    tb.configure(argv=[None, '--logdir', log_dir])\n",
    "    url = tb.launch()\n",
    "    print(f\"Tensorboard active on {url}\")\n",
    "    return\n",
    "\n",
    "def show_test_results(net, x_test, y_test, cm=True):\n",
    "    y_pred = net.predict(x_test)\n",
    "    \n",
    "    print (f'correct predictions:\\t{np.sum(y_pred==y_test)} out of {len(y_test)}')\n",
    "    print (f'test data accuracy:\\t{accuracy_score(y_test, y_pred)}\\n')\n",
    "    \n",
    "    if cm == True:\n",
    "        cm = confusion_matrix(y_test, y_pred)\n",
    "        cm_norm = np.around(cm.astype('float') / cm.sum(axis=1)[:, np.newaxis], decimals=2)\n",
    "\n",
    "        if cm_norm.shape[0] == 24:\n",
    "            class_names = dict()\n",
    "            for k,v in ref.items():\n",
    "                if v != 'J' and v != 'Z':\n",
    "                    class_names[k] = v\n",
    "        else:\n",
    "            class_names = ref\n",
    "\n",
    "        con_mat_df = pd.DataFrame(cm_norm,index = class_names.values(), columns = class_names.values())\n",
    "        figure = plt.figure(figsize=(15, 15))\n",
    "        sns.heatmap(con_mat_df, annot=True,cmap=\"YlGnBu\")\n",
    "        plt.tight_layout()\n",
    "        plt.ylabel('True label')\n",
    "        plt.xlabel('Predicted label')\n",
    "        plt.title('Test data confusion matrix')\n",
    "        plt.show()\n",
    "    return y_pred"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## B. Class Definition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "code_folding": [],
    "tags": []
   },
   "outputs": [],
   "source": [
    "class MLP:\n",
    "    def __init__(self, layers, dropout=0, bn = False,\n",
    "                 activation = tf.nn.relu, optimizer=tf.train.AdamOptimizer,\n",
    "                 lr=0.001, w_std=0.01):\n",
    "        '''\n",
    "        - layers: the list of neurons in each layer e.g. [784, 256, 64, 10]\n",
    "            784: input dimension\n",
    "            256: first hidden layer\n",
    "            64 : second hidden layer\n",
    "            10 : number of classes\n",
    "        - dropout: dropout rate for hidden neurons; default is 0 meaning no dropout\n",
    "        - bn: boolean; determines whether we use batch normalization in hidden layers or not\n",
    "        - activation: activation function for inner layer as function name like tf.nn.relu\n",
    "        - optimizer: optimizer for training the network as function name like tf.train.GradientDescentOptimizer\n",
    "        - lr: learning rate of the optimizer\n",
    "        - w_std: standard deviation for weights initialization\n",
    "        '''\n",
    "        \n",
    "        self.inp = layers[0]\n",
    "        self.out = layers[-1]\n",
    "        \n",
    "        self.layers = layers\n",
    "        self.depth  = len(layers) # or L-1; not so much differnce\n",
    "        \n",
    "        self.weights = dict()\n",
    "        self.biases  = dict()\n",
    "        \n",
    "        self.drop_rate  = dropout # for forward pass\n",
    "        self.bn = bn\n",
    "        self.activation = activation\n",
    "        \n",
    "        with tf.variable_scope('I/O'):\n",
    "            self.x_in  = tf.placeholder (dtype=tf.float32, shape=(None,self.inp),name='input')\n",
    "            self.y_out = tf.placeholder (dtype=tf.float32, shape=(None,self.out),name='output')\n",
    "            \n",
    "        with tf.variable_scope('Dropout'):\n",
    "            self.dout = tf.placeholder (dtype=tf.float32, shape=(), name='dropout')\n",
    "        \n",
    "        with tf.variable_scope('bn'):\n",
    "            self.bnorm = tf.placeholder (dtype=tf.bool, shape=(), name = 'batch_normalization')\n",
    "        # ============================================= Here we define the hierarchy in the graph\n",
    "        self.graph = dict()\n",
    "        self.graph[0] = self.x_in\n",
    "        for i in range(1, self.depth):\n",
    "            \n",
    "            with tf.variable_scope(f'Layer-{i}-{i+1}'):\n",
    "                self.weights[i] = tf.get_variable (\n",
    "                    name = f'W_{i}',dtype = tf.float32,\n",
    "                    shape = (self.layers[i-1],self.layers[i]),\n",
    "                    initializer = tf.truncated_normal_initializer(stddev=w_std)\n",
    "                )\n",
    "                tf.summary.histogram(f'W_{i}', self.weights[i])\n",
    "\n",
    "                self.biases[i] = tf.get_variable (\n",
    "                    name=f'B_{i}', dtype=tf.float32,\n",
    "                    shape = (self.layers[i],), initializer = tf.zeros_initializer()\n",
    "                )\n",
    "                tf.summary.histogram(f'B_{i}', self.biases[i])\n",
    "                \n",
    "                if i < self.depth - 1:\n",
    "                    if self.bn == True:\n",
    "                        self.graph[i] = tf.layers.batch_normalization(\n",
    "                            self.activation(linear(self.graph[i-1],self.weights[i], self.biases[i]))\n",
    "                            ,training = self.bnorm\n",
    "                        )\n",
    "                    else:\n",
    "                        self.graph[i] = tf.nn.dropout(\n",
    "                                self.activation(linear(self.graph[i-1],self.weights[i], self.biases[i]))\n",
    "                                ,rate = self.dout\n",
    "                                )\n",
    "                    \n",
    "                    \n",
    "                else:\n",
    "                    self.graph[i] = linear(\n",
    "                        self.graph[i-1],\n",
    "                        self.weights[i],\n",
    "                        self.biases[i]\n",
    "                    )\n",
    "        \n",
    "        # ============================================== Defining handful variables for training\n",
    "        with tf.variable_scope('Train'):\n",
    "            \n",
    "            with tf.variable_scope('Loss'):\n",
    "                self.loss = tf.reduce_mean(\n",
    "                    tf.nn.softmax_cross_entropy_with_logits(labels=self.y_out,logits=self.graph[self.depth-1]),\n",
    "                    name = 'loss'\n",
    "                    )\n",
    "                tf.summary.scalar('loss', self.loss)\n",
    "                \n",
    "            with tf.variable_scope('Accuracy'):\n",
    "                self.corr = tf.equal(tf.argmax(self.graph[self.depth-1],1),tf.argmax(self.y_out,1),name='correct')\n",
    "                self.accuracy = tf.reduce_mean(tf.cast(self.corr, tf.float32), name='accuracy')\n",
    "                tf.summary.scalar('accuracy', self.accuracy)\n",
    "            \n",
    "            with tf.variable_scope('Optimizer'):\n",
    "                self.opt = optimizer(learning_rate=lr).minimize(self.loss)\n",
    "        \n",
    "        # ============================================== Starting session and initialization\n",
    "        self.sess = tf.InteractiveSession()\n",
    "        self.init = tf.global_variables_initializer()\n",
    "        self.sess.run(self.init)\n",
    "    \n",
    "    def predict(self, X_in):\n",
    "        pred = self.sess.run(\n",
    "            self.graph[self.depth-1],\n",
    "            feed_dict={self.x_in: X_in, self.dout: 0, self.bnorm: False}\n",
    "        )\n",
    "        return np.argmax(pred,axis=1)\n",
    "    \n",
    "    def train(self, x_train, y_train, x_test, y_test, eps, bs, log_dir='./summaries'):\n",
    "        merged = tf.summary.merge_all()\n",
    "        writer = tf.summary.FileWriter(log_dir, self.sess.graph)\n",
    "        \n",
    "        \n",
    "        history = {\n",
    "            'train_loss': list(),\n",
    "            'train_acc': list(),\n",
    "            'val_loss': list(),\n",
    "            'val_acc': list()\n",
    "        }\n",
    "        \n",
    "        step = 0\n",
    "        for ep in range(1,eps+1):\n",
    "            if ep % 5 == 0:\n",
    "                print (f'*** Epoch {ep} ***')\n",
    "            \n",
    "            # ============================================ Training Loop\n",
    "            for i in range(x_train.shape[0]//bs):\n",
    "                xb = x_train[i*bs: (i+1)*bs]\n",
    "                yb = y_train[i*bs: (i+1)*bs]\n",
    "                _ = self.sess.run (\n",
    "                    self.opt,\n",
    "                    feed_dict={self.x_in: xb, self.y_out: yb,\n",
    "                               self.dout: self.drop_rate, self.bnorm: self.bn}\n",
    "                )                \n",
    "            \n",
    "            # ================================================ Training data\n",
    "            step += 1\n",
    "            train_summary, loss_train, acc_train = self.sess.run(\n",
    "                [merged, self.loss, self.accuracy],\n",
    "                feed_dict={self.x_in: x_train, self.y_out: y_train,\n",
    "                           self.dout: 0, self.bnorm: False}\n",
    "            )\n",
    "            writer.add_summary(train_summary, step)\n",
    "            if ep % 5 == 0:\n",
    "                print(\"training loss: {1:.2f}\\ttraining accuracy: {2:.01%}\".\n",
    "                  format(ep, loss_train, acc_train))\n",
    "            history['train_loss'].append(loss_train)\n",
    "            history['train_acc'].append(acc_train)\n",
    "                \n",
    "            # ================================================ Validation\n",
    "            loss_valid, acc_valid = self.sess.run(\n",
    "                [self.loss,self.accuracy],\n",
    "                feed_dict={self.x_in: x_test, self.y_out: y_test,\n",
    "                           self.dout: 0, self.bnorm: False}\n",
    "            )\n",
    "            \n",
    "            if ep % 5 == 0:\n",
    "                print(\"validation loss: {1:.2f}\\tvalidation accuracy: {2:.01%}\\n\".\n",
    "                  format(ep, loss_valid, acc_valid))\n",
    "            history['val_loss'].append(loss_valid)\n",
    "            history['val_acc'].append(acc_valid)\n",
    "        \n",
    "        writer.close()\n",
    "        \n",
    "        return history"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### B. Adam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./summaries/20211118-230130\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Asus\\anaconda3\\lib\\site-packages\\tensorflow\\python\\client\\session.py:1771: UserWarning: An interactive session is already active. This can cause out-of-memory errors in some cases. You must explicitly call `InteractiveSession.close()` to release resources held by the other session(s).\n",
      "  warnings.warn('An interactive session is already active. This can '\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "*** Epoch 5 ***\n",
      "training loss: 0.18\ttraining accuracy: 97.9%\n",
      "validation loss: 0.20\tvalidation accuracy: 97.3%\n",
      "\n",
      "*** Epoch 10 ***\n",
      "training loss: 0.02\ttraining accuracy: 100.0%\n",
      "validation loss: 0.02\tvalidation accuracy: 100.0%\n",
      "\n",
      "*** Epoch 15 ***\n",
      "training loss: 0.01\ttraining accuracy: 100.0%\n",
      "validation loss: 0.01\tvalidation accuracy: 100.0%\n",
      "\n",
      "*** Epoch 20 ***\n",
      "training loss: 0.00\ttraining accuracy: 100.0%\n",
      "validation loss: 0.01\tvalidation accuracy: 100.0%\n",
      "\n",
      "correct predictions:\t5812 out of 7172\n",
      "test data accuracy:\t0.8103736754043502\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "log_dir1 = \"./summaries/\" + datetime.now().strftime(\"%Y%m%d-%H%M%S\")\n",
    "print (log_dir1)\n",
    "\n",
    "tf.reset_default_graph()\n",
    "net1 = MLP(\n",
    "    [784,256,25], \n",
    "    w_std=0.001, lr=0.001\n",
    "    ) # Adam is the default optimizer\n",
    "\n",
    "hist1 = net1.train(\n",
    "    x_train, y_train_hot, \n",
    "    x_valid, y_valid_hot,\n",
    "    eps=20, bs=1024,\n",
    "    log_dir = log_dir1\n",
    "    )\n",
    "\n",
    "# ============================== Test\n",
    "y_pred = show_test_results(net1, x_test, y_test)\n",
    "\n",
    "#run_tensorboard(log_dir1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### B. SGD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./summaries/20211118-230718\n",
      "*** Epoch 5 ***\n",
      "training loss: 1.12\ttraining accuracy: 67.2%\n",
      "validation loss: 1.16\tvalidation accuracy: 65.3%\n",
      "\n",
      "*** Epoch 10 ***\n",
      "training loss: 0.36\ttraining accuracy: 93.2%\n",
      "validation loss: 0.39\tvalidation accuracy: 92.3%\n",
      "\n",
      "*** Epoch 15 ***\n",
      "training loss: 0.13\ttraining accuracy: 99.3%\n",
      "validation loss: 0.15\tvalidation accuracy: 99.1%\n",
      "\n",
      "*** Epoch 20 ***\n",
      "training loss: 0.06\ttraining accuracy: 100.0%\n",
      "validation loss: 0.07\tvalidation accuracy: 99.9%\n",
      "\n",
      "*** Epoch 25 ***\n",
      "training loss: 0.04\ttraining accuracy: 100.0%\n",
      "validation loss: 0.04\tvalidation accuracy: 100.0%\n",
      "\n",
      "*** Epoch 30 ***\n",
      "training loss: 0.03\ttraining accuracy: 100.0%\n",
      "validation loss: 0.03\tvalidation accuracy: 100.0%\n",
      "\n",
      "correct predictions:\t5593 out of 7172\n",
      "test data accuracy:\t0.7798382598996096\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "log_dir2 = \"./summaries/\" + datetime.now().strftime(\"%Y%m%d-%H%M%S\")\n",
    "print (log_dir2)\n",
    "\n",
    "tf.reset_default_graph()\n",
    "net2 = MLP(\n",
    "    [784,256,25],\n",
    "    optimizer=tf.train.GradientDescentOptimizer,\n",
    "    lr=0.05, dropout=0, bn=False, w_std=0.001\n",
    ")\n",
    "\n",
    "hist2 = net2.train(\n",
    "    x_train, y_train_hot, \n",
    "    x_valid, y_valid_hot,\n",
    "    eps=30, bs=256,\n",
    "    log_dir = log_dir2\n",
    "    )\n",
    "\n",
    "# ============================== Test\n",
    "y_pred = show_test_results(net2, x_test, y_test)\n",
    "\n",
    "#run_tensorboard(log_dir2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## C. Tensorboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorboard active on http://localhost:6006/\n"
     ]
    }
   ],
   "source": [
    "run_tensorboard(log_dir1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## C. Reset Tensorboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!taskkill /IM \"tensorboard.exe\" /F\n",
    "!rmdir /S /Q %temp%\\.tensorboard-info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## D. Adam with Dropout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./summaries/20211118-233939\n",
      "*** Epoch 5 ***\n",
      "training loss: 0.30\ttraining accuracy: 94.5%\n",
      "validation loss: 0.32\tvalidation accuracy: 94.0%\n",
      "\n",
      "*** Epoch 10 ***\n",
      "training loss: 0.04\ttraining accuracy: 100.0%\n",
      "validation loss: 0.05\tvalidation accuracy: 100.0%\n",
      "\n",
      "*** Epoch 15 ***\n",
      "training loss: 0.01\ttraining accuracy: 100.0%\n",
      "validation loss: 0.01\tvalidation accuracy: 100.0%\n",
      "\n",
      "*** Epoch 20 ***\n",
      "training loss: 0.01\ttraining accuracy: 100.0%\n",
      "validation loss: 0.01\tvalidation accuracy: 100.0%\n",
      "\n",
      "correct predictions:\t5822 out of 7172\n",
      "test data accuracy:\t0.8117679866146124\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "log_dir3 = \"./summaries/\" + datetime.now().strftime(\"%Y%m%d-%H%M%S\")\n",
    "print (log_dir3)\n",
    "\n",
    "tf.reset_default_graph()\n",
    "net1 = MLP(\n",
    "    [784,256,25], \n",
    "    w_std=0.001, lr=0.001, dropout=0.5\n",
    "    ) # Adam is the default optimizer\n",
    "\n",
    "hist1 = net1.train(\n",
    "    x_train, y_train_hot, \n",
    "    x_valid, y_valid_hot,\n",
    "    eps=20, bs=1024,\n",
    "    log_dir = log_dir3\n",
    "    )\n",
    "\n",
    "# ============================== Test\n",
    "y_pred = show_test_results(net1, x_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## D. SGD with Dropout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./summaries/20211118-234452\n",
      "*** Epoch 5 ***\n",
      "training loss: 1.16\ttraining accuracy: 66.4%\n",
      "validation loss: 1.20\tvalidation accuracy: 64.9%\n",
      "\n",
      "*** Epoch 10 ***\n",
      "training loss: 0.43\ttraining accuracy: 91.6%\n",
      "validation loss: 0.46\tvalidation accuracy: 90.2%\n",
      "\n",
      "*** Epoch 15 ***\n",
      "training loss: 0.18\ttraining accuracy: 98.1%\n",
      "validation loss: 0.20\tvalidation accuracy: 97.5%\n",
      "\n",
      "*** Epoch 20 ***\n",
      "training loss: 0.09\ttraining accuracy: 99.8%\n",
      "validation loss: 0.10\tvalidation accuracy: 99.7%\n",
      "\n",
      "*** Epoch 25 ***\n",
      "training loss: 0.05\ttraining accuracy: 99.9%\n",
      "validation loss: 0.05\tvalidation accuracy: 99.9%\n",
      "\n",
      "*** Epoch 30 ***\n",
      "training loss: 0.03\ttraining accuracy: 100.0%\n",
      "validation loss: 0.03\tvalidation accuracy: 100.0%\n",
      "\n",
      "correct predictions:\t5680 out of 7172\n",
      "test data accuracy:\t0.7919687674288901\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "log_dir4 = \"./summaries/\" + datetime.now().strftime(\"%Y%m%d-%H%M%S\")\n",
    "print (log_dir4)\n",
    "\n",
    "tf.reset_default_graph()\n",
    "net2 = MLP(\n",
    "    [784,256,25],\n",
    "    optimizer=tf.train.GradientDescentOptimizer,\n",
    "    lr=0.05, dropout=0.5, bn=False, w_std=0.001\n",
    ")\n",
    "\n",
    "hist2 = net2.train(\n",
    "    x_train, y_train_hot, \n",
    "    x_valid, y_valid_hot,\n",
    "    eps=30, bs=256,\n",
    "    log_dir = log_dir4\n",
    "    )\n",
    "\n",
    "# ============================== Test\n",
    "y_pred = show_test_results(net2, x_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## E. Adam with Batch Normalization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### E. Hidden: {256}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./summaries/20211119-001407\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Asus\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:62: UserWarning: `tf.layers.batch_normalization` is deprecated and will be removed in a future version. Please use `tf.keras.layers.BatchNormalization` instead. In particular, `tf.control_dependencies(tf.GraphKeys.UPDATE_OPS)` should not be used (consult the `tf.keras.layers.BatchNormalization` documentation).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "*** Epoch 5 ***\n",
      "training loss: 1.57\ttraining accuracy: 99.0%\n",
      "validation loss: 1.58\tvalidation accuracy: 98.9%\n",
      "\n",
      "*** Epoch 10 ***\n",
      "training loss: 1.56\ttraining accuracy: 99.9%\n",
      "validation loss: 1.57\tvalidation accuracy: 99.9%\n",
      "\n",
      "*** Epoch 15 ***\n",
      "training loss: 1.56\ttraining accuracy: 100.0%\n",
      "validation loss: 1.57\tvalidation accuracy: 100.0%\n",
      "\n",
      "*** Epoch 20 ***\n",
      "training loss: 1.56\ttraining accuracy: 100.0%\n",
      "validation loss: 1.57\tvalidation accuracy: 100.0%\n",
      "\n",
      "correct predictions:\t4598 out of 7172\n",
      "test data accuracy:\t0.6411042944785276\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "log_dir5 = \"./summaries/\" + datetime.now().strftime(\"%Y%m%d-%H%M%S\")\n",
    "print (log_dir5)\n",
    "\n",
    "tf.reset_default_graph()\n",
    "net1 = MLP(\n",
    "    [784,256,25], \n",
    "    w_std=0.001, lr=0.001, dropout=0, bn=True\n",
    "    )\n",
    "\n",
    "hist1 = net1.train(\n",
    "    x_train, y_train_hot, \n",
    "    x_valid, y_valid_hot,\n",
    "    eps=20, bs=1024,\n",
    "    log_dir = log_dir5\n",
    "    )\n",
    "\n",
    "# ============================== Test\n",
    "y_pred = show_test_results(net1, x_test, y_test, cm=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### E. hidden {256,128}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./summaries/20211119-001430\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Asus\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:62: UserWarning: `tf.layers.batch_normalization` is deprecated and will be removed in a future version. Please use `tf.keras.layers.BatchNormalization` instead. In particular, `tf.control_dependencies(tf.GraphKeys.UPDATE_OPS)` should not be used (consult the `tf.keras.layers.BatchNormalization` documentation).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "*** Epoch 5 ***\n",
      "training loss: 0.56\ttraining accuracy: 86.5%\n",
      "validation loss: 0.57\tvalidation accuracy: 85.9%\n",
      "\n",
      "*** Epoch 10 ***\n",
      "training loss: 0.57\ttraining accuracy: 89.2%\n",
      "validation loss: 0.58\tvalidation accuracy: 88.9%\n",
      "\n",
      "*** Epoch 15 ***\n",
      "training loss: 0.59\ttraining accuracy: 90.8%\n",
      "validation loss: 0.60\tvalidation accuracy: 90.6%\n",
      "\n",
      "*** Epoch 20 ***\n",
      "training loss: 0.60\ttraining accuracy: 91.9%\n",
      "validation loss: 0.61\tvalidation accuracy: 91.8%\n",
      "\n",
      "*** Epoch 25 ***\n",
      "training loss: 0.61\ttraining accuracy: 92.5%\n",
      "validation loss: 0.62\tvalidation accuracy: 92.4%\n",
      "\n",
      "*** Epoch 30 ***\n",
      "training loss: 0.62\ttraining accuracy: 92.9%\n",
      "validation loss: 0.63\tvalidation accuracy: 92.6%\n",
      "\n",
      "*** Epoch 35 ***\n",
      "training loss: 0.63\ttraining accuracy: 93.2%\n",
      "validation loss: 0.64\tvalidation accuracy: 92.9%\n",
      "\n",
      "*** Epoch 40 ***\n",
      "training loss: 0.64\ttraining accuracy: 93.4%\n",
      "validation loss: 0.64\tvalidation accuracy: 93.1%\n",
      "\n",
      "*** Epoch 45 ***\n",
      "training loss: 0.65\ttraining accuracy: 93.6%\n",
      "validation loss: 0.65\tvalidation accuracy: 93.4%\n",
      "\n",
      "*** Epoch 50 ***\n",
      "training loss: 0.66\ttraining accuracy: 93.6%\n",
      "validation loss: 0.66\tvalidation accuracy: 93.6%\n",
      "\n",
      "*** Epoch 55 ***\n",
      "training loss: 0.66\ttraining accuracy: 93.7%\n",
      "validation loss: 0.66\tvalidation accuracy: 93.5%\n",
      "\n",
      "*** Epoch 60 ***\n",
      "training loss: 0.67\ttraining accuracy: 93.7%\n",
      "validation loss: 0.67\tvalidation accuracy: 93.6%\n",
      "\n",
      "*** Epoch 65 ***\n",
      "training loss: 0.67\ttraining accuracy: 93.8%\n",
      "validation loss: 0.67\tvalidation accuracy: 93.7%\n",
      "\n",
      "*** Epoch 70 ***\n",
      "training loss: 0.68\ttraining accuracy: 93.8%\n",
      "validation loss: 0.68\tvalidation accuracy: 93.7%\n",
      "\n",
      "*** Epoch 75 ***\n",
      "training loss: 0.68\ttraining accuracy: 93.8%\n",
      "validation loss: 0.68\tvalidation accuracy: 93.8%\n",
      "\n",
      "*** Epoch 80 ***\n",
      "training loss: 0.68\ttraining accuracy: 93.9%\n",
      "validation loss: 0.68\tvalidation accuracy: 93.9%\n",
      "\n",
      "*** Epoch 85 ***\n",
      "training loss: 0.69\ttraining accuracy: 93.9%\n",
      "validation loss: 0.69\tvalidation accuracy: 93.9%\n",
      "\n",
      "*** Epoch 90 ***\n",
      "training loss: 0.69\ttraining accuracy: 94.0%\n",
      "validation loss: 0.69\tvalidation accuracy: 93.8%\n",
      "\n",
      "*** Epoch 95 ***\n",
      "training loss: 0.69\ttraining accuracy: 94.0%\n",
      "validation loss: 0.69\tvalidation accuracy: 93.9%\n",
      "\n",
      "*** Epoch 100 ***\n",
      "training loss: 0.70\ttraining accuracy: 94.0%\n",
      "validation loss: 0.69\tvalidation accuracy: 93.8%\n",
      "\n",
      "correct predictions:\t4494 out of 7172\n",
      "test data accuracy:\t0.6266034578918015\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "log_dir6 = \"./summaries/\" + datetime.now().strftime(\"%Y%m%d-%H%M%S\")\n",
    "print (log_dir6)\n",
    "\n",
    "tf.reset_default_graph()\n",
    "net1 = MLP(\n",
    "    [784,256,128,25], \n",
    "    w_std=0.003, lr=0.005, dropout=0, bn=True\n",
    "    )\n",
    "\n",
    "hist1 = net1.train(\n",
    "    x_train, y_train_hot, \n",
    "    x_valid, y_valid_hot,\n",
    "    eps=100, bs=1024,\n",
    "    log_dir = log_dir6\n",
    "    )\n",
    "\n",
    "# ============================== Test\n",
    "y_pred = show_test_results(net1, x_test, y_test, cm=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## F. Unbalanced Dataset\n",
    "The results on class A were good. So, we randomly choose 20% of this class for training."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### F. Random Sampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of class A samples: 896\n",
      "x_train:\t(21964, 784)\n",
      "y_train:\t(21964,)\n",
      "\n",
      "*** After Random Sampling***\n",
      "x_train:\t(21248, 784)\n",
      "y_train:\t(21248,)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from math import floor\n",
    "\n",
    "I = np.where(y_train==0)[0]\n",
    "I = np.random.permutation(I)\n",
    "D = I[:floor(0.8 * len(I))]\n",
    "\n",
    "print(f'Number of class A samples: {len(I)}')\n",
    "print('x_train:\\t{}'.format(x_train.shape))\n",
    "print('y_train:\\t{}\\n'.format(y_train.shape))\n",
    "\n",
    "x_tr = np.delete(x_train, D, axis=0)\n",
    "y_tr = np.delete(y_train, D, axis=0)\n",
    "y_tr_hot = np.delete(y_train_hot, D, axis=0)\n",
    "\n",
    "print('*** After Random Sampling***')\n",
    "print('x_train:\\t{}'.format(x_tr.shape))\n",
    "print('y_train:\\t{}\\n'.format(y_tr.shape))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./summaries/20211119-004307\n",
      "*** Epoch 5 ***\n",
      "training loss: 0.34\ttraining accuracy: 93.2%\n",
      "validation loss: 0.40\tvalidation accuracy: 90.9%\n",
      "\n",
      "*** Epoch 10 ***\n",
      "training loss: 0.05\ttraining accuracy: 99.9%\n",
      "validation loss: 0.07\tvalidation accuracy: 99.2%\n",
      "\n",
      "*** Epoch 15 ***\n",
      "training loss: 0.01\ttraining accuracy: 100.0%\n",
      "validation loss: 0.02\tvalidation accuracy: 99.9%\n",
      "\n",
      "*** Epoch 20 ***\n",
      "training loss: 0.01\ttraining accuracy: 100.0%\n",
      "validation loss: 0.01\tvalidation accuracy: 99.9%\n",
      "\n",
      "correct predictions:\t5856 out of 7172\n",
      "test data accuracy:\t0.8165086447295036\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorboard:Deleting accumulator '.'\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "log_dir7 = \"./summaries/\" + datetime.now().strftime(\"%Y%m%d-%H%M%S\")\n",
    "print (log_dir7)\n",
    "\n",
    "tf.reset_default_graph()\n",
    "net1 = MLP(\n",
    "    [784,256,25], \n",
    "    w_std=0.001, lr=0.001, dropout=0.5\n",
    "    ) \n",
    "\n",
    "hist1 = net1.train(\n",
    "    x_tr, y_tr_hot, \n",
    "    x_valid, y_valid_hot,\n",
    "    eps=20, bs=1024,\n",
    "    log_dir = log_dir7\n",
    "    )\n",
    "\n",
    "# ============================== Test\n",
    "y_pred = show_test_results(net1, x_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "authorship_tag": "ABX9TyMR6xqB8Q9bA+XusS+YlJzb",
   "collapsed_sections": [],
   "name": "Hand-Gesture-Classification.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  },
  "latex_envs": {
   "LaTeX_envs_menu_present": true,
   "autoclose": false,
   "autocomplete": true,
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
    "itemize": "Ctrl-I"
   },
   "labels_anchors": false,
   "latex_user_defs": false,
   "report_style_numbering": false,
   "user_envs_cfg": false
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
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    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
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     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
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    "_Feature"
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   "window_display": false
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 "nbformat": 4,
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}