gradCamALL.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Grad Cam on Any Deep Network\n",
    "------------------------------------\n",
    "1) Define model\n",
    "2) get predicted class\n",
    "3) Pass layer_name to grad_cam function\n",
    "4) Outputs heatmap overlayed on input image\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from keras.preprocessing.image import load_img, img_to_array\n",
    "import numpy as np\n",
    "import scipy\n",
    "import argparse\n",
    "import cv2\n",
    "from keras.applications import inception_resnet_v2\n",
    "from keras.applications import resnet50\n",
    "from keras import backend as K\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "K.set_learning_phase(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model = resnet50.ResNet50(weights='imagenet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            (None, 224, 224, 3)  0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv1 (Conv2D)                  (None, 112, 112, 64) 9472        input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "bn_conv1 (BatchNormalization)   (None, 112, 112, 64) 256         conv1[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "activation_1 (Activation)       (None, 112, 112, 64) 0           bn_conv1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2D)  (None, 55, 55, 64)   0           activation_1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "res2a_branch2a (Conv2D)         (None, 55, 55, 64)   4160        max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "bn2a_branch2a (BatchNormalizati (None, 55, 55, 64)   256         res2a_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_2 (Activation)       (None, 55, 55, 64)   0           bn2a_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res2a_branch2b (Conv2D)         (None, 55, 55, 64)   36928       activation_2[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2a_branch2b (BatchNormalizati (None, 55, 55, 64)   256         res2a_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_3 (Activation)       (None, 55, 55, 64)   0           bn2a_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res2a_branch2c (Conv2D)         (None, 55, 55, 256)  16640       activation_3[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "res2a_branch1 (Conv2D)          (None, 55, 55, 256)  16640       max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "bn2a_branch2c (BatchNormalizati (None, 55, 55, 256)  1024        res2a_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "bn2a_branch1 (BatchNormalizatio (None, 55, 55, 256)  1024        res2a_branch1[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "add_1 (Add)                     (None, 55, 55, 256)  0           bn2a_branch2c[0][0]              \n",
      "                                                                 bn2a_branch1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_4 (Activation)       (None, 55, 55, 256)  0           add_1[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res2b_branch2a (Conv2D)         (None, 55, 55, 64)   16448       activation_4[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2b_branch2a (BatchNormalizati (None, 55, 55, 64)   256         res2b_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_5 (Activation)       (None, 55, 55, 64)   0           bn2b_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res2b_branch2b (Conv2D)         (None, 55, 55, 64)   36928       activation_5[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2b_branch2b (BatchNormalizati (None, 55, 55, 64)   256         res2b_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_6 (Activation)       (None, 55, 55, 64)   0           bn2b_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res2b_branch2c (Conv2D)         (None, 55, 55, 256)  16640       activation_6[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2b_branch2c (BatchNormalizati (None, 55, 55, 256)  1024        res2b_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_2 (Add)                     (None, 55, 55, 256)  0           bn2b_branch2c[0][0]              \n",
      "                                                                 activation_4[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_7 (Activation)       (None, 55, 55, 256)  0           add_2[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res2c_branch2a (Conv2D)         (None, 55, 55, 64)   16448       activation_7[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2c_branch2a (BatchNormalizati (None, 55, 55, 64)   256         res2c_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_8 (Activation)       (None, 55, 55, 64)   0           bn2c_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res2c_branch2b (Conv2D)         (None, 55, 55, 64)   36928       activation_8[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2c_branch2b (BatchNormalizati (None, 55, 55, 64)   256         res2c_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_9 (Activation)       (None, 55, 55, 64)   0           bn2c_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res2c_branch2c (Conv2D)         (None, 55, 55, 256)  16640       activation_9[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "bn2c_branch2c (BatchNormalizati (None, 55, 55, 256)  1024        res2c_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_3 (Add)                     (None, 55, 55, 256)  0           bn2c_branch2c[0][0]              \n",
      "                                                                 activation_7[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_10 (Activation)      (None, 55, 55, 256)  0           add_3[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res3a_branch2a (Conv2D)         (None, 28, 28, 128)  32896       activation_10[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3a_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3a_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_11 (Activation)      (None, 28, 28, 128)  0           bn3a_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3a_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_11[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3a_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3a_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_12 (Activation)      (None, 28, 28, 128)  0           bn3a_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3a_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_12[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3a_branch1 (Conv2D)          (None, 28, 28, 512)  131584      activation_10[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3a_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3a_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "bn3a_branch1 (BatchNormalizatio (None, 28, 28, 512)  2048        res3a_branch1[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "add_4 (Add)                     (None, 28, 28, 512)  0           bn3a_branch2c[0][0]              \n",
      "                                                                 bn3a_branch1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_13 (Activation)      (None, 28, 28, 512)  0           add_4[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res3b_branch2a (Conv2D)         (None, 28, 28, 128)  65664       activation_13[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3b_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3b_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_14 (Activation)      (None, 28, 28, 128)  0           bn3b_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3b_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_14[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3b_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3b_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_15 (Activation)      (None, 28, 28, 128)  0           bn3b_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3b_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_15[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3b_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3b_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_5 (Add)                     (None, 28, 28, 512)  0           bn3b_branch2c[0][0]              \n",
      "                                                                 activation_13[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_16 (Activation)      (None, 28, 28, 512)  0           add_5[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res3c_branch2a (Conv2D)         (None, 28, 28, 128)  65664       activation_16[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3c_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3c_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_17 (Activation)      (None, 28, 28, 128)  0           bn3c_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3c_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_17[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3c_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3c_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_18 (Activation)      (None, 28, 28, 128)  0           bn3c_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3c_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_18[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3c_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3c_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_6 (Add)                     (None, 28, 28, 512)  0           bn3c_branch2c[0][0]              \n",
      "                                                                 activation_16[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_19 (Activation)      (None, 28, 28, 512)  0           add_6[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res3d_branch2a (Conv2D)         (None, 28, 28, 128)  65664       activation_19[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3d_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3d_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_20 (Activation)      (None, 28, 28, 128)  0           bn3d_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3d_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_20[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3d_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3d_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_21 (Activation)      (None, 28, 28, 128)  0           bn3d_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res3d_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_21[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn3d_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3d_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_7 (Add)                     (None, 28, 28, 512)  0           bn3d_branch2c[0][0]              \n",
      "                                                                 activation_19[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_22 (Activation)      (None, 28, 28, 512)  0           add_7[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res4a_branch2a (Conv2D)         (None, 14, 14, 256)  131328      activation_22[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4a_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4a_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_23 (Activation)      (None, 14, 14, 256)  0           bn4a_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4a_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_23[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4a_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4a_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_24 (Activation)      (None, 14, 14, 256)  0           bn4a_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4a_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_24[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4a_branch1 (Conv2D)          (None, 14, 14, 1024) 525312      activation_22[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4a_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4a_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "bn4a_branch1 (BatchNormalizatio (None, 14, 14, 1024) 4096        res4a_branch1[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "add_8 (Add)                     (None, 14, 14, 1024) 0           bn4a_branch2c[0][0]              \n",
      "                                                                 bn4a_branch1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_25 (Activation)      (None, 14, 14, 1024) 0           add_8[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res4b_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_25[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4b_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4b_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_26 (Activation)      (None, 14, 14, 256)  0           bn4b_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4b_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_26[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4b_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4b_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_27 (Activation)      (None, 14, 14, 256)  0           bn4b_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4b_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_27[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4b_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4b_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_9 (Add)                     (None, 14, 14, 1024) 0           bn4b_branch2c[0][0]              \n",
      "                                                                 activation_25[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_28 (Activation)      (None, 14, 14, 1024) 0           add_9[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "res4c_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_28[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4c_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4c_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_29 (Activation)      (None, 14, 14, 256)  0           bn4c_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4c_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_29[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4c_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4c_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_30 (Activation)      (None, 14, 14, 256)  0           bn4c_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4c_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_30[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4c_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4c_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_10 (Add)                    (None, 14, 14, 1024) 0           bn4c_branch2c[0][0]              \n",
      "                                                                 activation_28[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_31 (Activation)      (None, 14, 14, 1024) 0           add_10[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "res4d_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_31[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4d_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4d_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_32 (Activation)      (None, 14, 14, 256)  0           bn4d_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4d_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_32[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4d_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4d_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_33 (Activation)      (None, 14, 14, 256)  0           bn4d_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4d_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_33[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4d_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4d_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_11 (Add)                    (None, 14, 14, 1024) 0           bn4d_branch2c[0][0]              \n",
      "                                                                 activation_31[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_34 (Activation)      (None, 14, 14, 1024) 0           add_11[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "res4e_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_34[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4e_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4e_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_35 (Activation)      (None, 14, 14, 256)  0           bn4e_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4e_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_35[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4e_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4e_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_36 (Activation)      (None, 14, 14, 256)  0           bn4e_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4e_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_36[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4e_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4e_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_12 (Add)                    (None, 14, 14, 1024) 0           bn4e_branch2c[0][0]              \n",
      "                                                                 activation_34[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_37 (Activation)      (None, 14, 14, 1024) 0           add_12[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "res4f_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_37[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4f_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4f_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_38 (Activation)      (None, 14, 14, 256)  0           bn4f_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4f_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_38[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4f_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4f_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_39 (Activation)      (None, 14, 14, 256)  0           bn4f_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res4f_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_39[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn4f_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4f_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_13 (Add)                    (None, 14, 14, 1024) 0           bn4f_branch2c[0][0]              \n",
      "                                                                 activation_37[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_40 (Activation)      (None, 14, 14, 1024) 0           add_13[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "res5a_branch2a (Conv2D)         (None, 7, 7, 512)    524800      activation_40[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5a_branch2a (BatchNormalizati (None, 7, 7, 512)    2048        res5a_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_41 (Activation)      (None, 7, 7, 512)    0           bn5a_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5a_branch2b (Conv2D)         (None, 7, 7, 512)    2359808     activation_41[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5a_branch2b (BatchNormalizati (None, 7, 7, 512)    2048        res5a_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_42 (Activation)      (None, 7, 7, 512)    0           bn5a_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5a_branch2c (Conv2D)         (None, 7, 7, 2048)   1050624     activation_42[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5a_branch1 (Conv2D)          (None, 7, 7, 2048)   2099200     activation_40[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5a_branch2c (BatchNormalizati (None, 7, 7, 2048)   8192        res5a_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "bn5a_branch1 (BatchNormalizatio (None, 7, 7, 2048)   8192        res5a_branch1[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "add_14 (Add)                    (None, 7, 7, 2048)   0           bn5a_branch2c[0][0]              \n",
      "                                                                 bn5a_branch1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_43 (Activation)      (None, 7, 7, 2048)   0           add_14[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "res5b_branch2a (Conv2D)         (None, 7, 7, 512)    1049088     activation_43[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5b_branch2a (BatchNormalizati (None, 7, 7, 512)    2048        res5b_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_44 (Activation)      (None, 7, 7, 512)    0           bn5b_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5b_branch2b (Conv2D)         (None, 7, 7, 512)    2359808     activation_44[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5b_branch2b (BatchNormalizati (None, 7, 7, 512)    2048        res5b_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_45 (Activation)      (None, 7, 7, 512)    0           bn5b_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5b_branch2c (Conv2D)         (None, 7, 7, 2048)   1050624     activation_45[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5b_branch2c (BatchNormalizati (None, 7, 7, 2048)   8192        res5b_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_15 (Add)                    (None, 7, 7, 2048)   0           bn5b_branch2c[0][0]              \n",
      "                                                                 activation_43[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_46 (Activation)      (None, 7, 7, 2048)   0           add_15[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "res5c_branch2a (Conv2D)         (None, 7, 7, 512)    1049088     activation_46[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5c_branch2a (BatchNormalizati (None, 7, 7, 512)    2048        res5c_branch2a[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_47 (Activation)      (None, 7, 7, 512)    0           bn5c_branch2a[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5c_branch2b (Conv2D)         (None, 7, 7, 512)    2359808     activation_47[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5c_branch2b (BatchNormalizati (None, 7, 7, 512)    2048        res5c_branch2b[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "activation_48 (Activation)      (None, 7, 7, 512)    0           bn5c_branch2b[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "res5c_branch2c (Conv2D)         (None, 7, 7, 2048)   1050624     activation_48[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "bn5c_branch2c (BatchNormalizati (None, 7, 7, 2048)   8192        res5c_branch2c[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "add_16 (Add)                    (None, 7, 7, 2048)   0           bn5c_branch2c[0][0]              \n",
      "                                                                 activation_46[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_49 (Activation)      (None, 7, 7, 2048)   0           add_16[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "avg_pool (AveragePooling2D)     (None, 1, 1, 2048)   0           activation_49[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "flatten_1 (Flatten)             (None, 2048)         0           avg_pool[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "fc1000 (Dense)                  (None, 1000)         2049000     flatten_1[0][0]                  \n",
      "==================================================================================================\n",
      "Total params: 25,636,712\n",
      "Trainable params: 25,583,592\n",
      "Non-trainable params: 53,120\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "layer_dict = dict([(layer.name, layer) for layer in model.layers])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def load_image(image_path):\n",
    "    # Util function to open, resize and format pictures\n",
    "    # into appropriate tensors.\n",
    "    img = load_img(image_path, target_size=(224, 224))\n",
    "    img = img_to_array(img)\n",
    "    img = np.expand_dims(img, axis=0)\n",
    "    img = resnet50.preprocess_input(img)\n",
    "    return img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "preprocessed_image = load_image(\"/home/nishanth/Documents/index.jpeg\")\n",
    "org_img = cv2.resize(cv2.imread(\"/home/nishanth/Documents/index.jpeg\"),(224,224))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted class:\n",
      "African_elephant (n02504458) with probability 0.83\n"
     ]
    }
   ],
   "source": [
    "predictions = model.predict(preprocessed_image)\n",
    "top_1 = resnet50.decode_predictions(predictions)[0][0]\n",
    "print('Predicted class:')\n",
    "print('%s (%s) with probability %.2f' % (top_1[1], top_1[0], top_1[2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "predicted_class = np.argmax(predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def grad_cam(input_model, image, org_img, category_index, layer_name):\n",
    "    \n",
    "\n",
    "    mod_outputs = input_model.output[0, category_index]\n",
    "    conv_output = input_model.get_layer(layer_name).output\n",
    "    grads = K.gradients(mod_outputs, conv_output)[0]\n",
    "    gradient_function = K.function([input_model.input], [conv_output, grads])\n",
    "    output, grads_val = gradient_function([image])\n",
    "    output, grads_val = output[0, :], grads_val[0, :, :, :]\n",
    "    weights = np.mean(grads_val, axis = (0, 1))\n",
    "    cam = np.ones(output.shape[0 : 2], dtype = np.float32)\n",
    "    cam = np.dot(output, weights)\n",
    "    cam = cv2.resize(cam, (224, 224))\n",
    "    cam = np.maximum(cam, 0)\n",
    "    heatmap = cam / np.max(cam)\n",
    "    cam = cv2.applyColorMap(np.uint8(255*heatmap), cv2.COLORMAP_JET)\n",
    "    #cam = np.float32(cam) \n",
    "    #grad_cam_out = 0.3 * np.uint8(255 * cam / np.max(cam)) + 0.7 * org_img\n",
    "    grad_cam_out = 0.3 * cam + 0.7 * org_img\n",
    "    return grad_cam_out\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f13743b5cd0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Ri9cYfbLltLHurJI621xedzGKVLdlcp/njOVa5d7xfreJJ/qbSa+FdVav4+Zy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+Lt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\nKSg8raf1tB6s/wf/Ghcav6XkqgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f137480b1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "heatmap_out = grad_cam(model, preprocessed_image, org_img, predicted_class, \"res5c_branch2c\")\n",
    "im = cv2.cvtColor(heatmap_out.astype('uint8'), cv2.COLOR_BGR2RGB)\n",
    "plt.imshow(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
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