30_subcoco_frcnn_lightning.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# default_exp subcoco_frcnn_lightning\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploring Object Detection using Faster RCNN and Pytorch Lightning\n",
    "\n",
    "Instead of using higher level library such as IceVision, I am gonna try using what's in Torch Vision, see [example](https://pytorch.org/tutorials/intermediate/torchvision_tutorial.html).\n",
    "\n",
    "To force some learning, I shall attempt to port the example to [Pytorch-Lightning](https://github.com/PyTorchLightning/pytorch-lightning) as it removes a lot of boiler plate code and standardized Pytorch usage. It also makes advanced features like gradient accumulation and multi-GPU multi-node training simple."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#export\n",
    "import json, os, requests, sys, tarfile\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.colors as mcolors\n",
    "import numpy as np\n",
    "import pickle\n",
    "import random\n",
    "\n",
    "from collections import defaultdict\n",
    "from functools import reduce\n",
    "from IPython.utils import io\n",
    "from pathlib import Path\n",
    "from PIL import Image\n",
    "from PIL import ImageStat\n",
    "\n",
    "from pycocotools.coco import COCO\n",
    "from pycocotools.cocoeval import COCOeval\n",
    "from tqdm import tqdm\n",
    "from typing import Hashable, List, Tuple, Union"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Current Directory is now /home/brian/Projects/mcbbox\n"
     ]
    }
   ],
   "source": [
    "#hide\n",
    "\n",
    "IN_COLAB = 'google.colab' in sys.modules\n",
    "\n",
    "if IN_COLAB:\n",
    "    from google.colab import drive\n",
    "    drive.mount('/content/drive/', force_remount=True)\n",
    "    os.chdir('/content/drive/My Drive/ColabData')\n",
    "    !wget -O 'mcbbox/subcoco_utils.py' https://raw.githubusercontent.com/bguan/mcbbox/master/mcbbox/subcoco_utils.py\n",
    "    !wget -O 'mcbbox/subcoco_lightning_utils.py' https://raw.githubusercontent.com/bguan/mcbbox/master/mcbbox/subcoco_lightning_utils.py\n",
    "    !pip install torch torchvision pytorch_lightning effdet gpumonitor albumentations==0.4.6\n",
    "\n",
    "print(f'Current Directory is now {os.getcwd()}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python ver 3.8.5 (default, Jul 28 2020, 12:59:40) \n",
      "[GCC 9.3.0], torch 1.7.0, torchvision 0.8.1, pytorch_lightning 1.0.4, Albumentation 0.5.0\n",
      "Python ver 3.8.5 (default, Jul 28 2020, 12:59:40) \n",
      "[GCC 9.3.0], torch 1.7.0, torchvision 0.8.1, pytorch_lightning 1.0.4\n"
     ]
    }
   ],
   "source": [
    "#export\n",
    "import albumentations as A\n",
    "import pytorch_lightning as pl\n",
    "import torch, torchvision\n",
    "import torch.nn.functional as F\n",
    "import torch.multiprocessing\n",
    "from pytorch_lightning import LightningDataModule, LightningModule, Trainer\n",
    "from torch import nn\n",
    "from torch.nn.modules import module\n",
    "from torch import optim\n",
    "from torch.utils.data import DataLoader, random_split\n",
    "from torchvision.models.detection import FasterRCNN\n",
    "from torchvision.models.detection.rpn import AnchorGenerator\n",
    "from torchvision.models.detection.faster_rcnn import FastRCNNPredictor\n",
    "from mcbbox.subcoco_utils import *\n",
    "from mcbbox.subcoco_lightning_utils import *\n",
    "\n",
    "torch.multiprocessing.set_sharing_strategy('file_system')\n",
    "print(f\"Python ver {sys.version}, torch {torch.__version__}, torchvision {torchvision.__version__}, pytorch_lightning {pl.__version__}\")\n",
    "\n",
    "if is_notebook():\n",
    "    from nbdev.showdoc import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Setup the Run\n",
    "\n",
    "Centralize test run vs prod time parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/brian/.local/lib/python3.8/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
      "  and should_run_async(code)\n"
     ]
    }
   ],
   "source": [
    "#hide\n",
    "test = True\n",
    "backbone_name = 'fasterrcnn_resnet50_fpn'\n",
    "if test:\n",
    "    img_sz, head_runs, full_runs, save_top, lr, patience, calc_metrics = 128, 1, 1, 1, 0.01, 1, True\n",
    "    bs, acc, workers = 2, 16, 4\n",
    "    datadir, url, img_subdir = '/tmp', 'http://files.fast.ai/data/examples/coco_tiny.tgz', 'train'\n",
    "else:\n",
    "    img_sz, head_runs, full_runs, save_top, lr, patience, calc_metrics = 384, 5, 20, -1, 0.01, 10, True\n",
    "    bs, acc, workers =  (16, 2, 8) if IN_COLAB else (6, 6, 4) \n",
    "    datadir, url, img_subdir = 'workspace', 'https://s3.amazonaws.com/fast-ai-coco/coco_sample.tgz', 'train_sample'\n",
    "    \n",
    "stem = Path(url).stem\n",
    "img_dir=f'{datadir}/{stem}/{img_subdir}'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download a Sample of COCO Data\n",
    "\n",
    "The full COCO Dataset is huge (~50GB?). For my self education exploring object detection, with the intention of using pretrained model in transfer learning, it is not practical to deal with dataset this big as my first project.  Luckily, the kind folks at [FastAI](https://fast.ai) have prepared some convenient subsets, the medium size 3GB https://s3.amazonaws.com/fast-ai-coco/coco_sample.tgz seems like a good candidate.  The 800KB \"http://files.fast.ai/data/examples/coco_tiny.tgz\" on the other hand seems way too small, thus may not have enough data for adequate training."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([{'id': 62, 'name': 'chair'},\n",
       "  {'id': 63, 'name': 'couch'},\n",
       "  {'id': 72, 'name': 'tv'},\n",
       "  {'id': 75, 'name': 'remote'},\n",
       "  {'id': 84, 'name': 'book'},\n",
       "  {'id': 86, 'name': 'vase'}],\n",
       " {'id': 542959, 'file_name': '000000542959.jpg'},\n",
       " [{'image_id': 542959, 'bbox': [32.52, 86.34, 8.53, 9.41], 'category_id': 62},\n",
       "  {'image_id': 542959, 'bbox': [98.12, 110.52, 1.95, 4.07], 'category_id': 86},\n",
       "  {'image_id': 542959, 'bbox': [91.28, 51.62, 3.95, 5.72], 'category_id': 86},\n",
       "  {'image_id': 542959,\n",
       "   'bbox': [110.48, 110.82, 14.55, 15.22],\n",
       "   'category_id': 62},\n",
       "  {'image_id': 542959,\n",
       "   'bbox': [96.63, 50.18, 18.67, 13.46],\n",
       "   'category_id': 62},\n",
       "  {'image_id': 542959,\n",
       "   'bbox': [0.69, 111.73, 11.8, 13.06],\n",
       "   'category_id': 62}])"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#hide\n",
    "train_json = fetch_subcoco(datadir=datadir, url=url, img_subdir=img_subdir)\n",
    "train_json['categories'], train_json['images'][0], [a for a in train_json['annotations'] if a['image_id']==train_json['images'][0]['id'] ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Digest the Dataset for useful Stats\n",
    "\n",
    "Do some basic analysis of the data to get numbers like total images, boxes, and average box count per image... Print out number of boxes per category to see if the distribution is not too unbalanced..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Categories 6, Images 200, Boxes 688, avg (w,h) (128.0, 128.0)avg cats/img 7.0, avg boxs/img 3.4, avg boxs/cat 114.7.\n",
      "Image means by channel [126.2909314  109.02263367 100.61073242], std.dev by channel [65.60744282 65.09696176 60.4631069 ]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'chair': 284, 'vase': 64, 'tv': 26, 'couch': 40, 'book': 254, 'remote': 20}"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#hide\n",
    "stats = load_stats(train_json, img_dir=img_dir, force_reload=False)\n",
    "print(\n",
    "    f\"Categories {stats.num_cats}, Images {stats.num_imgs}, Boxes {stats.num_bboxs}, avg (w,h) {(stats.avg_width, stats.avg_height)}\"\n",
    "    f\"avg cats/img {stats.avg_ncats_per_img:.1f}, avg boxs/img {stats.avg_nboxs_per_img:.1f}, avg boxs/cat {stats.avg_nboxs_per_cat:.1f}.\")\n",
    "\n",
    "print(f\"Image means by channel {stats.chn_means}, std.dev by channel {stats.chn_stds}\")\n",
    "{ stats.cat2name[stats.lbl2cat[lid]]: len(ibs) for lid, ibs in stats.l2ibs.items()}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Look at Images\n",
    "\n",
    "Let's look at an image annotation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "best_img_pos 89\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(107903,\n",
       " '000000107903.jpg',\n",
       " {0: [],\n",
       "  1: [(90.86, 85.09, 33.16, 38.46)],\n",
       "  2: [(81.75, 56.7, 42.12, 31.66), (91.19, 85.84, 33.11, 37.77)],\n",
       "  3: [(31.67, 36.95, 29.82, 24.54)],\n",
       "  4: [],\n",
       "  5: [(70.08, 91.25, 9.82, 5.1),\n",
       "   (67.28, 77.63, 16.32, 5.83),\n",
       "   (37.7, 76.38, 1.16, 4.6),\n",
       "   (5.12, 73.58, 3.41, 8.88),\n",
       "   (115.35, 75.7, 8.47, 2.68),\n",
       "   (69.76, 93.02, 9.79, 6.08),\n",
       "   (64.86, 87.24, 9.3, 4.97),\n",
       "   (8.36, 63.94, 1.09, 6.74),\n",
       "   (115.74, 74.44, 8.03, 3.33),\n",
       "   (77.48, 91.77, 6.14, 2.82),\n",
       "   (8.33, 73.88, 1.55, 8.13)],\n",
       "  6: [(6.2, 42.53, 3.48, 3.95)]})"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#hide\n",
    "best_img_pos = None\n",
    "max_boxs = 0\n",
    "for img_pos in range(len(train_json['images'])):  \n",
    "    img_id = train_json['images'][img_pos]['id']\n",
    "    l2bs = stats.img2l2bs.get(img_id, {})\n",
    "    n_boxs =  reduce((lambda x, y: x + y), [1 if len(bs) > 0 else 0 for bs in l2bs.values()], 0)\n",
    "    if n_boxs >= max_boxs:\n",
    "        best_img_pos = img_pos\n",
    "        max_boxs = n_boxs\n",
    "\n",
    "print(f'best_img_pos {best_img_pos}')\n",
    "best_img_id = train_json['images'][best_img_pos]['id']\n",
    "l2bs = stats.img2l2bs[best_img_id]\n",
    "best_img_fname = stats.img2fname[best_img_id]\n",
    "best_img_id, best_img_fname, l2bs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overlay Boxes and Labels from Annotation\n",
    "\n",
    "Let's overlay bounding boxes and labels over the image to confirm our understanding of the data.\n",
    "Pick some random image to test drive the box overlay code..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "img = <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=128x128 at 0x7F9BB1CBA6A0>\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#hide\n",
    "img = Image.open(Path(img_dir)/stats.img2fname[best_img_id])\n",
    "print(f\"img = {img}\")\n",
    "overlay_img_bbox(img, stats.img2l2bs[best_img_id], stats.lbl2name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Packaging Model and Metric Into A Lightning Module"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# export\n",
    "class FRCNN(AbstractDetectorLightningModule):\n",
    "    def __init__(self, **kwargs):\n",
    "        AbstractDetectorLightningModule.__init__(self, **kwargs)\n",
    "    \n",
    "    def create_model(self, backbone_name, num_classes=1, **kwargs): \n",
    "        model = torchvision.models.detection.fasterrcnn_resnet50_fpn(pretrained=True)\n",
    "        self.in_features = model.roi_heads.box_predictor.cls_score.in_features\n",
    "        # replace the pre-trained head with a new one, which is trainable\n",
    "        model.roi_heads.box_predictor = FastRCNNPredictor(self.in_features, self.num_classes+1)\n",
    "        \n",
    "        # Hacked to avoid model builtin call to GeneralizedRCNNTransform.normalize() as done in augmentation\n",
    "        def noop_normalize(image): return image \n",
    "\n",
    "        # Hacked to avoid model builtin call to GeneralizedRCNNTransform.resize() as done in augmentation\n",
    "        def noop_resize(image, target): return image, target  \n",
    "\n",
    "        # HACK!! IceVision does this too!\n",
    "        model.transform.normalize = noop_normalize\n",
    "        model.transform.resize = noop_resize\n",
    "        \n",
    "        return model\n",
    "        \n",
    "    def get_main_model(self): return self.model\n",
    "        \n",
    "    def get_head(self):  return self.model.roi_heads\n",
    "        \n",
    "    def get_backbone(self): return self.model.backbone"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Neural Network Architecture Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On my Dell XPS15 GTX-1050 GPU w/ 4GB VRAM,  I can average 1 epoc every 120 min or so, at bs=2 acc=16, img 384x384, with unfrozen backbone.\n",
    "\n",
    "Using my GCP w/ V100 of 16GB VRAM, I can fit bs=12 for sample_coco, acc=16, img 384x384, with unfrozen backbone, 1 epoc every ~25 minutes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training with image size 128, learning rate 0.01, patience = 1, for 1+1 epochs.\n",
      "Loading previously saved model: models/fasterrcnn_resnet50_fpn-128-last.ckpt...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.8/dist-packages/pytorch_lightning/utilities/distributed.py:45: UserWarning: Checkpoint directory models exists and is not empty. With save_top_k=1, all files in this directory will be deleted when a checkpoint is saved!\n",
      "  warnings.warn(*args, **kwargs)\n",
      "GPU available: True, used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training with image size 128, learning rate 0.01, for 1+1 epochs.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  | Name  | Type       | Params\n",
      "-------------------------------------\n",
      "0 | model | FasterRCNN | 41 M  \n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', description='Validation sanity check', layout=Layout…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Entering validation_step\n",
      "Entering forward, training = False\n",
      "Exiting forward, returning [{'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}, {'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}, {'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}, {'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}]\n",
      "Exiting validation_step, returning {'val_loss': tensor(0.6147, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n",
      "Entering validation_step\n",
      "Entering forward, training = False\n",
      "Exiting forward, returning [{'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}, {'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}, {'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}, {'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}]\n",
      "Exiting validation_step, returning {'val_loss': tensor(1.0277, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n",
      "Entering validation_epoch_end\n",
      "Exiting validation_epoch_end, returning {'val_loss': tensor(0.8212, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "56a046b97c654be8890b1aff28f8e058",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', description='Training', layout=Layout(flex='2'), max…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Entering training_step\n",
      "Exiting training_step, returning 0.9724935293197632\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.144490122795105\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.246211051940918\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.0208759307861328\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.0443642139434814\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.3040162324905396\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.5702695846557617\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.8864560723304749\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9028453230857849\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.126023292541504\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.037903070449829\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.7624186277389526\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.7767469882965088\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.7411105036735535\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.0412241220474243\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.479278326034546\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.3115040063858032\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.6212706565856934\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9724074006080627\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.8161281943321228\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.5160703659057617\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.2723312377929688\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.5457644462585449\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.8964812755584717\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.0640501976013184\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.1318199634552002\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9591837525367737\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.44512656331062317\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.8722243309020996\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.8631480932235718\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.7357665300369263\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.8437418937683105\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.7889716029167175\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.5746426582336426\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.0900193452835083\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.1254485845565796\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.5980916023254395\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9193638563156128\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9534958600997925\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.3574482202529907\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9593803882598877\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.945280909538269\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.5671595931053162\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.0808650255203247\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.6270435452461243\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.0525052547454834\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.6028538942337036\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.8879815340042114\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', description='Validating', layout=Layout(flex='2'), m…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Entering validation_step\n",
      "Entering forward, training = False\n",
      "Exiting forward, returning [{'boxes': tensor([[  0.0000,  12.3304, 128.0000, 125.6344]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0702], device='cuda:0')}, {'boxes': tensor([[  0.0000,  12.3038, 128.0000, 125.5829]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0704], device='cuda:0')}, {'boxes': tensor([[  0.0000,  12.2518, 128.0000, 125.6484]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0704], device='cuda:0')}, {'boxes': tensor([[  0.0000,  12.2719, 128.0000, 125.6467]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0704], device='cuda:0')}]\n",
      "Exiting validation_step, returning {'val_loss': tensor(0.4868, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n",
      "Entering validation_step\n",
      "Entering forward, training = False\n",
      "Exiting forward, returning [{'boxes': tensor([[  0.0000,  12.2840, 128.0000, 125.7254]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0703], device='cuda:0')}, {'boxes': tensor([[  0.0000,  12.3420, 128.0000, 125.7392]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0703], device='cuda:0')}, {'boxes': tensor([[  0.0000,  12.2754, 128.0000, 125.6674]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0703], device='cuda:0')}, {'boxes': tensor([[  0.0000,  12.3138, 128.0000, 125.6779]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0703], device='cuda:0')}]\n",
      "Exiting validation_step, returning {'val_loss': tensor(0.9874, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n",
      "Entering validation_step\n",
      "Entering forward, training = False\n",
      "Exiting forward, returning [{'boxes': tensor([[  0.0000,  12.3179, 128.0000, 125.6453]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0703], device='cuda:0')}, {'boxes': tensor([[  0.0000,  12.2327, 128.0000, 125.6993]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0704], device='cuda:0')}]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 0: val_acc reached 0.00000 (best 0.00000), saving model to /home/brian/Projects/mcbbox/models/fasterrcnn_resnet50_fpn-head-128-epoch=000-val_acc=0.000.ckpt as top 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exiting validation_step, returning {'val_loss': tensor(0.4071, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n",
      "Entering validation_epoch_end\n",
      "Exiting validation_epoch_end, returning {'val_loss': tensor(0.6271, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Saving latest checkpoint...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\u001b[36m[0]\u001b[m \u001b[34mGeForce GTX 1050\u001b[m |\u001b[1m\u001b[31m 52'C\u001b[m, \u001b[1m\u001b[32m 54 %\u001b[m | \u001b[36m\u001b[1m\u001b[33m 2382\u001b[m / \u001b[33m 4042\u001b[m MB | \u001b[1m\u001b[30mbrian\u001b[m(\u001b[33m747M\u001b[m) \u001b[1m\u001b[30mroot\u001b[m(\u001b[33m797M\u001b[m) \u001b[1m\u001b[30mbrian\u001b[m(\u001b[33m41M\u001b[m) \u001b[1m\u001b[30mbrian\u001b[m(\u001b[33m307M\u001b[m)\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True, used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "\n",
      "  | Name  | Type       | Params\n",
      "-------------------------------------\n",
      "0 | model | FasterRCNN | 41 M  \n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', description='Validation sanity check', layout=Layout…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Entering validation_step\n",
      "Entering forward, training = False\n",
      "Exiting forward, returning [{'boxes': tensor([[  0.0000,  12.2646, 128.0000, 125.6347]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0701], device='cuda:0')}, {'boxes': tensor([[  0.0000,  12.3686, 128.0000, 125.6894]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0705], device='cuda:0')}]\n",
      "Exiting validation_step, returning {'val_loss': tensor(1.1156, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n",
      "Entering validation_step\n",
      "Entering forward, training = False\n",
      "Exiting forward, returning [{'boxes': tensor([[  0.0000,  12.2926, 128.0000, 125.6159]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0703], device='cuda:0')}, {'boxes': tensor([[  0.0000,  12.3144, 128.0000, 125.6657]], device='cuda:0'), 'labels': tensor([1], device='cuda:0'), 'scores': tensor([0.0701], device='cuda:0')}]\n",
      "Exiting validation_step, returning {'val_loss': tensor(0.3665, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n",
      "Entering validation_epoch_end\n",
      "Exiting validation_epoch_end, returning {'val_loss': tensor(0.7411, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5ce65760776e4c7d9148f35fd80a2839",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', description='Training', layout=Layout(flex='2'), max…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Entering training_step\n",
      "Exiting training_step, returning 0.4102698862552643\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9468743801116943\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.8420443534851074\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9778741598129272\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.6765507459640503\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.563879370689392\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.6058794856071472\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.1313060522079468\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.531723141670227\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.4131311774253845\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.4278509616851807\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.8069641590118408\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.48928147554397583\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.1162185668945312\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.4475666284561157\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9751744866371155\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.0214444398880005\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.7945626974105835\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.7929340600967407\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.6894004344940186\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.5930355787277222\n",
      "Entering training_step\n",
      "Exiting training_step, returning 2.5765719413757324\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.001726746559143\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.3062028884887695\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.5373644828796387\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.9118242263793945\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9375554323196411\n",
      "Entering training_step\n",
      "Exiting training_step, returning 2.377303123474121\n",
      "Entering training_step\n",
      "Exiting training_step, returning 2.313868999481201\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.0642063617706299\n",
      "Entering training_step\n",
      "Exiting training_step, returning 4.677117347717285\n",
      "Entering training_step\n",
      "Exiting training_step, returning 2.024970054626465\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.5648105144500732\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.555124044418335\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.7583223581314087\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.2034204006195068\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.6985280513763428\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.4989676475524902\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.6390599012374878\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.237457036972046\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.8667927384376526\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.5824425220489502\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.9929165840148926\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.0308159589767456\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.6576775908470154\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.797438144683838\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9230095744132996\n",
      "Entering training_step\n",
      "Exiting training_step, returning 2.0785951614379883\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.8519203066825867\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.5862002968788147\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.2322416305541992\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.4621952772140503\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.8844645023345947\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9795483946800232\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.4586622714996338\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9169639348983765\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.7176406383514404\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.5897235870361328\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.4559810161590576\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.2242350578308105\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.768538236618042\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.8600794076919556\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.5015125274658203\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.6506377458572388\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.6096819639205933\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.3396639823913574\n",
      "Entering training_step\n",
      "Exiting training_step, returning 2.1451478004455566\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.29204168915748596\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.39946484565734863\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.5124154090881348\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.9189492464065552\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.0745375156402588\n",
      "Entering training_step\n",
      "Exiting training_step, returning 2.849510669708252\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.4586036205291748\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.6181780695915222\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.694303035736084\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.655608057975769\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.4984714388847351\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.6290011405944824\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.8388872742652893\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9241981506347656\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.3951050937175751\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.7576401233673096\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.4559640884399414\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.9130533933639526\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.0853196382522583\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.5177980661392212\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.2824516296386719\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.009179949760437\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.6442155838012695\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.7653717398643494\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.7150694131851196\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.39516881108283997\n",
      "Entering training_step\n",
      "Exiting training_step, returning 0.3724730610847473\n",
      "Entering training_step\n",
      "Exiting training_step, returning 1.4730136394500732\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', description='Validating', layout=Layout(flex='2'), m…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Entering validation_step\n",
      "Entering forward, training = False\n",
      "Exiting forward, returning [{'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}, {'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}]\n",
      "Exiting validation_step, returning {'val_loss': tensor(1.1153, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n",
      "Entering validation_step\n",
      "Entering forward, training = False\n",
      "Exiting forward, returning [{'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}, {'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}]\n",
      "Exiting validation_step, returning {'val_loss': tensor(0.3583, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n",
      "Entering validation_step\n",
      "Entering forward, training = False\n",
      "Exiting forward, returning [{'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}, {'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}]\n",
      "Exiting validation_step, returning {'val_loss': tensor(0.5853, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n",
      "Entering validation_step\n",
      "Entering forward, training = False\n",
      "Exiting forward, returning [{'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}, {'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}]\n",
      "Exiting validation_step, returning {'val_loss': tensor(0.7410, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n",
      "Entering validation_step\n",
      "Entering forward, training = False\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 0: val_acc reached 0.00000 (best 0.00000), saving model to /home/brian/Projects/mcbbox/models/fasterrcnn_resnet50_fpn-full-128-epoch=000-val_acc=0.000.ckpt as top 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exiting forward, returning [{'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}, {'boxes': tensor([], device='cuda:0', size=(0, 4)), 'labels': tensor([], device='cuda:0', dtype=torch.int64), 'scores': tensor([], device='cuda:0')}]\n",
      "Exiting validation_step, returning {'val_loss': tensor(0.9007, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n",
      "Entering validation_epoch_end\n",
      "Exiting validation_epoch_end, returning {'val_loss': tensor(0.7401, device='cuda:0'), 'val_acc': tensor(0.), 'val_coco': tensor(0.)}\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Saving latest checkpoint...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\u001b[36m[0]\u001b[m \u001b[34mGeForce GTX 1050\u001b[m |\u001b[1m\u001b[31m 54'C\u001b[m, \u001b[1m\u001b[32m 54 %\u001b[m | \u001b[36m\u001b[1m\u001b[33m 2627\u001b[m / \u001b[33m 4042\u001b[m MB | \u001b[1m\u001b[30mbrian\u001b[m(\u001b[33m951M\u001b[m) \u001b[1m\u001b[30mroot\u001b[m(\u001b[33m797M\u001b[m) \u001b[1m\u001b[30mbrian\u001b[m(\u001b[33m41M\u001b[m) \u001b[1m\u001b[30mbrian\u001b[m(\u001b[33m264M\u001b[m)\n",
      "\n",
      "last_model_path saved = /home/brian/Projects/mcbbox/models/fasterrcnn_resnet50_fpn-128-last.ckpt\n"
     ]
    }
   ],
   "source": [
    "#hide\n",
    "if torch.cuda.is_available():\n",
    "    frcnn_model, last_model_path = run_training(FRCNN, backbone_name, stats, img_dir, \n",
    "        resume_ckpt_fname=f'{backbone_name}-{img_sz}-last.ckpt', \n",
    "        img_sz=img_sz, lr=lr, bs=bs, acc=acc, workers=workers, head_runs=head_runs, full_runs=full_runs,\n",
    "        save_top=save_top, test=test, calc_metrics=calc_metrics, monitor='val_acc', mode='max', patience=patience\n",
    "    )\n",
    "\n",
    "    print(f\"last_model_path saved = {last_model_path}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#hide\n",
    "# if is_notebook() and torch.cuda.is_available():\n",
    "#     %reload_ext tensorboard\n",
    "#     %tensorboard --logdir lightning_logs/ --host \"0.0.0.0\" "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Inference\n",
    "\n",
    "Time to see how well the model can perform."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Entering forward, training = False\n",
      "Exiting forward, returning [{'boxes': tensor([], size=(0, 4)), 'labels': tensor([], dtype=torch.int64), 'scores': tensor([])}]\n",
      "pred labels to boxes: {}\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bbox_aware_test_tfms=A.Compose([\n",
    "    A.Resize(width=img_sz, height=img_sz),\n",
    "], bbox_params=A.BboxParams(format='pascal_voc', label_fields=['class_labels']))\n",
    "\n",
    "test_set = SubCocoDataset(img_dir, stats, img_ids=[best_img_id], bbox_aware_tfms=bbox_aware_test_tfms)\n",
    "\n",
    "if torch.cuda.is_available():\n",
    "    x, y = test_set[0] \n",
    "    pimg = torchvision.transforms.ToPILImage()(x)\n",
    "    tgt_l2bs = defaultdict(empty_list)\n",
    "    for l, b in zip(list(y['labels']), y['boxes']):\n",
    "        tgt_l2bs[int(l)].append( (int(b[0]), int(b[1]), int(b[2]-b[0]), int(b[3]-b[1])) ) \n",
    "\n",
    "    overlay_img_bbox(pimg, tgt_l2bs, stats.lbl2name)\n",
    "\n",
    "    frcnn_model.eval()\n",
    "    pred = frcnn_model([x])\n",
    "    pred_l2bs = digest_pred(stats.lbl2name, pred[0], cutoff=0.1, img_sz=x.shape[1])\n",
    "    print(f\"pred labels to boxes: { {k:len(v) for k, v in pred_l2bs.items()} }\")\n",
    "    overlay_img_bbox(pimg, pred_l2bs, stats.lbl2name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare with Original Image before transformations incl. Normalization and Resize."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "if torch.cuda.is_available():\n",
    "    img_id = int(y['image_id'])\n",
    "    img = Image.open(Path(img_dir)/stats.img2fname[img_id])\n",
    "    overlay_img_bbox(img, stats.img2l2bs[img_id], stats.lbl2name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reloading Saved Checkpoint using Pytorch Lightning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#hide\n",
    "if torch.cuda.is_available():\n",
    "    last_model_path = f'models/{backbone_name}-{img_sz}-last.ckpt'\n",
    "    pretrained_model = FRCNN.load_from_checkpoint(last_model_path, backbone_name=backbone_name, bs=bs, steps_per_epoch=0, num_classes=len(stats.lbl2name), img_sz=img_sz)\n",
    "    pretrained_model.freeze()\n",
    "    x, y = test_set[0]\n",
    "    pred = pretrained_model([x])\n",
    "    pred_l2bs = digest_pred(stats.lbl2name, pred[0], cutoff=0.5, img_sz=x.shape[1])\n",
    "    pimg = torchvision.transforms.ToPILImage()(x)\n",
    "    overlay_img_bbox(pimg, pred_l2bs, stats.lbl2name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Saving and Reloading using Underlying Pytorch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# export\n",
    "def save_final(frcnn_model, model_save_path):\n",
    "    torch.save(frcnn_model.model.state_dict(), model_save_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "if torch.cuda.is_available():\n",
    "    model_save_path = f'models/FRCNN-{img_sz}-final.pth'\n",
    "    save_final(frcnn_model, model_save_path)\n",
    "    pretrained_model = FRCNN(backbone_name=backbone_name, bs=bs, steps_per_epoch=0, num_classes=len(stats.lbl2name), img_sz=img_sz)\n",
    "    pretrained_model.model.load_state_dict(torch.load(model_save_path))\n",
    "    pretrained_model.freeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pred labels to boxes: {}\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "if torch.cuda.is_available():\n",
    "    x, y = test_set[0] \n",
    "    pred = pretrained_model([x])\n",
    "    pred_l2bs = digest_pred(stats.lbl2name, pred[0], cutoff=0.1, img_sz=x.shape[1])\n",
    "    print(f\"pred labels to boxes: { {k:len(v) for k, v in pred_l2bs.items()} }\")\n",
    "    pimg = torchvision.transforms.ToPILImage()(x)\n",
    "    overlay_img_bbox(pimg, pred_l2bs, stats.lbl2name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}