test_model_balanced.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from src.thickness_dataset import ThicknessDataset, ToTensor\n",
    "from src.models import U_Net\n",
    "from src.trainer import Trainer\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import torch\n",
    "from torch.utils.data import DataLoader\n",
    "from torch import nn\n",
    "from tqdm import tqdm\n",
    "\n",
    "import albumentations as A\n",
    "from albumentations.pytorch import ToTensorV2\n",
    "\n",
    "PATH = \"data\\gen_data_6000_v2\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 52/52 [00:26<00:00,  1.95it/s]\n"
     ]
    }
   ],
   "source": [
    "augs = A.Compose([A.Normalize(mean = (0, 0, 0),\n",
    "                              std  = (1, 1, 1)),\n",
    "                 ToTensorV2()])\n",
    "thickness_dataset = ThicknessDataset(PATH, transform=augs)\n",
    "\n",
    "# Calculate mean and std\n",
    "image_loader = DataLoader(thickness_dataset, \n",
    "                          batch_size  = 128, \n",
    "                          shuffle     = False, \n",
    "                          num_workers = 4,\n",
    "                          pin_memory  = True)\n",
    "\n",
    "# placeholders\n",
    "psum    = torch.tensor([0.0, 0.0, 0.0])\n",
    "psum_sq = torch.tensor([0.0, 0.0, 0.0])\n",
    "\n",
    "# loop through images\n",
    "for inputs in tqdm(image_loader):\n",
    "    psum    += inputs['img'].sum(axis        = [0, 2, 3])\n",
    "    psum_sq += (inputs['img'] ** 2).sum(axis = [0, 2, 3])\n",
    "\n",
    "# pixel count\n",
    "count = len(thickness_dataset) * 128 * 128\n",
    "\n",
    "# mean and std\n",
    "total_mean = psum / count\n",
    "total_var  = (psum_sq / count) - (total_mean ** 2)\n",
    "total_std  = torch.sqrt(total_var)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch.utils.data import DataLoader, Subset\n",
    "\n",
    "def customRandomSplit(dataset, train_size, val_size, test_size):\n",
    "    # TODO: DONT think its adding in the indices +1 and +2 need to add that to all the indices arrays\n",
    "    rnd_Seed=42\n",
    "    mandatory_test_models = [\"88d183f319cddb7344221bef0fa3c36b\",\"ce40b134b11e8c822bbc2c380e91dfe2\",\"67bc9bec05f78850f9e08161aea27d2f\",\"ba494b33be3a3e0dc1bbb501b1d87871\",\"15cc3d9020384e8d6e09a8e31c7575c5\",\"bc6a3fa659dd7ec0c62ac18334863d36\",\"46dbba829a57ace8cffd61677456447e\",\"1d527bbed4d12817fa3bb91f4e3cd35f\",\"f400eb5421283e8a102f4912aece242b\",\"899af991203577f019790c8746d79a6f\"]\n",
    "    data_len = len(dataset)\n",
    "    train_size = int(round((train_size * data_len)/3))\n",
    "    val_size   = int(round((val_size * data_len)/3))\n",
    "    test_size  = int(round((test_size * data_len)/3))\n",
    "\n",
    "    assert train_size*3 + val_size*3 + test_size*3 == data_len, \"The split sizes do not add up to the dataset size\"\n",
    "    # Using pytorch subsets to split the dataset\n",
    "    # 3 is the number of frames per model\n",
    "    # randomly sample indices for the train size\n",
    "    choices = np.arange(0, data_len, 3, dtype=int)\n",
    "    # get the index numbers for the mandatory test models from dataset dataframe\n",
    "    mandatory_test_indices = []\n",
    "    for i in range(len(mandatory_test_models)):\n",
    "        mandatory_test_indices.append(dataset.dataframe[dataset.dataframe[\"model_id\"] == mandatory_test_models[i]].index[0])\n",
    "    mandatory_test_indices = np.array(np.array(mandatory_test_indices), dtype=int)\n",
    "    # remove the values in mandatory_test_indices from the choices\n",
    "    choices = np.setdiff1d(choices, mandatory_test_indices)\n",
    "    \n",
    "    np.random.seed(rnd_Seed)\n",
    "    np.random.shuffle(choices)\n",
    "    # randomly sample indices for the train size\n",
    "    train_indices = choices[:train_size]\n",
    "    # randomly sample indices for the val size\n",
    "    val_indices = choices[train_size:train_size+val_size]\n",
    "    # randomly sample indices for the test size\n",
    "    test_indices = choices[train_size+val_size:train_size+val_size+test_size]\n",
    "    # add the mandatory test indices to the test indices\n",
    "    test_indices = np.concatenate((test_indices, mandatory_test_indices))\n",
    "    # final check the values in mandatory_test_indices are in test_indices\n",
    "    assert np.all(np.isin(mandatory_test_indices, test_indices)), \"The mandatory test indices are not in the test indices\"\n",
    "    # check mandatory_test_indices values arent in the other 2\n",
    "    assert np.all(np.isin(mandatory_test_indices, train_indices)) == False, \"The mandatory test indices are in the train indices\"\n",
    "    assert np.all(np.isin(mandatory_test_indices, val_indices)) == False, \"The mandatory test indices are in the val indices\"\n",
    "\n",
    "\n",
    "    train_indices = np.concatenate((train_indices, train_indices+1, train_indices+2))\n",
    "    val_indices = np.concatenate((val_indices, val_indices+1, val_indices+2))\n",
    "    test_indices = np.concatenate((test_indices, test_indices+1, test_indices+2))\n",
    "    # no intersections between the sets\n",
    "    it = np.intersect1d(train_indices, val_indices)\n",
    "    it2 = np.intersect1d(train_indices, test_indices)\n",
    "    it3 = np.intersect1d(val_indices, test_indices)\n",
    "    assert len(it) == 0 , f\"The train and val sets have the same indices {it}\"\n",
    "    assert len(it2) == 0 , f\"The train and test sets have the same indices {it2}\"\n",
    "    assert len(it3) == 0 , f\"The val and test sets have the same indices{it3}\"\n",
    "    \n",
    "    # create the subsets\n",
    "    train_set = Subset(dataset, train_indices)\n",
    "    val_set   = Subset(dataset, val_indices,)\n",
    "    test_set  = Subset(dataset, test_indices)\n",
    "    assert len(train_set) + len(val_set) + len(test_set) == data_len, \"The split sizes do not add up to the dataset size\"\n",
    "    return train_set, val_set, test_set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# of samples in train set: 4587\n",
      "# of samples in validation set: 654\n",
      "# of samples in test set: 1311\n"
     ]
    }
   ],
   "source": [
    "train_split = 0.7\n",
    "valid_split = 0.1\n",
    "test_split = 0.2\n",
    "\n",
    "augs = A.Compose([A.Normalize(mean = total_mean,\n",
    "                              std  = total_std),\n",
    "                 ToTensorV2()])\n",
    "thickness_dataset = ThicknessDataset(PATH, transform=augs)\n",
    "\n",
    "train_dataset, valid_dataset, test_dataset = customRandomSplit(thickness_dataset, train_split, valid_split, test_split)\n",
    "\n",
    "batch_size = 16\n",
    "\n",
    "train_dataloader = DataLoader(train_dataset, batch_size=batch_size)\n",
    "valid_dataloader = DataLoader(valid_dataset, batch_size=batch_size)\n",
    "test_dataloader = DataLoader(test_dataset, batch_size=128)\n",
    "print (\"# of samples in train set:\", len(train_dataset))\n",
    "print(\"# of samples in validation set:\", len(valid_dataset))\n",
    "print(\"# of samples in test set:\", len(test_dataset))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using cuda device\n"
     ]
    }
   ],
   "source": [
    "# 85 and 107 148are also intersting epochs\n",
    "# path = f\"models\\Full train (balanced)\\model_20230329-155809_148\" \n",
    "# path = \"models\\Full train (balanced)\\model_20230329-155809_85\"\n",
    "path = \"models\\Full train (balanced)\\model_20230329-155809_107\" # best model\n",
    "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
    "print(\"Using {} device\".format(device))\n",
    "\n",
    "model = U_Net()\n",
    "\n",
    "criterion = nn.MSELoss()\n",
    "model = model.to(device)\n",
    "model.load_state_dict(torch.load(path))\n",
    "model.eval()\n",
    "trained_model = model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test MSE loss: 0.000930786762513559\n",
      "Test MMSE loss: 0.007023253478109837\n",
      "Test MMSE loss with extras: 0.007023253478109837\n"
     ]
    }
   ],
   "source": [
    "# Get the masked loss for the test set quantative evaluation \n",
    "# https://torchmetrics.readthedocs.io/en/stable/image/peak_signal_noise_ratio.html\n",
    "from skimage.metrics import structural_similarity as ssim\n",
    "from src.evaluation import mse_loss_with_nans, mse_loss_with_nans_with_extras\n",
    "mse_full_loss = 0\n",
    "mmse_full_loss = 0\n",
    "mmse_full_loss_extr = 0\n",
    "\n",
    "batches = 0\n",
    "catagory_losses = {}\n",
    "catagory_index = {} # appends tuple to list that stores as batch_no, idx in batch\n",
    "\n",
    "loss_fn = torch.nn.MSELoss()\n",
    "with torch.no_grad():\n",
    "    for data in test_dataloader:\n",
    "        images, labels = data['img'].to(device, dtype=torch.float), data['thick_map'].to(device, dtype=torch.float)\n",
    "        catagory_id = data['catagory_id']\n",
    "        outputs = trained_model(images)\n",
    "\n",
    "        mse_loss = loss_fn(outputs, labels)\n",
    "        masked_lossv0 = mse_loss_with_nans(outputs, labels)\n",
    "        masked_lossv1, losses = mse_loss_with_nans_with_extras(outputs, labels)\n",
    "        # using the catagory id to keep adding the loss to the scores\n",
    "        for i in range(losses.shape[0]):\n",
    "            if catagory_id[i] in catagory_losses:\n",
    "                catagory_losses[catagory_id[i]].append(losses[i].cpu().numpy())\n",
    "                catagory_index[catagory_id[i]].append((batches, i))\n",
    "                \n",
    "            else:\n",
    "                catagory_losses[catagory_id[i]] = [losses[i].cpu().numpy()]\n",
    "                catagory_index[catagory_id[i]] = [(batches, i)]\n",
    "\n",
    "        mse_full_loss += mse_loss.item()\n",
    "        mmse_full_loss += masked_lossv0\n",
    "        mmse_full_loss_extr += masked_lossv1\n",
    "        batches += 1\n",
    "print(\"Test MSE loss: {}\".format(mse_full_loss/batches))\n",
    "print(\"Test MMSE loss: {}\".format(mmse_full_loss/batches))\n",
    "print(\"Test MMSE loss with extras: {}\".format(mmse_full_loss_extr/batches))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# for each catagory calculate the mean then plot a bar graph of the mean loss of each catagory\n",
    "catagory_mean_losses = {}\n",
    "for catagory in catagory_losses:\n",
    "    catagory_mean_losses[catagory] = np.mean(catagory_losses[catagory])\n",
    "catagory_lens = {}\n",
    "for catagory in catagory_losses:\n",
    "    catagory_lens[catagory] = len(catagory_losses[catagory])\n",
    "\n",
    "\n",
    "\n",
    "# catagory_mean_losses sorted by the mean loss\n",
    "catagory_mean_losses = {k: v for k, v in sorted(catagory_mean_losses.items(), key=lambda item: item[1])}\n",
    "\n",
    "fig = plt.figure(figsize=(10, 5))\n",
    "plt.title(\"Full Test Set: Masked Mean loss of each category\")\n",
    "plt.xlabel(\"Category Names\")\n",
    "plt.ylabel(\"Mean of Masked loss\")\n",
    "    # change the xticks rotate the labels 90 degrees\n",
    "plt.bar(catagory_mean_losses.keys(), catagory_mean_losses.values())\n",
    "plt.xticks(rotation=90)\n",
    "# using thickness_dataset.labels to get the catagory name strings for the xticks\n",
    "plt.xticks(list(catagory_mean_losses.keys()), [thickness_dataset.labels[i].split(',')[0].capitalize() for i in catagory_mean_losses.keys()])\n",
    "\n",
    "\n",
    "plt.show()\n",
    "# save as pdf\n",
    "fig.savefig(\"figs\\\\full\\\\mean_loss_of_each_catagory.pdf\", bbox_inches='tight')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The sum of the mean losses of each category is: 0.00022243146510570274\n"
     ]
    }
   ],
   "source": [
    "# catagory_mean_losses.values() sumthem\n",
    "print(\"The sum of the mean losses of each category is: {}\".format(sum(catagory_mean_losses.values())/1311))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot count of each catgory, sorted by the acending mean loss dict\n",
    "# catagory_lens sorted by the mean loss dictionary catagory_mean_losses\n",
    "\n",
    "catagory_lens = {k: v for k, v in sorted(catagory_lens.items(), key=lambda item: catagory_mean_losses[item[0]])}\n",
    "\n",
    "fig = plt.figure(figsize=(10, 5))\n",
    "plt.title(\"Full Test Set: Count of each category\")\n",
    "plt.xlabel(\"Category Names\")\n",
    "plt.ylabel(\"Count of samples\")\n",
    "\n",
    "plt.bar(catagory_lens.keys(), catagory_lens.values())\n",
    "plt.xticks(rotation=90)\n",
    "# using thickness_dataset.labels to get the catagory name strings for the xticks\n",
    "plt.xticks(list(catagory_lens.keys()), [thickness_dataset.labels[i].split(',')[0].capitalize() for i in catagory_lens.keys()])\n",
    "plt.show()\n",
    "# save as pdf\n",
    "fig.savefig(\"figs\\\\full\\\\count_of_each_catagory.pdf\", bbox_inches='tight')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The sum of the count of each catagory is: 1311\n"
     ]
    }
   ],
   "source": [
    "# catagory_lens.values() sumthem\n",
    "print(\"The sum of the count of each catagory is: {}\".format(sum(catagory_lens.values())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Structure Simililarity:  0.9874034006327783\n"
     ]
    }
   ],
   "source": [
    "import cv2\n",
    "from mpl_toolkits.axes_grid1 import ImageGrid\n",
    "id = \"03691459\"\n",
    "num = 15\n",
    "# locator \n",
    "batch_no, sample_no =catagory_index[id][num]\n",
    "iters = 0\n",
    "with torch.no_grad():\n",
    "    for data in test_dataloader:\n",
    "        samples = data\n",
    "        images, labels = data['img'].to(device, dtype=torch.float), data['thick_map'].to(device, dtype=torch.float)\n",
    "        image_locs = data['img_loc']\n",
    "        outputs = trained_model(images)\n",
    "        if iters == batch_no:\n",
    "            for i in range(outputs.shape[0]):\n",
    "                if i == sample_no:\n",
    "                    img_loc = image_locs[i]\n",
    "\n",
    "                    fig = plt.figure(figsize=(12,8))\n",
    "                    grid = ImageGrid(fig, 111,\n",
    "                                     nrows_ncols = (1,3),\n",
    "                                     axes_pad = .5,\n",
    "                                     cbar_location = \"right\",\n",
    "                                     cbar_mode=\"each\",\n",
    "                                     cbar_size=\"5%\",\n",
    "                                     cbar_pad=0.1,\n",
    "                                    )\n",
    "\n",
    "                    im1 = grid[0].imshow(cv2.cvtColor(cv2.imread(img_loc), cv2.COLOR_BGR2RGB), aspect=\"equal\")\n",
    "                    grid[0].set_title('Input Image')\n",
    "                    grid[0].axis('off')\n",
    "                    grid.cbar_axes[0].colorbar(im1)\n",
    "                    grid.cbar_axes[0].toggle_label(True)\n",
    "                    im2 = grid[1].imshow(labels[i].cpu().numpy()[0], cmap='plasma')\n",
    "                    grid[1].set_title('Ground Truth')\n",
    "                    grid[1].axis('off')\n",
    "                    grid.cbar_axes[1].colorbar(im2)\n",
    "                    im3= grid[2].imshow(outputs[i].cpu().numpy()[0], cmap='plasma')\n",
    "                    grid[2].set_title('Predicted Thickness Map')\n",
    "                    grid[2].axis('off')\n",
    "                    grid.cbar_axes[2].colorbar(im3)\n",
    "                    fig.suptitle(f\"{thickness_dataset.labels[id].split(',')[0].capitalize()} Sample {num}\", fontsize=16,y=0.75, fontweight = \"600\")\n",
    "                    plt.show()\n",
    "                    fig.savefig(\"figs\\\\full\\\\sample_{}_from_catagory_{}.pdf\".format(num, data['catagory_id'][i]), bbox_inches='tight')\n",
    "                    print(\"Structure Simililarity: \",ssim(labels[i].cpu().numpy()[0], outputs[i].cpu().numpy()[0].reshape(128,128)))\n",
    "                    break\n",
    "            break\n",
    "        iters +=1"
   ]
  }
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