Localization_Model_v0.1_demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "5Nbz2xj6UT42"
   },
   "source": [
    "On final dataset, using only labeled images ; Resnet18 -> Linear"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "_FsPlBygKHxW"
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from torch.utils.data import Dataset\n",
    "from torch.optim import lr_scheduler\n",
    "from torchvision import datasets, models, transforms\n",
    "from PIL import Image # pip3 install pillow\n",
    "import random\n",
    "import cv2\n",
    "import time\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 153
    },
    "colab_type": "code",
    "id": "1RC2tw5lKHxb",
    "outputId": "3d30ea49-59c9-4304-fb66-fb6bff16c1ef"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>image</th>\n",
       "      <th>points</th>\n",
       "      <th>labeled</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>data/dactar/1300_img.png</td>\n",
       "      <td>[177.16228095049055, 184.83182101741053, 244.7...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>data/dactar/1766_img.png</td>\n",
       "      <td>[409.7109787838158, 362.74050003943523, 536.55...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>data/dactar/130_img.png</td>\n",
       "      <td>[386.66894459252546, 342.1963080587535, 503.59...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>data/dactar/1785_img.png</td>\n",
       "      <td>[197.75577726950075, 171.98786970581278, 250.1...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>data/dactar/617_img.png</td>\n",
       "      <td>[180.14505945291972, 298.14972872833135, 288.5...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      image  \\\n",
       "0  data/dactar/1300_img.png   \n",
       "1  data/dactar/1766_img.png   \n",
       "2   data/dactar/130_img.png   \n",
       "3  data/dactar/1785_img.png   \n",
       "4   data/dactar/617_img.png   \n",
       "\n",
       "                                              points  labeled  \n",
       "0  [177.16228095049055, 184.83182101741053, 244.7...        1  \n",
       "1  [409.7109787838158, 362.74050003943523, 536.55...        1  \n",
       "2  [386.66894459252546, 342.1963080587535, 503.59...        1  \n",
       "3  [197.75577726950075, 171.98786970581278, 250.1...        1  \n",
       "4  [180.14505945291972, 298.14972872833135, 288.5...        1  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_pickle(\"data/dataset.pkl\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(80, 'test/dactar/302_img.png')"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_folder = \"test/\"\n",
    "imlist = []\n",
    "for (dirpath, dirnames, filenames) in os.walk(img_folder):\n",
    "#     imlist.extend(filenames)\n",
    "    imlist.extend([os.path.join(dirpath, filename) for filename in filenames])\n",
    "\n",
    "# imlist =[f for f in os.listdir(img_folder) \n",
    "#          if os.path.isfile(os.path.join(img_folder, f))]\n",
    "len(imlist), imlist[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "80 80\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>image</th>\n",
       "      <th>points</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>test/dactar/302_img.png</td>\n",
       "      <td>[311.5482687909141, 263.43743197413045, 412.96...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>test/dactar/643_img.png</td>\n",
       "      <td>[200.52462157335316, 178.39022592894423, 270.9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>test/dactar/4_img.png</td>\n",
       "      <td>[731.6394153243285, 558.4904461359735, 881.935...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>test/dactar/833_img.png</td>\n",
       "      <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>test/dactar/246_img.png</td>\n",
       "      <td>[159.01733886166608, 167.15541582428125, 239.7...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     image                                             points\n",
       "0  test/dactar/302_img.png  [311.5482687909141, 263.43743197413045, 412.96...\n",
       "1  test/dactar/643_img.png  [200.52462157335316, 178.39022592894423, 270.9...\n",
       "2    test/dactar/4_img.png  [731.6394153243285, 558.4904461359735, 881.935...\n",
       "3  test/dactar/833_img.png           [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\n",
       "4  test/dactar/246_img.png  [159.01733886166608, 167.15541582428125, 239.7..."
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_list = []\n",
    "all_imgs = [imgname.replace(\"data\",\"test\") for imgname in df.image.tolist()]\n",
    "for img in imlist:\n",
    "    try:\n",
    "        indx = all_imgs.index(img)\n",
    "        tokeep.append(indx)\n",
    "#         data_list.append([df.iloc[indx].image, df.iloc[indx].points])\n",
    "#         data_list.append([os.path.join(img_folder, df.iloc[indx].image.split('/')[-1]), df.iloc[indx].points])\n",
    "        data_list.append([all_imgs[indx], df.iloc[indx].points])\n",
    "\n",
    "    except ValueError as e:\n",
    "        continue\n",
    "df_test = pd.DataFrame(data=data_list, columns=[\"image\", \"points\"])\n",
    "print(len(imlist), len(df_test))\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_test1 = df.iloc[tokeep].reset_index()\n",
    "# df_test = df_test1.copy()\n",
    "# df_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# all_imgs = [os.path.join(img_folder, imgname.split('/')[-1]) for imgname in df_test.image.tolist()]\n",
    "# df_test1 = df_test.drop(columns=['image'])\n",
    "# df_test1['image'] = all_imgs\n",
    "# df_test1 = df_test1[[\"image\", \"points\"]]\n",
    "# df_test1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test/jeevan/571_img.png [136.06358885 219.09233449 220.85452962 214.23170732 220.85452962\n",
      " 235.29442509 136.06358885 240.15505226]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fa5baf2d198>]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# i=-1\n",
    "i+=1\n",
    "path, targ = df_test.iloc[i].image, df_test.iloc[i].points\n",
    "print(path, targ)\n",
    "img = Image.open(path).convert('RGB')\n",
    "\n",
    "targ = np.append(targ, targ[:2]).reshape(-1,2)\n",
    "# targ = targ.reshape(-1,2)\n",
    "plt.figure(figsize=(8, 8))\n",
    "plt.imshow(img)\n",
    "plt.plot(targ[:,0], targ[:,1], lw=3, c='g')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "5-mKB_zRKHxo"
   },
   "source": [
    "### Image Transform"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "3Xe7PAzKKHxo"
   },
   "outputs": [],
   "source": [
    "class ResizeAspect(object):\n",
    "    def __init__(self, h, w):\n",
    "        self.hw = (h, w)\n",
    "        self.rescale_factor=None\n",
    "        self.shift_h=None\n",
    "        self.shift_w=None\n",
    "        \n",
    "    def do_image(self, img):\n",
    "        h, w = self.hw\n",
    "        img_h, img_w = img.shape[0], img.shape[1]\n",
    "        rescale_factor = min(w/img_w, h/img_h)\n",
    "        new_w = int(img_w * rescale_factor)\n",
    "        new_h = int(img_h * rescale_factor)\n",
    "        resized_image = cv2.resize(img, (new_w,new_h), interpolation = cv2.INTER_CUBIC)\n",
    "\n",
    "        canvas = np.full((h, w, 3), 128, dtype=np.uint8)\n",
    "        shift_h = (h-new_h)//2\n",
    "        shift_w = (w-new_w)//2\n",
    "        canvas[(h-new_h)//2:(h-new_h)//2 + new_h,(w-new_w)//2:(w-new_w)//2 + new_w,  :] = resized_image\n",
    "        img = canvas.copy()\n",
    "        self.rescale_factor=rescale_factor\n",
    "        self.shift_h = shift_h\n",
    "        self.shift_w = shift_w\n",
    "        return img\n",
    "    \n",
    "    def do_box(self, box):\n",
    "        box = box.reshape(-1,2)\n",
    "        box *=self.rescale_factor\n",
    "        box[: ,0] += self.shift_w\n",
    "        box[: ,1] += self.shift_h\n",
    "        box = box.reshape(-1)\n",
    "        return box\n",
    "    \n",
    "    def undo_box(self, box):\n",
    "        box = box.reshape(-1,2)\n",
    "        box[: ,0] -= self.shift_w\n",
    "        box[: ,1] -= self.shift_h\n",
    "        box /=self.rescale_factor\n",
    "        box = box.reshape(-1)\n",
    "        return box"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "9szOaV5wKHxs"
   },
   "outputs": [],
   "source": [
    "class FinalTransform:\n",
    "    def __init__(self):\n",
    "        self.transform = transforms.Compose([\n",
    "            transforms.ToTensor(),\n",
    "            transforms.Normalize(mean=[0.485, 0.456, 0.406],\n",
    "                                 std=[0.229, 0.224, 0.225])])\n",
    "    \n",
    "    def transform_inv(self,img):\n",
    "        inp = img.numpy().transpose((1, 2, 0))\n",
    "        mean = np.array([0.485, 0.456, 0.406])\n",
    "        std = np.array([0.229, 0.224, 0.225])\n",
    "        inp = std * inp + mean\n",
    "        inp = np.clip(inp, 0, 1)\n",
    "        return inp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "niEfDCspKHxv"
   },
   "source": [
    "### Dataset Loader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Jsd-VuCkKHxv"
   },
   "outputs": [],
   "source": [
    "class LicenseDataset(Dataset):\n",
    "    def __init__(self, df):\n",
    "        \n",
    "        self.imgs = list(df.image)\n",
    "        self.boxes = df.points.tolist()\n",
    "        self.final_transform = FinalTransform()\n",
    "        self.transform = self.final_transform.transform\n",
    "        self.transform_inv = self.final_transform.transform_inv\n",
    "        self.resizer = ResizeAspect(h=224, w=224)\n",
    "            \n",
    "    def __getitem__(self, index):\n",
    "        path= self.imgs[index]\n",
    "        box = self.boxes[index]\n",
    "        \n",
    "        \n",
    "        img = Image.open(path).convert('RGB')\n",
    "        img = self.resizer.do_image(np.array(img))\n",
    "        img = self.final_transform.transform(img)\n",
    "        box = self.resizer.do_box(box)\n",
    "        box = np.array(box, dtype=np.float32)\n",
    "\n",
    "        factor = np.array(\n",
    "            [self.resizer.rescale_factor, self.resizer.shift_h, self.resizer.shift_w],\n",
    "            dtype=np.float32\n",
    "        )\n",
    "        return img, box, factor, index\n",
    "      \n",
    "    \n",
    "    def __len__(self):\n",
    "        return len(self.imgs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Q__KgwU1KHyB"
   },
   "outputs": [],
   "source": [
    "test = LicenseDataset(df_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "jKrQ6UJlKHyI"
   },
   "outputs": [],
   "source": [
    "test_loader = torch.utils.data.DataLoader(\n",
    "                test, batch_size=32,shuffle=False,\n",
    "                num_workers=4, pin_memory=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "LpduTwnOKHyL"
   },
   "source": [
    "### Defining Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "48sFrjXrKHyL"
   },
   "outputs": [],
   "source": [
    "model = models.resnet18(pretrained=True)\n",
    "'''\n",
    "output of our model is :\n",
    "x1, y1,\n",
    "x2, y2,\n",
    "x3, y3,\n",
    "x4, y4,\n",
    "conf -> only when no bounding box images are taken\n",
    "'''\n",
    "num_feature = model.fc.in_features\n",
    "num_output = 8#9\n",
    "model.fc = nn.Linear(num_feature, num_output)\n",
    "model = model.cpu()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "XczjvxsXKHyU"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "IncompatibleKeys(missing_keys=[], unexpected_keys=[])"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.load_state_dict(torch.load('saved_states/model_state_v0.pth', map_location='cpu'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "aRB_bJN6U7Z0",
    "outputId": "500da7d5-7089-444c-90dd-7d788dc457a6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Working in test mode\n"
     ]
    }
   ],
   "source": [
    "test_batch = 0\n",
    "indx = -1\n",
    "model.eval()\n",
    "print('Working in test mode')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 503
    },
    "colab_type": "code",
    "id": "1i-BSsbTTfuW",
    "outputId": "bd7bb399-5891-4490-98c5-ad5b02964ab0"
   },
   "outputs": [],
   "source": [
    "# if indx < 0:\n",
    "#     for j,(ims, boxes, factors, index) in enumerate(test_loader):\n",
    "#         if j<test_batch:\n",
    "#             continue\n",
    "#         index = index.cpu().numpy()\n",
    "#         inputs = ims.cpu()\n",
    "#         targets = boxes.cpu().numpy()\n",
    "#         factors = factors.cpu().numpy()\n",
    "#         outputs = model(inputs)\n",
    "#         outputs = outputs.data.cpu().numpy()\n",
    "#         test_batch +=1\n",
    "#         break\n",
    "    \n",
    "# indx +=1\n",
    "# loader_indx = index[indx]\n",
    "# factor = factors[indx]\n",
    "# resizer = test.resizer\n",
    "\n",
    "\n",
    "# path= test.imgs[loader_indx]\n",
    "# img = Image.open(path).convert('RGB')\n",
    "# resizer.rescale_factor=factor[0]\n",
    "# resizer.shift_h=factor[1]\n",
    "# resizer.shift_w=factor[2]\n",
    "\n",
    "\n",
    "# targ = test.boxes[loader_indx]\n",
    "# targ = np.append(targ, targ[:2]).reshape(-1,2)\n",
    "\n",
    "# out = outputs[indx]\n",
    "# # print(out)\n",
    "# # print(resizer, resizer.rescale_factor, resizer.shift_h, resizer.shift_w)\n",
    "# out = resizer.undo_box(out)\n",
    "# out = np.append(out, out[:2]).reshape(-1,2)\n",
    "\n",
    "# plt.figure(figsize=(8, 8))\n",
    "# plt.imshow(img)\n",
    "# plt.plot(targ[:,0], targ[:,1], lw=3, c='g')\n",
    "# plt.plot(out[:,0], out[:,1], lw=3, c='r')\n",
    "# print(indx)\n",
    "# if indx == 31:\n",
    "#     indx = -1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "jC0m718jgs_F"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tsuman/Program_Files/miniconda3.7/lib/python3.7/site-packages/matplotlib/pyplot.py:514: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
      "  max_open_warning, RuntimeWarning)\n"
     ]
    },
    {
     "data": {
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     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<Figure size 576x576 with 0 Axes>"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<Figure size 576x576 with 0 Axes>"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 576x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 576x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 576x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 576x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 576x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 576x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 576x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "resizer = test.resizer\n",
    "for j,(ims, boxes, factors, index) in enumerate(test_loader):\n",
    "\n",
    "    index = index.cpu().numpy()\n",
    "    inputs = ims.cpu()\n",
    "    targets = boxes.cpu().numpy()\n",
    "    factors = factors.cpu().numpy()\n",
    "    outputs = model(inputs)\n",
    "    outputs = outputs.data.cpu().numpy()\n",
    "\n",
    "    for indx in range(len(outputs)):\n",
    "        loader_indx = index[indx]\n",
    "        factor = factors[indx]\n",
    "\n",
    "        path= test.imgs[loader_indx]\n",
    "        img = Image.open(path).convert('RGB')\n",
    "        resizer.rescale_factor=factor[0]\n",
    "        resizer.shift_h=factor[1]\n",
    "        resizer.shift_w=factor[2]\n",
    "\n",
    "        targ = test.boxes[loader_indx]\n",
    "        targ = np.append(targ, targ[:2]).reshape(-1,2)\n",
    "\n",
    "        out = outputs[indx]\n",
    "        out = resizer.undo_box(out)\n",
    "        out = np.append(out, out[:2]).reshape(-1,2)\n",
    "\n",
    "        plt.figure(figsize=(8, 8))\n",
    "        plt.imshow(img)\n",
    "        plt.plot(targ[:,0], targ[:,1], lw=3, c='g')\n",
    "        plt.plot(out[:,0], out[:,1], lw=3, c='r')\n",
    "        plt.savefig(\"pred_\"+path)\n",
    "        plt.clf()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "QZDh9D0UOFG2"
   },
   "outputs": [],
   "source": []
  }
 ],
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   "name": "Localization_Model_v0.ipynb",
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