CSE515_MWDB_Project/Phase 1/task_1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Global imports\n",
    "import numpy as np\n",
    "import cv2\n",
    "\n",
    "import torch\n",
    "import torchvision.transforms as transforms\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading Caltech101 dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torchvision.datasets as datasets\n",
    "\n",
    "dataset_path = \"C:\\Kaushik\\ASU\\CSE 515 - Multimedia and Web Databases\\Project\\Phase 1\\Datasets\"\n",
    "\n",
    "dataset = datasets.Caltech101(\n",
    "    root=dataset_path,\n",
    "    download=False,  # True if downloading for first time\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Select image by ID"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "selected_image_id = int(input(\"Enter image ID: \"))\n",
    "sample_image, sample_label = dataset[selected_image_id]\n",
    "plt.imshow(sample_image)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Class transform to partition image into rows x cols grid\n",
    "\n",
    "\n",
    "class GridPartition:\n",
    "    def __init__(self, rows, cols):\n",
    "        self.rows = rows\n",
    "        self.cols = cols\n",
    "\n",
    "    def __call__(self, img):\n",
    "        img_width, img_height = img.size\n",
    "        cell_width = img_width // self.cols\n",
    "        cell_height = img_height // self.rows\n",
    "\n",
    "        grids = []\n",
    "        for i in range(self.rows):\n",
    "            for j in range(self.cols):\n",
    "                left = j * cell_width\n",
    "                top = i * cell_height\n",
    "                right = left + cell_width\n",
    "                bottom = top + cell_height\n",
    "                grid = img.crop((left, top, right, bottom))\n",
    "                grids.append(grid)\n",
    "\n",
    "        return grids\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature model 1: Color moments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import skew\n",
    "\n",
    "\n",
    "def compute_color_moments(image):\n",
    "    image = np.array(image)  # Convert PIL Image to NumPy array\n",
    "    moments = []\n",
    "\n",
    "    for channel in range(3):  # Iterate over RGB channels\n",
    "        channel_data = image[:, :, channel]\n",
    "        mean = np.mean(channel_data)\n",
    "        std_dev = np.std(channel_data)\n",
    "        skewness = skew(channel_data, axis=None)\n",
    "        moments.append([mean, std_dev, skewness])\n",
    "\n",
    "    return moments\n",
    "\n",
    "\n",
    "# Iterate over grid cells and return as 1-d array for easier resizing by torch\n",
    "def compute_color_moments_for_grid(grid):\n",
    "    color_moments = [compute_color_moments(grid_cell) for grid_cell in grid]\n",
    "    return np.array(color_moments).flatten()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def combine_color_moments(grid_color_moments):\n",
    "    return torch.Tensor(grid_color_moments).view(\n",
    "        10, 10, 3, 3\n",
    "    )  # resize as needed: 10x10 grid, 3 channels per cell, 3 moments per channel\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Composed color moment transform (CM10x10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[[[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]]\n",
      "\n",
      "\n",
      " [[[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]]\n",
      "\n",
      "\n",
      " [[[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.54710007e+02  6.57698035e-01 -2.63368249e+00]\n",
      "   [ 2.54923340e+02  3.42717886e-01 -5.19701481e+00]\n",
      "   [ 2.54750000e+02  5.83809316e-01 -2.20497680e+00]]\n",
      "\n",
      "  [[ 2.54966660e+02  1.79505497e-01 -5.19946957e+00]\n",
      "   [ 2.54970001e+02  1.70587227e-01 -5.51037741e+00]\n",
      "   [ 2.54963333e+02  2.04911903e-01 -6.04352093e+00]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]]\n",
      "\n",
      "\n",
      " [[[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.52203339e+02  1.00154209e+01 -4.72609568e+00]\n",
      "   [ 2.52286667e+02  1.01441851e+01 -4.94595528e+00]\n",
      "   [ 2.52289993e+02  1.03730049e+01 -5.01307106e+00]]\n",
      "\n",
      "  [[ 2.37803329e+02  2.78608093e+01 -1.55498159e+00]\n",
      "   [ 2.34506668e+02  3.20275383e+01 -1.34417689e+00]\n",
      "   [ 2.30300003e+02  3.94261742e+01 -1.39859498e+00]]\n",
      "\n",
      "  [[ 2.06220001e+02  4.53948402e+01 -5.64331174e-01]\n",
      "   [ 1.93993332e+02  5.19916000e+01 -3.60722393e-01]\n",
      "   [ 1.74399994e+02  6.12691345e+01 -6.11884221e-02]]\n",
      "\n",
      "  [[ 2.06830002e+02  4.82941093e+01 -6.08778417e-01]\n",
      "   [ 1.96363327e+02  5.50190086e+01 -4.05773431e-01]\n",
      "   [ 1.81383331e+02  6.40616608e+01 -1.61348820e-01]]\n",
      "\n",
      "  [[ 2.36139999e+02  3.58651237e+01 -1.81053245e+00]\n",
      "   [ 2.34316666e+02  3.99032555e+01 -1.84734416e+00]\n",
      "   [ 2.31520004e+02  4.67114868e+01 -1.98882532e+00]]\n",
      "\n",
      "  [[ 2.54266663e+02  2.14993548e+00 -6.34870005e+00]\n",
      "   [ 2.54509995e+02  2.21883607e+00 -7.93815517e+00]\n",
      "   [ 2.54463333e+02  2.59010720e+00 -8.23780155e+00]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]]\n",
      "\n",
      "\n",
      " [[[ 1.62456665e+02  6.92447433e+01  7.08163455e-02]\n",
      "   [ 1.51743332e+02  7.45378952e+01  1.81094214e-01]\n",
      "   [ 1.40889999e+02  8.08659286e+01  2.60647833e-01]]\n",
      "\n",
      "  [[ 1.54656662e+02  7.03443832e+01  8.01036805e-02]\n",
      "   [ 1.44873337e+02  7.47838516e+01  1.80467248e-01]\n",
      "   [ 1.37339996e+02  7.77658768e+01  2.97032177e-01]]\n",
      "\n",
      "  [[ 1.73463333e+02  4.59732018e+01 -1.25360429e-01]\n",
      "   [ 1.61820007e+02  4.49838600e+01 -8.56622756e-02]\n",
      "   [ 1.48986664e+02  4.59477959e+01  8.01871717e-02]]\n",
      "\n",
      "  [[ 1.66779999e+02  4.14694862e+01  1.46571159e-01]\n",
      "   [ 1.54846664e+02  3.48746796e+01  7.51983840e-03]\n",
      "   [ 1.43669998e+02  2.89604511e+01 -1.51391149e-01]]\n",
      "\n",
      "  [[ 1.53446671e+02  3.60159302e+01 -8.31869781e-01]\n",
      "   [ 1.51183334e+02  3.58542862e+01 -8.55960667e-01]\n",
      "   [ 1.69103333e+02  3.76489830e+01 -8.69700313e-01]]\n",
      "\n",
      "  [[ 1.53279999e+02  3.12257633e+01 -3.19770157e-01]\n",
      "   [ 1.51743332e+02  3.14255333e+01 -3.12740445e-01]\n",
      "   [ 1.67190002e+02  3.31249237e+01 -2.22840086e-01]]\n",
      "\n",
      "  [[ 1.44866669e+02  2.52188206e+01  3.44266109e-02]\n",
      "   [ 1.32013336e+02  2.19881744e+01 -2.03826427e-01]\n",
      "   [ 1.19396667e+02  2.30752239e+01 -3.23609829e-01]]\n",
      "\n",
      "  [[ 1.46020004e+02  5.69442368e+01  4.19411272e-01]\n",
      "   [ 1.36593338e+02  5.91075401e+01  5.88113248e-01]\n",
      "   [ 1.29396667e+02  6.18047409e+01  7.38014936e-01]]\n",
      "\n",
      "  [[ 1.52433334e+02  7.04666748e+01  3.23606700e-01]\n",
      "   [ 1.43600006e+02  7.52337723e+01  4.00436848e-01]\n",
      "   [ 1.36683334e+02  7.97173538e+01  4.22783375e-01]]\n",
      "\n",
      "  [[ 1.64559998e+02  6.91445847e+01  3.86838652e-02]\n",
      "   [ 1.55346664e+02  7.42358398e+01  1.28387168e-01]\n",
      "   [ 1.48869995e+02  7.90541534e+01  1.61970302e-01]]]\n",
      "\n",
      "\n",
      " [[[ 1.60363327e+02  6.68925323e+01  6.48481622e-02]\n",
      "   [ 1.48836670e+02  7.21250076e+01  2.05606118e-01]\n",
      "   [ 1.36993332e+02  7.77189789e+01  2.78239518e-01]]\n",
      "\n",
      "  [[ 1.56583328e+02  6.88461761e+01  5.59217818e-02]\n",
      "   [ 1.45600006e+02  7.40602875e+01  1.60494938e-01]\n",
      "   [ 1.36136673e+02  7.68329697e+01  2.91585863e-01]]\n",
      "\n",
      "  [[ 1.74029999e+02  4.62856598e+01 -6.27577752e-02]\n",
      "   [ 1.62903336e+02  4.50085983e+01 -1.01143010e-01]\n",
      "   [ 1.50273331e+02  4.39119415e+01 -7.14720180e-03]]\n",
      "\n",
      "  [[ 1.61990005e+02  4.27014809e+01  2.78086454e-01]\n",
      "   [ 1.50326660e+02  3.74347420e+01  6.16108812e-02]\n",
      "   [ 1.39906662e+02  3.10518589e+01 -2.63566852e-01]]\n",
      "\n",
      "  [[ 1.54066666e+02  3.23888168e+01 -1.07505417e+00]\n",
      "   [ 1.51986664e+02  3.23104706e+01 -1.09906793e+00]\n",
      "   [ 1.69596664e+02  3.46202354e+01 -1.10477662e+00]]\n",
      "\n",
      "  [[ 1.39270004e+02  3.17540092e+01 -4.68760520e-01]\n",
      "   [ 1.37743332e+02  3.15964794e+01 -4.61559206e-01]\n",
      "   [ 1.50236664e+02  3.23626442e+01 -4.08295214e-01]]\n",
      "\n",
      "  [[ 1.42283340e+02  3.18476009e+01 -6.01729043e-02]\n",
      "   [ 1.28633331e+02  2.69245663e+01 -2.58602649e-01]\n",
      "   [ 1.18096664e+02  2.36929092e+01 -5.09195566e-01]]\n",
      "\n",
      "  [[ 1.44053329e+02  5.32151985e+01  3.90238345e-01]\n",
      "   [ 1.32103333e+02  5.43714943e+01  5.82211494e-01]\n",
      "   [ 1.22500000e+02  5.71484337e+01  8.24262619e-01]]\n",
      "\n",
      "  [[ 1.44236664e+02  6.43232498e+01  5.09608328e-01]\n",
      "   [ 1.33880005e+02  6.89022903e+01  5.77082872e-01]\n",
      "   [ 1.25480003e+02  7.35727539e+01  6.49692595e-01]]\n",
      "\n",
      "  [[ 1.55456665e+02  6.78821106e+01  1.75332382e-01]\n",
      "   [ 1.45513336e+02  7.23643799e+01  2.68143505e-01]\n",
      "   [ 1.33446671e+02  7.84251709e+01  3.74798536e-01]]]\n",
      "\n",
      "\n",
      " [[[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.54990005e+02  9.94987413e-02 -9.84937096e+00]\n",
      "   [ 2.54990005e+02  9.94987413e-02 -9.84937096e+00]\n",
      "   [ 2.54990005e+02  9.94987413e-02 -9.84937096e+00]]\n",
      "\n",
      "  [[ 2.52176666e+02  9.82304001e+00 -5.21032906e+00]\n",
      "   [ 2.52350006e+02  1.07418575e+01 -5.18172932e+00]\n",
      "   [ 2.51553329e+02  1.13572512e+01 -5.04050493e+00]]\n",
      "\n",
      "  [[ 2.34343338e+02  3.08486423e+01 -1.39186811e+00]\n",
      "   [ 2.30179993e+02  3.63200722e+01 -1.24187469e+00]\n",
      "   [ 2.23606674e+02  4.62066231e+01 -1.26233923e+00]]\n",
      "\n",
      "  [[ 2.09796661e+02  5.45326996e+01 -1.01019919e+00]\n",
      "   [ 2.00146667e+02  5.89418221e+01 -7.22108185e-01]\n",
      "   [ 1.86076660e+02  6.55873795e+01 -3.15005690e-01]]\n",
      "\n",
      "  [[ 2.13206665e+02  4.94687500e+01 -9.57047522e-01]\n",
      "   [ 2.03076660e+02  5.49594765e+01 -6.23570085e-01]\n",
      "   [ 1.89906662e+02  6.14942093e+01 -2.00811476e-01]]\n",
      "\n",
      "  [[ 2.31356674e+02  3.92177200e+01 -1.46929097e+00]\n",
      "   [ 2.28573334e+02  4.37885590e+01 -1.39060414e+00]\n",
      "   [ 2.24633331e+02  4.99822540e+01 -1.33810270e+00]]\n",
      "\n",
      "  [[ 2.53173340e+02  9.25004292e+00 -7.18825388e+00]\n",
      "   [ 2.53006668e+02  9.65090466e+00 -7.23071098e+00]\n",
      "   [ 2.53039993e+02  9.98457432e+00 -7.30431223e+00]]\n",
      "\n",
      "  [[ 2.54933334e+02  2.49443829e-01 -3.47439623e+00]\n",
      "   [ 2.54933334e+02  2.49443829e-01 -3.47439623e+00]\n",
      "   [ 2.54933334e+02  2.49443829e-01 -3.47439623e+00]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]]\n",
      "\n",
      "\n",
      " [[[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]]\n",
      "\n",
      "\n",
      " [[[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]]\n",
      "\n",
      "\n",
      " [[[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]\n",
      "\n",
      "  [[ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]\n",
      "   [ 2.55000000e+02  0.00000000e+00             nan]]]]\n"
     ]
    }
   ],
   "source": [
    "CM_transform = transforms.Compose(\n",
    "    [\n",
    "        transforms.Resize((100, 300)),  # resize to H:W=100:300\n",
    "        GridPartition(\n",
    "            rows=10, cols=10\n",
    "        ),  # partition into grid of 10 rows, 10 columns as a list\n",
    "        compute_color_moments_for_grid,\n",
    "        combine_color_moments,\n",
    "    ]\n",
    ")\n",
    "\n",
    "if np.array(sample_image).shape[2] >= 3:\n",
    "    # no color moments for grayscale images\n",
    "    cm_fd = CM_transform(sample_image)\n",
    "else:\n",
    "    cm_fd = torch.zeros((10, 10, 3, 3)) #TODO: store with some flag to indicate grayscale\n",
    "\n",
    "print(np.array(cm_fd))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(note that skewness is NaN when all elements are equal i.e. std. dev. = 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Visualizing color moments - stacked bar chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2700x1800 with 100 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# cm_fd should be a NumPy array of shape (M, N, 3, 3), where (M, N) is the grid size\n",
    "\n",
    "# Define the number of grid cells (M and N)\n",
    "M, N = cm_fd.shape[:2]\n",
    "\n",
    "# Create subplots for each color moment (mean, standard deviation, skewness)\n",
    "fig, axes = plt.subplots(M, N, figsize=(27, 18))\n",
    "\n",
    "# Loop through each grid cell and visualize the color moments as stacked bar charts\n",
    "for i in range(M):\n",
    "    for j in range(N):\n",
    "        moments = cm_fd[i, j]\n",
    "        colors = [\"red\", \"green\", \"blue\"]\n",
    "\n",
    "        for c in range(3):\n",
    "            ax = axes[i, j]\n",
    "            ax.bar(\n",
    "                [\"Mean\", \"Std Dev\", \"Skewness\"],\n",
    "                moments[c],\n",
    "                color=colors[c],\n",
    "                bottom=np.sum(np.array(moments[:c]), axis=0),\n",
    "            )  # stack channels\n",
    "            ax.set_ylim(\n",
    "                0, 3 * 255\n",
    "            )  # since max possible meanset can be [255, 255, 255] for entirely white grid cell\n",
    "            ax.set_title(f\"Grid Cell ({i}, {j})\")\n",
    "\n",
    "\n",
    "# Adjust spacing and show the plot\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Feature model 2: Histogram Oriented Gradients (HOG)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "def compute_gradient_histogram(grid_cell):\n",
    "    histograms = []\n",
    "\n",
    "    # Convert grid cell to NumPy array\n",
    "    grid_array = np.array(grid_cell, dtype=np.uint8)\n",
    "\n",
    "    # Compute the gradient using first-order central differences\n",
    "    dx = cv2.Sobel(\n",
    "        grid_array, cv2.CV_32F, dx=1, dy=0, ksize=1\n",
    "    )  # first order x derivative = [-1, 0, 1]\n",
    "    dy = cv2.Sobel(\n",
    "        grid_array, cv2.CV_32F, dx=0, dy=1, ksize=1\n",
    "    )  # first order y derivative = [-1, 0, 1]^T\n",
    "\n",
    "    # Compute magnitude and direction of gradients\n",
    "    magnitude = np.sqrt(dx**2 + dy**2)\n",
    "    direction = np.arctan2(dy, dx) * 180 / np.pi  # in degrees\n",
    "\n",
    "    # Compute HOG - 9 bins, counted across the range of -180 to 180 degrees, weighted by gradient magnitude\n",
    "    histogram, _ = np.histogram(direction, bins=9, range=(-180, 180), weights=magnitude)\n",
    "\n",
    "    histograms.append(histogram)\n",
    "\n",
    "    return histograms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "def compute_histograms_for_grid(grid):\n",
    "    histograms = [compute_gradient_histogram(grid_cell) for grid_cell in grid]\n",
    "    return np.array(histograms).flatten()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "def combine_histograms(grid_histograms):\n",
    "    return torch.Tensor(grid_histograms).view(10, 10, 9)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]]\n",
      "\n",
      " [[0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]\n",
      "  [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "   0.00000000e+00]]]\n"
     ]
    }
   ],
   "source": [
    "HOG_transform = transforms.Compose(\n",
    "    [\n",
    "        transforms.Grayscale(num_output_channels=1),  # grayscale transform\n",
    "        transforms.Resize((100, 300)),  # resize to H:W=100:300\n",
    "        GridPartition(\n",
    "            rows=10, cols=10\n",
    "        ),  # partition into grid of 10 rows, 10 columns as a list\n",
    "        compute_histograms_for_grid,\n",
    "        combine_histograms,\n",
    "    ]\n",
    ")\n",
    "\n",
    "hog_fd = HOG_transform(sample_image)\n",
    "print(np.array(hog_fd))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualizing HOG as histograms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 4800x4800 with 100 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# # The 'hog' should now contain the 10x10x9 feature descriptor\n",
    "# # Reshape it to a 10x10 grid of histograms, each of shape (9,)\n",
    "histograms = np.array(hog_fd.reshape(10, 10, 9))\n",
    "\n",
    "# # Visualize the histograms\n",
    "fig, axes = plt.subplots(10, 10, figsize=(48, 48))\n",
    "for i in range(10):\n",
    "    for j in range(10):\n",
    "        histogram = histograms[i, j]\n",
    "        angles = np.linspace(-180, 180, 9, endpoint=False)\n",
    "\n",
    "        axes[i, j].bar(angles, histogram, width=40, align=\"edge\", color=\"b\", alpha=0.7)\n",
    "        axes[i, j].set_xlim(-180, 180)\n",
    "        axes[i, j].set_ylim(0, np.max(histogram) * 1.1)\n",
    "        axes[i, j].set_xticks([-180, -140, -100, -60, -20, 20, 60, 100, 140])\n",
    "        axes[i, j].set_title(f\"Grid Cell ({i}, {j})\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing HOG gradient directions as an arrow overlay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a blank canvas to visualize the HOG features\n",
    "block_size = 30\n",
    "canvas = np.zeros((10 * block_size, 10 * block_size, 3), dtype=np.uint8)\n",
    "\n",
    "# Define the arrow properties\n",
    "base_arrow_length = block_size * 3 / 4  # Adjust as needed\n",
    "arrow_color = (0, 255, 0)  # Green arrows for gradient direction\n",
    "\n",
    "# Loop through each block in the HOG feature descriptor\n",
    "for i in range(10):\n",
    "    for j in range(10):\n",
    "        block = hog_fd[i, j]\n",
    "        x, y = j * block_size, i * block_size  # Top-left corner of the block\n",
    "\n",
    "        # Compute the center position of the block\n",
    "        center_x = x + block_size // 2\n",
    "        center_y = y + block_size // 2\n",
    "\n",
    "        # Find n most dominant directions (pairs of index and gradient magnitude in that direction)\n",
    "        num_dir = 1\n",
    "        dominant_directions = [pair for pair in sorted(\n",
    "                list(enumerate(block)), key=lambda x: x[1], reverse=True\n",
    "            )[:num_dir]\n",
    "        ]\n",
    "\n",
    "        for idx, (direction, magnitude) in enumerate(dominant_directions):\n",
    "            arrow_thickness = num_dir - idx # decreasing thickness\n",
    "            \n",
    "            # Compute end points\n",
    "            # arrow_start_x = int(\n",
    "            #     center_x - ((base_arrow_length * np.cos(np.deg2rad(direction * 40))) / 2)\n",
    "            # )\n",
    "            # arrow_start_y = int(\n",
    "            #     center_y - ((base_arrow_length * np.sin(np.deg2rad(direction * 40))) / 2)\n",
    "            # )\n",
    "            arrow_end_x = int(\n",
    "                center_x\n",
    "                + ((base_arrow_length * np.cos(np.deg2rad(direction * 40))) / 2)\n",
    "            )\n",
    "            arrow_end_y = int(\n",
    "                center_y\n",
    "                + ((base_arrow_length * np.sin(np.deg2rad(direction * 40))) / 2 )\n",
    "            )\n",
    "\n",
    "            # Draw the arrow on the canvas\n",
    "            cv2.arrowedLine(\n",
    "                canvas,\n",
    "                (center_x, center_y),\n",
    "                # (arrow_start_x, arrow_start_y),\n",
    "                (arrow_end_x, arrow_end_y),\n",
    "                arrow_color,\n",
    "                thickness=arrow_thickness,\n",
    "                tipLength=0.2,\n",
    "            )\n",
    "\n",
    "# Display the canvas with HOG arrows visualization alongside HOG overlay over resized image\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 8), sharex=True, sharey=False)\n",
    "\n",
    "ax1.imshow(canvas)\n",
    "ax1.set_title('Histogram of Oriented Gradients (HOG)')\n",
    "\n",
    "ax2.imshow(transforms.Resize((300,300))(sample_image))\n",
    "ax2.imshow(canvas, alpha=0.5) # overlay HOG on image\n",
    "# ax.imshow(transforms.Resize((300, 300))(sample_image))\n",
    "ax2.set_title('HOG Overlay (original resized to 300x300)')\n",
    "\n",
    "ax1.set_xticks(range(0, 300, 30))\n",
    "ax1.set_yticks(range(0, 300, 30))\n",
    "ax2.set_xticks(range(0, 300, 30))\n",
    "ax2.set_yticks(range(0, 300, 30))\n",
    "plt.grid()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Working with ResNet50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torchvision.models as models\n",
    "\n",
    "# use GPU (Nvidia)\n",
    "if torch.cuda.is_available():\n",
    "    dev = torch.device(\"cuda\")\n",
    "    torch.cuda.empty_cache()\n",
    "else:\n",
    "    dev = torch.device(\"cpu\")\n",
    "\n",
    "print(f\"Using {dev}\")\n",
    "\n",
    "# Load model\n",
    "model = models.resnet50(models.ResNet50_Weights.DEFAULT)\n",
    "model = model.to(dev)\n",
    "\n",
    "# ResNet architecture in brief\n",
    "model.eval()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### ResNet50 - Feature extractor module (for ease of use - attach hooks at multiple layers at once)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Feature extractor for all layers at once\n",
    "\n",
    "\n",
    "class FeatureExtractor(torch.nn.Module):\n",
    "    def __init__(self, model, layers):\n",
    "        super().__init__()\n",
    "        self.model = model\n",
    "        self.layers = layers\n",
    "        self._features = {layer: None for layer in layers}  # store layer outputs here\n",
    "\n",
    "        # Create hooks for all specified layers at once\n",
    "        for layer_id in layers:\n",
    "            layer = dict(self.model.named_modules())[layer_id]  # get actual layer in the model\n",
    "            layer.register_forward_hook(self.save_outputs_hook(layer_id))  # register feature extractor hook on layer\n",
    "\n",
    "    # Hook to save output of layer\n",
    "    def save_outputs_hook(self, layer_id):\n",
    "        def fn(_module, _input, output):\n",
    "            self._features[layer_id] = output\n",
    "\n",
    "        return fn\n",
    "\n",
    "    # Forward pass returns extracted features\n",
    "    def forward(self, input):\n",
    "        _ = self.model(input)\n",
    "        return self._features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Resize image to 224x224 with 3 channels for ResNet50 (no grayscale)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "resized_image = (\n",
    "    torch.Tensor(np.array(transforms.Resize((224, 224))(sample_image)).flatten())\n",
    "    .view(1, 3, 224, 224)\n",
    "    .to(dev)\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'avgpool': torch.Size([1, 2048, 1, 1]), 'layer3': torch.Size([1, 1024, 14, 14]), 'fc': torch.Size([1, 1000])}\n"
     ]
    }
   ],
   "source": [
    "# Attach all hooks on model and extract features\n",
    "\n",
    "resnet_features = FeatureExtractor(model=model, layers=[\"avgpool\", \"layer3\", \"fc\"])\n",
    "\n",
    "features = resnet_features(resized_image)\n",
    "\n",
    "print({name: output.shape for name, output in features.items()})\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ResNet-AvgPool-1024"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([1.9426, 2.6439, 0.0000,  ..., 0.0000, 0.8319, 0.0000], device='cuda:0',\n",
      "       grad_fn=<ReshapeAliasBackward0>)\n",
      "tensor([2.2933, 0.0000, 2.4384,  ..., 0.0000, 0.0000, 0.4159], device='cuda:0',\n",
      "       grad_fn=<MeanBackward1>)\n"
     ]
    }
   ],
   "source": [
    "avgpool_2048 = features[\"avgpool\"]\n",
    "\n",
    "# Reshape the vector into row pairs of elements and average across rows\n",
    "avgpool_1024_fd = torch.mean(avgpool_2048.view(-1, 2), axis=1)\n",
    "\n",
    "print(avgpool_2048.flatten())\n",
    "print(avgpool_1024_fd)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ResNet-Layer3-1024"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[[[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          ...,\n",
      "          [2.5682e+01, 4.2184e+01, 4.1923e+01,  ..., 3.6128e+01,\n",
      "           3.8690e+01, 2.4934e+01],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00]],\n",
      "\n",
      "         [[2.5090e+02, 4.3473e+02, 3.5955e+02,  ..., 3.2161e+02,\n",
      "           3.5421e+02, 2.8750e+02],\n",
      "          [7.2420e+01, 1.5282e+02, 1.4668e+02,  ..., 1.2188e+02,\n",
      "           1.3251e+02, 9.7097e+01],\n",
      "          [1.4194e+01, 2.2164e+01, 2.1021e+01,  ..., 2.3378e+01,\n",
      "           1.9422e+01, 1.5501e+01],\n",
      "          ...,\n",
      "          [1.7674e+01, 2.9534e+01, 2.8957e+01,  ..., 2.7021e+01,\n",
      "           2.8365e+01, 1.7271e+01],\n",
      "          [2.0392e+02, 3.0679e+02, 2.2008e+02,  ..., 2.7134e+02,\n",
      "           2.6721e+02, 1.7477e+02],\n",
      "          [1.0662e+02, 2.8967e+02, 2.5432e+02,  ..., 2.5917e+02,\n",
      "           3.0687e+02, 2.4542e+02]],\n",
      "\n",
      "         [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [4.4301e+01, 1.4492e+02, 7.9154e+01,  ..., 4.9435e+01,\n",
      "           3.4705e+01, 2.1634e+01],\n",
      "          ...,\n",
      "          [2.3120e+01, 1.6354e+01, 2.7114e+01,  ..., 1.8197e+01,\n",
      "           3.0402e+01, 2.6725e+01],\n",
      "          [0.0000e+00, 0.0000e+00, 5.9414e+01,  ..., 2.7847e+00,\n",
      "           1.9872e+01, 3.6130e+01],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00]],\n",
      "\n",
      "         ...,\n",
      "\n",
      "         [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          ...,\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00]],\n",
      "\n",
      "         [[1.5585e+01, 2.9524e+01, 4.0533e+01,  ..., 1.4366e+01,\n",
      "           3.7882e+01, 4.8514e+01],\n",
      "          [2.4785e+01, 6.5535e+01, 7.0544e+01,  ..., 4.7574e+01,\n",
      "           7.0169e+01, 6.4070e+01],\n",
      "          [1.0898e-02, 1.3153e+01, 2.5829e+01,  ..., 7.3081e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          ...,\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00]],\n",
      "\n",
      "         [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          ...,\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00],\n",
      "          [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
      "           0.0000e+00, 0.0000e+00]]]], device='cuda:0',\n",
      "       grad_fn=<ReluBackward0>)\n",
      "tensor([ 1.3118, 62.1597, 38.8808,  ...,  0.1582, 10.7903,  0.0000],\n",
      "       device='cuda:0', grad_fn=<MeanBackward1>)\n"
     ]
    }
   ],
   "source": [
    "layer3_1024_14_14 = features[\"layer3\"]\n",
    "\n",
    "# Reshape the vector into 1024 rows of 196 elements and average across rows\n",
    "layer3_1024_fd = torch.mean(layer3_1024_14_14.view(1024, -1), axis=1)\n",
    "\n",
    "print(layer3_1024_14_14)\n",
    "print(layer3_1024_fd)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ResNet-FC-1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([-1.6599e+01, -7.3065e+00, -9.9335e+00, -1.9164e+01, -1.4890e+01,\n",
      "        -1.2751e+01, -1.0787e+01, -3.0016e+01, -1.4808e+01,  8.2885e+00,\n",
      "         9.2186e+00, -4.6726e+01, -1.5658e+01, -1.3921e+01, -3.9682e+01,\n",
      "        -6.2184e+00, -3.4682e+01, -1.5706e+01,  2.5679e+01, -7.3244e-01,\n",
      "        -1.4558e+01, -7.1408e+00,  2.2808e+01,  4.2694e+01,  1.3051e+01,\n",
      "        -7.2299e+00, -3.7666e+01, -7.7757e+00, -1.1570e+01,  1.4032e+01,\n",
      "        -2.4568e+01,  5.0127e+00, -1.5342e+01, -3.5899e+00, -3.1899e+01,\n",
      "        -6.2582e+00,  1.6825e+01, -2.2763e+01,  6.5692e+00, -8.2334e+00,\n",
      "        -3.3320e+01, -1.1561e+01, -1.0618e+01,  1.8856e+01, -1.0095e+01,\n",
      "        -1.8097e+01, -4.2079e+01, -8.0502e+00, -2.1285e+01, -1.4217e+01,\n",
      "        -2.5346e+01, -8.8489e+00,  1.1895e+01,  9.8676e-01, -3.7103e+01,\n",
      "        -5.0455e+00, -1.3847e+01, -3.5528e+01, -1.8539e+01,  2.3709e+01,\n",
      "         6.2435e+01,  1.6605e+00, -3.9280e+00, -1.8692e+01,  1.5156e+01,\n",
      "        -7.0797e+00, -9.6634e+00, -2.3084e+01, -1.9590e+01, -1.0596e+01,\n",
      "        -4.5171e+01,  1.2393e+01, -1.8126e+01, -2.8664e+01, -4.4424e+01,\n",
      "        -4.7200e+01, -9.7867e+00, -1.4484e+01, -3.5850e+01, -2.1643e+01,\n",
      "         3.2526e+01, -1.8786e+01, -4.4862e-01, -3.0894e+01, -1.5188e+01,\n",
      "        -5.2455e+00,  4.5613e+01,  4.4463e+00, -6.8736e+00,  2.2025e+01,\n",
      "        -1.4288e+01, -5.2826e+01,  7.0019e+00,  9.5541e+00, -1.3428e+01,\n",
      "        -5.9626e+00,  1.7771e+01, -4.0428e+01, -1.1869e+01, -1.0704e+01,\n",
      "        -1.4969e+01, -1.5804e+01, -3.1317e+01, -2.8195e+00, -7.5364e+00,\n",
      "        -2.4857e+01,  8.6698e-01, -1.1115e+01,  4.8792e+00, -1.7741e+01,\n",
      "         1.5789e+01,  2.9556e+00, -2.9081e+01, -1.1635e+01, -3.1450e+01,\n",
      "        -2.1588e+01, -3.3337e+01,  2.8547e+00, -2.2742e+01, -4.4550e+01,\n",
      "        -2.2864e+01,  2.6362e+00, -2.3102e+01, -2.6272e+01, -5.7939e+01,\n",
      "        -1.4245e+01,  1.5030e+01,  2.8121e+01, -1.9268e+01, -3.5677e+01,\n",
      "        -6.6290e+00, -2.6485e+01,  1.2587e+01, -5.1108e+01, -2.1856e+01,\n",
      "        -1.3056e+01, -3.8353e+01, -3.2483e+01, -3.6402e+01, -4.5172e+01,\n",
      "        -4.0701e+01, -4.5793e+01, -1.6491e+01, -2.7301e+01, -2.2757e+01,\n",
      "         4.4327e+00, -5.7813e+01, -6.2682e+01, -4.7242e+00, -1.1702e+01,\n",
      "         3.4871e+00,  2.5567e+01,  5.4541e+01,  4.7376e+01,  2.7267e+01,\n",
      "         2.7221e+01,  4.5370e+01,  1.2140e+01,  5.7178e+00, -8.7378e-01,\n",
      "         1.6824e+01,  2.1127e+01,  8.6520e+00,  3.9364e+01,  4.7337e+01,\n",
      "         6.7369e+01,  5.6313e+01,  8.4013e+01,  6.9090e+01,  2.5498e+01,\n",
      "         3.9701e+01,  1.5686e+01,  2.8079e+01,  2.1976e+01,  5.2006e+01,\n",
      "         5.8824e+01,  3.1192e+01,  5.4819e+01,  2.6232e+01,  4.5908e+01,\n",
      "         1.7860e+01,  4.2506e+01,  6.3351e+01,  5.4360e+01,  3.2270e+01,\n",
      "         5.1793e+01,  6.5389e+01,  4.1099e+01,  3.4290e+01,  7.1916e+01,\n",
      "         4.2822e+01,  5.2578e+01,  3.7933e+01,  8.5141e+01,  4.4162e+01,\n",
      "         8.2361e+01,  2.6309e+01,  6.2027e+00,  1.0398e+02,  8.9711e+01,\n",
      "         3.9076e+01,  1.2966e+01,  1.8782e+01,  3.5125e+01, -2.3359e+01,\n",
      "         5.9677e+01,  5.2722e+01,  3.5727e+01,  6.3539e+01,  3.8215e+01,\n",
      "         5.1591e+01,  2.1021e+01,  3.8418e+01,  3.9444e+01,  6.0276e+01,\n",
      "         6.2878e+01,  4.7283e+01,  2.1469e+01,  4.3664e+01, -2.0172e+01,\n",
      "         6.5248e+01,  5.6288e+01,  4.6432e+01,  6.4756e+01,  2.9661e+01,\n",
      "         4.4651e+00,  3.3115e+01,  7.0305e+01,  3.6752e+01,  3.5397e+01,\n",
      "         5.0515e+01,  3.3111e+01,  9.0902e+01,  1.6475e+01,  5.9315e+01,\n",
      "         7.7444e+01,  1.8997e+01,  4.7083e+01,  2.0926e+01,  3.9774e+01,\n",
      "         4.1876e+01,  8.7614e+01,  4.6987e+01,  5.1059e+01,  5.8501e+01,\n",
      "         4.1868e+01,  5.2489e+01,  5.5871e+01,  3.7904e+01,  5.1799e+01,\n",
      "         5.9866e+01,  3.5195e+01,  6.5543e+01,  2.0767e+01,  5.8192e+00,\n",
      "         8.6530e+01,  5.3641e+01,  3.4666e+01,  1.8715e+01, -7.9367e+00,\n",
      "         5.1824e+01,  4.3265e+01,  5.5845e+01,  3.5356e+01,  4.3346e+01,\n",
      "         2.4252e+01,  1.2920e+01,  2.8566e+01,  2.9918e+01,  1.3671e+01,\n",
      "         4.1091e+01,  3.6634e+01, -4.2944e+00,  4.4716e+01,  5.3828e+01,\n",
      "         6.7161e+00, -3.7858e+00, -1.8001e+01,  1.1931e+01,  2.7607e+01,\n",
      "         2.1170e+01, -3.4870e+01,  2.0377e+01, -2.5104e+01,  3.4798e+01,\n",
      "         1.5822e+01,  3.0157e+01, -2.3732e+01,  3.5177e+01, -4.7527e+00,\n",
      "        -1.8032e+01,  3.3267e+01,  2.9027e+01, -7.6858e+00,  1.1421e+01,\n",
      "         7.6238e+00,  3.3363e+01,  9.3996e+01, -4.1172e+01, -6.0408e+00,\n",
      "        -3.5155e+01, -1.8021e+01, -1.2951e+00, -1.0968e+01, -4.3550e+01,\n",
      "        -5.5822e+01, -1.8078e+01, -2.4318e+01, -2.8852e+01, -2.0510e+01,\n",
      "        -2.9436e+01, -3.6692e+01, -4.8433e+00, -5.6070e+01, -2.4980e+01,\n",
      "        -4.7286e+01, -3.6320e+01, -3.8975e+01, -3.4852e+01,  7.7203e+00,\n",
      "         1.9571e+01, -1.0401e+01, -2.1862e+01, -1.2440e+01,  4.1349e+00,\n",
      "        -1.5585e+01, -3.6649e+00, -1.3313e+01, -2.3706e+01, -2.8153e+01,\n",
      "        -7.7474e-01,  3.5745e+00,  1.3485e+01, -2.2623e+01,  1.8529e+01,\n",
      "         2.6235e+01, -2.9954e+01,  2.1760e+01,  2.3535e+01,  2.7773e+01,\n",
      "         1.2979e+01, -5.4077e+00,  7.5784e+00, -6.9819e+00,  2.8253e+01,\n",
      "         8.2485e+01, -3.9973e+01,  1.9595e+01, -3.4642e+00,  1.7987e+01,\n",
      "         3.2839e+01,  4.4665e+00, -1.9535e+01,  1.4190e+01,  6.8267e+01,\n",
      "         4.8946e+01, -2.7425e+01,  1.6767e+01, -3.8318e+00,  4.6046e+00,\n",
      "        -7.4502e+00,  2.9456e+01, -5.6213e+00, -1.0334e-01,  8.7438e+00,\n",
      "         3.0044e+01, -1.1726e+01, -4.4539e-01, -8.6358e+00,  1.1107e+01,\n",
      "         3.6346e+00,  3.1810e+01,  2.1473e+01,  1.1957e+01,  2.1626e+01,\n",
      "         2.0351e+01,  2.5009e+01, -1.3770e+01, -3.9697e+00,  1.6799e+01,\n",
      "         4.7222e+01,  2.2812e+00,  4.0509e+00, -6.7875e+00,  6.1361e+01,\n",
      "         1.4976e+01, -7.6827e+00,  7.6333e+00,  3.2122e+01, -2.1674e+01,\n",
      "        -2.9188e+01, -5.3673e-01,  8.6587e+00, -1.2959e+01,  4.3720e+00,\n",
      "        -1.1748e+01, -1.4994e+01, -6.8744e+00,  2.4047e+01,  1.5259e+01,\n",
      "        -9.9793e+00,  1.6112e+00,  4.0037e+01, -3.9943e+01, -3.7928e+01,\n",
      "        -1.6193e+01,  1.7833e+01,  3.0218e+01, -1.1861e+01,  1.1944e+02,\n",
      "        -5.8169e+00, -3.9065e+01, -5.9218e+01,  1.1078e+01, -9.0573e+00,\n",
      "        -4.3124e+01,  2.3193e+01, -4.1670e+01, -1.9087e+01,  4.4147e+01,\n",
      "         3.5375e+01, -5.9415e+00,  6.3861e+00, -2.9650e+01, -1.8859e+01,\n",
      "        -8.6887e+00,  1.2132e+02,  3.4924e+00, -6.4524e+01,  9.2237e+00,\n",
      "         2.2937e+01,  1.7154e+01, -2.9267e+01, -1.2238e+01, -4.9287e+01,\n",
      "        -5.8176e+01,  1.0962e+01,  7.8129e+00, -5.3737e+01, -2.7016e+01,\n",
      "        -4.7079e+00, -7.5618e+01,  1.3820e+00, -2.5927e+01, -1.2474e+01,\n",
      "        -3.2050e+01, -2.3899e+01,  3.9838e+01, -7.8141e+00, -2.1106e+01,\n",
      "        -1.6615e+01,  9.1685e+01, -3.3234e+01,  4.9965e+01, -5.1241e+01,\n",
      "         9.0566e+01, -7.6569e+00,  4.9950e+00, -3.0947e+01, -3.1951e+00,\n",
      "        -1.3074e+01, -4.8047e+00,  2.6288e+01,  1.7195e+01,  9.0588e+01,\n",
      "        -3.6162e+01, -5.4785e+01, -4.0937e+01,  1.9642e+01, -3.8350e+00,\n",
      "        -2.1465e+01, -5.1441e+00, -3.1363e+01, -3.2877e+01, -3.0014e+01,\n",
      "        -5.5025e+00, -3.0746e+01, -3.9012e+01, -5.1168e+01,  2.5486e+01,\n",
      "        -3.0879e+01,  3.7906e+01, -1.8724e+01, -2.1546e+01, -3.4095e+01,\n",
      "        -1.6507e+01, -2.7946e+00, -3.8388e+00,  9.8140e+01, -2.0290e+01,\n",
      "         3.4556e+00,  1.3258e+00, -3.1537e+01,  5.6430e+00,  6.2050e+01,\n",
      "         1.2022e+01, -4.3501e+00, -1.2630e+01, -5.8846e+00,  2.9107e+01,\n",
      "        -1.0782e+01,  1.1321e+01, -5.2448e+01,  8.2804e-02,  2.1543e+01,\n",
      "        -4.0379e+00,  6.0840e+00, -3.2172e+01,  1.5848e+00, -2.4789e+01,\n",
      "        -1.4507e+01, -9.8948e+00,  2.1794e+00, -3.1860e+01,  3.9636e+01,\n",
      "        -2.1743e+01, -3.6903e+01,  3.9649e+01, -1.5036e+01, -3.3425e+01,\n",
      "         1.4649e+01, -1.7809e+00, -1.8117e+01,  4.3937e+01, -3.0089e+01,\n",
      "        -2.2297e+01,  1.1177e+01, -4.5247e+00,  8.4464e+00, -2.5248e+01,\n",
      "         9.7637e+00,  1.9278e+01, -1.9932e+01, -5.1651e+01, -3.9697e+01,\n",
      "        -2.7780e+01, -2.6805e+01,  6.0272e+00,  4.2600e+01, -2.7920e+01,\n",
      "        -2.0016e+01, -6.4928e+00,  1.2638e+01,  4.4368e+01, -5.5339e+01,\n",
      "        -8.1936e+00,  1.5769e+01, -3.8383e+01, -1.3639e+01, -3.8904e+01,\n",
      "        -2.0362e+01,  4.7327e+00,  1.4214e+01, -4.5241e+00, -1.9906e+01,\n",
      "        -7.0221e+00, -5.6942e+00,  1.6665e+01,  1.6432e+01,  2.0902e+01,\n",
      "         3.4357e+01, -4.9761e+00,  3.2961e+01,  1.5337e+00, -4.2216e+01,\n",
      "        -2.2374e+01, -2.2161e+01,  5.4352e+00, -5.6862e+00, -1.1365e+01,\n",
      "         1.9827e+01, -4.6590e+01,  2.5964e+01, -1.2957e+01,  3.1015e+01,\n",
      "        -7.4889e+00, -4.8374e+01,  3.2151e+01, -3.0873e+01, -9.1530e+00,\n",
      "        -4.0331e+01,  9.0964e+00, -5.0909e+01,  5.8982e-01,  3.1959e+01,\n",
      "        -5.9466e+01, -1.1365e+01,  6.3629e+01, -1.4258e+01, -4.3049e+01,\n",
      "        -2.1868e+01, -5.6799e+01, -2.2266e+01,  4.1685e+00,  1.9057e+00,\n",
      "        -1.2197e+01,  9.2050e+01, -2.3026e+01, -2.9676e+01,  4.9569e+01,\n",
      "         1.2118e+02, -2.5378e+01, -1.4098e+01, -2.8484e+01,  6.4301e+01,\n",
      "        -2.0842e-01,  3.4570e+01, -1.8095e+01,  1.2099e+00,  8.0751e+00,\n",
      "        -3.5611e+01,  1.2121e+01, -4.2843e+01,  1.6779e+01, -3.6808e+01,\n",
      "        -7.0617e+00,  4.2841e+01,  6.6024e+00,  9.9449e+01,  1.4100e+01,\n",
      "        -1.8048e+01, -2.0557e+01, -1.0176e+01,  1.8480e+02, -5.5484e+01,\n",
      "        -2.3620e+01,  2.7940e+01, -1.4724e+01, -5.0291e+00,  5.5050e+00,\n",
      "        -3.1527e+01, -4.7543e+00,  4.8556e+01,  3.9927e+01, -5.3176e+01,\n",
      "         1.0361e+01, -2.6953e+01, -2.7929e+01, -1.0658e+01, -2.1410e+01,\n",
      "        -4.3713e+01,  2.9436e+01, -1.4936e+01,  1.7655e+01,  5.5347e+01,\n",
      "         2.0853e+01,  1.7424e+00, -2.0108e+01, -7.1467e+00,  5.2867e-01,\n",
      "        -4.3234e+01, -4.5620e+01,  1.5767e+01,  1.3692e+01,  5.5842e+00,\n",
      "        -1.9413e+00, -3.8106e+01, -2.1568e+00, -1.6107e+01, -2.9027e+01,\n",
      "        -4.7080e+01, -3.5639e+00, -4.0599e+01, -3.6208e+01, -9.3488e+00,\n",
      "        -6.0584e+01, -9.5654e-01, -6.5618e+00,  1.1408e+01, -1.1220e+01,\n",
      "        -1.6928e+00, -1.7051e+01, -1.0399e+01,  1.9577e+01,  2.5879e+01,\n",
      "        -1.7558e+01,  4.5411e+01,  5.7011e+01, -1.7610e+01,  1.4931e+02,\n",
      "        -1.9301e+00, -1.4201e+01,  2.2752e+01,  2.1812e+01, -9.4002e+00,\n",
      "        -1.6933e+01, -3.6416e+01, -3.8024e+01, -3.7284e+01, -9.6735e+01,\n",
      "        -2.4941e+01, -8.0883e+00, -2.1325e+01, -2.7353e+01, -3.6641e+01,\n",
      "        -2.0445e+01,  4.2053e+01,  7.5999e-01,  2.2973e+00,  2.5560e+01,\n",
      "         6.5422e+01, -2.4890e+01,  3.0126e+00, -4.1909e+01,  8.5550e+00,\n",
      "        -2.8599e+01, -2.9566e+01, -7.0468e+01, -1.4490e+01, -5.0377e+01,\n",
      "        -1.9233e+01, -3.0830e+01, -2.5701e+00, -1.5336e+01, -1.4642e+01,\n",
      "        -4.7829e+00, -1.7621e+01, -2.1916e-01, -1.2722e+01,  2.9288e+01,\n",
      "         1.6822e+01,  5.9312e-01,  3.3838e+01,  3.4479e+01, -4.5858e+01,\n",
      "        -2.5983e+01,  1.4339e+00,  4.4595e+01,  3.7895e+01, -2.1627e+01,\n",
      "        -4.3424e+01,  1.0692e+02, -2.0806e+01,  5.2959e+01, -1.0356e+01,\n",
      "        -1.1221e+01, -7.0531e+00,  3.0398e+01, -2.9477e+00, -2.3196e+01,\n",
      "         3.5764e+01, -5.0430e+01, -7.5902e+00, -1.0142e+01,  2.9394e+01,\n",
      "         6.1365e+01,  4.1641e+00,  3.4499e+01,  3.7904e+01,  8.5805e+01,\n",
      "         9.0101e+01,  7.0061e+00,  1.3168e+01, -4.2175e-01, -1.9471e+01,\n",
      "        -2.6332e+01, -2.8130e+01, -2.0056e+01, -1.8375e+01, -1.8056e+01,\n",
      "        -4.1432e+01,  8.4087e+00, -6.4610e+01,  1.3734e+00,  3.5405e+01,\n",
      "         1.6323e+01, -1.4167e+01,  1.6471e+00, -2.1123e+01, -1.2225e+01,\n",
      "        -3.9288e+01,  9.7528e-01, -1.2588e+01, -4.6440e+01, -4.1813e+01,\n",
      "        -2.6936e+01, -1.6856e+00,  2.4440e+01, -1.5732e+01, -7.9043e+00,\n",
      "        -5.5715e+01,  2.0593e+01, -4.3021e+01, -1.6885e+01, -1.6308e+01,\n",
      "        -1.3292e+01,  8.8489e+01,  4.6081e+00, -3.9470e+01, -2.9480e+01,\n",
      "        -4.6034e+01, -1.4267e+01,  1.5754e+01, -2.2639e+01, -2.2777e+01,\n",
      "         8.3326e+00,  1.9816e+01, -8.3543e+00,  8.0025e+00, -1.3207e+01,\n",
      "         1.5590e+01,  1.7850e+01, -1.1896e+01, -2.2181e+01,  2.1362e+00,\n",
      "         6.1035e+01, -1.3560e+01,  7.1693e+00, -4.3084e+00, -3.8665e+01,\n",
      "        -4.1526e+01, -1.3087e+01,  6.6755e+00,  1.2466e+01, -2.4768e+01,\n",
      "        -2.7349e+01,  7.4386e+00, -1.1259e+01,  3.0232e+01, -7.1800e+01,\n",
      "         1.4113e+01, -1.1756e+01, -2.4922e+01,  3.3631e+01, -4.4088e+01,\n",
      "         3.1629e+00,  7.1803e+00, -1.1633e+00,  3.1391e+01, -5.1716e+01,\n",
      "        -8.5452e+00,  2.8975e+01, -2.2679e+01, -2.6759e+01,  4.2189e+01,\n",
      "         9.2707e+00, -4.8849e+01, -9.0952e+00, -1.1483e+01, -4.4133e+01,\n",
      "         1.6755e-01, -4.5882e+01, -2.4937e-01,  7.8532e+00,  3.8985e+01,\n",
      "         3.7098e+01,  6.3676e+01,  1.8727e+01, -8.6247e+00, -5.3505e+00,\n",
      "         6.4824e+00,  4.3835e+01,  5.8602e+01, -1.7051e+01, -4.0397e+01,\n",
      "         2.0934e+01, -2.6906e+01, -4.4361e+01,  3.7342e+01,  1.1054e+01,\n",
      "        -6.4383e+01,  1.2933e+00, -2.2994e+01, -1.4803e+01, -7.0709e+00,\n",
      "        -8.4915e+01, -2.5600e+01, -8.4617e+00, -5.0248e+01, -1.6136e+00,\n",
      "        -4.5333e+01, -4.5590e+01,  2.0371e+01, -8.7989e+00,  1.1297e+01,\n",
      "         2.3037e+01,  1.6649e+01, -3.9139e+00,  2.4542e+01,  2.2315e+00,\n",
      "        -3.3965e+01,  1.4791e-02, -5.2000e+00,  2.1544e+01, -4.6242e+01,\n",
      "        -4.8996e+01, -3.6914e+01, -4.1631e+01, -2.8960e+01, -7.4641e+00,\n",
      "        -6.3156e+01, -9.5634e+00,  1.9398e+02,  8.5173e-01, -2.1570e+01,\n",
      "        -4.9791e+01, -4.2249e+01, -4.1160e+01,  3.4600e+01, -5.3331e+00,\n",
      "        -6.7386e-01, -5.0550e+01, -1.3525e+01, -1.2941e+01, -2.1062e+01,\n",
      "        -3.7267e+01, -3.3274e+00, -9.8780e-01, -3.8250e+01, -3.9710e+00,\n",
      "         8.5140e+01, -3.3322e+01, -4.0144e+00, -2.7482e+01, -3.2666e+01,\n",
      "        -7.1680e+00,  5.5156e+01, -1.2532e+01, -2.8467e+00, -1.5357e+01,\n",
      "        -7.7869e+00,  5.6264e+00, -1.2214e+01, -7.1989e+00, -2.5205e+01,\n",
      "        -1.9780e+01, -1.7911e+01, -1.9377e+01, -2.7755e-01,  2.6981e+01,\n",
      "         1.6181e+01, -3.0983e+01, -1.2970e+01, -2.9170e+01, -1.8488e+01,\n",
      "        -4.2313e+01, -2.9351e+01, -6.8647e+00, -1.9850e+01,  1.1587e+01,\n",
      "        -2.0410e+01, -4.2095e+01, -2.7931e+01, -2.5805e+01, -9.5033e+00,\n",
      "        -2.6607e+01, -1.5615e+01, -3.6512e+00,  6.6053e+00, -1.4018e+01,\n",
      "        -1.4889e+01, -2.4749e+00, -3.5100e+01, -1.8632e+00, -2.5041e+01,\n",
      "        -5.8570e+01, -1.5835e+01, -3.3617e+01, -3.9813e+01, -4.2570e+01,\n",
      "         2.9605e+01, -5.0111e+01, -2.4571e+01, -4.1218e+01, -3.9717e+01,\n",
      "        -1.7292e+01,  2.0963e+01, -7.6911e+00, -2.1001e+01, -1.0057e+01,\n",
      "        -2.1731e+01,  1.1596e+02, -2.1207e+01,  1.3177e+01,  2.1073e+01,\n",
      "        -3.3375e+01,  1.9787e+01, -4.5612e+01,  1.4566e+01, -3.9579e+00,\n",
      "        -3.4666e+01, -1.5623e+01,  1.3400e+01, -1.4822e+01,  3.0977e+00,\n",
      "         1.5115e+01,  1.5424e+00, -9.4860e+00, -9.3770e+00, -5.2511e+01,\n",
      "         1.5037e+00, -5.1975e+00, -3.3674e+01, -2.1091e+01, -1.0385e+01,\n",
      "        -7.0058e-01, -2.3876e+01, -2.3738e+01, -1.7120e+01,  4.4343e+00],\n",
      "       device='cuda:0', grad_fn=<ViewBackward0>)\n"
     ]
    }
   ],
   "source": [
    "fc_1000_fd = features['fc'].view(1000)\n",
    "\n",
    "print(fc_1000_fd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10, 10, 3, 3)\n",
      "(10, 10, 9)\n",
      "(1024,)\n",
      "(1024,)\n",
      "(1000,)\n"
     ]
    }
   ],
   "source": [
    "print(cm_fd.numpy().shape)\n",
    "print(hog_fd.numpy().shape)\n",
    "print(avgpool_1024_fd.detach().cpu().numpy().shape)\n",
    "print(layer3_1024_fd.detach().cpu().numpy().shape)\n",
    "print(fc_1000_fd.detach().cpu().numpy().shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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