test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from roboflow import Roboflow\n",
    "\n",
    "rf = Roboflow(api_key=\"LqD8Cs4OsoK8seO3CPkf\")  # Make sure your API key is correct\n",
    "project = rf.workspace(\"car-damage-detection-wjnwh\").project(\"car-damage-detection-krsix\")\n",
    "version = project.version(2)\n",
    "dataset = version.download(\"coco\")  # Downloading in COCO format\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m[03/11 13:13:23 d2.engine.defaults]: \u001b[0mModel:\n",
      "GeneralizedRCNN(\n",
      "  (backbone): FPN(\n",
      "    (fpn_lateral2): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n",
      "    (fpn_output2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (fpn_lateral3): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n",
      "    (fpn_output3): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (fpn_lateral4): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1))\n",
      "    (fpn_output4): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (fpn_lateral5): Conv2d(2048, 256, kernel_size=(1, 1), stride=(1, 1))\n",
      "    (fpn_output5): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (top_block): LastLevelMaxPool()\n",
      "    (bottom_up): ResNet(\n",
      "      (stem): BasicStem(\n",
      "        (conv1): Conv2d(\n",
      "          3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False\n",
      "          (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n",
      "        )\n",
      "      )\n",
      "      (res2): Sequential(\n",
      "        (0): BottleneckBlock(\n",
      "          (shortcut): Conv2d(\n",
      "            64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "          (conv1): Conv2d(\n",
      "            64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "        (1): BottleneckBlock(\n",
      "          (conv1): Conv2d(\n",
      "            256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "        (2): BottleneckBlock(\n",
      "          (conv1): Conv2d(\n",
      "            256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "      )\n",
      "      (res3): Sequential(\n",
      "        (0): BottleneckBlock(\n",
      "          (shortcut): Conv2d(\n",
      "            256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n",
      "          )\n",
      "          (conv1): Conv2d(\n",
      "            256, 128, kernel_size=(1, 1), stride=(2, 2), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "        (1): BottleneckBlock(\n",
      "          (conv1): Conv2d(\n",
      "            512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "        (2): BottleneckBlock(\n",
      "          (conv1): Conv2d(\n",
      "            512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "        (3): BottleneckBlock(\n",
      "          (conv1): Conv2d(\n",
      "            512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "      )\n",
      "      (res4): Sequential(\n",
      "        (0): BottleneckBlock(\n",
      "          (shortcut): Conv2d(\n",
      "            512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n",
      "          )\n",
      "          (conv1): Conv2d(\n",
      "            512, 256, kernel_size=(1, 1), stride=(2, 2), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "        (1): BottleneckBlock(\n",
      "          (conv1): Conv2d(\n",
      "            1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "        (2): BottleneckBlock(\n",
      "          (conv1): Conv2d(\n",
      "            1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "        (3): BottleneckBlock(\n",
      "          (conv1): Conv2d(\n",
      "            1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "        (4): BottleneckBlock(\n",
      "          (conv1): Conv2d(\n",
      "            1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "        (5): BottleneckBlock(\n",
      "          (conv1): Conv2d(\n",
      "            1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "      )\n",
      "      (res5): Sequential(\n",
      "        (0): BottleneckBlock(\n",
      "          (shortcut): Conv2d(\n",
      "            1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=2048, eps=1e-05)\n",
      "          )\n",
      "          (conv1): Conv2d(\n",
      "            1024, 512, kernel_size=(1, 1), stride=(2, 2), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=2048, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "        (1): BottleneckBlock(\n",
      "          (conv1): Conv2d(\n",
      "            2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=2048, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "        (2): BottleneckBlock(\n",
      "          (conv1): Conv2d(\n",
      "            2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n",
      "          )\n",
      "          (conv2): Conv2d(\n",
      "            512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n",
      "          )\n",
      "          (conv3): Conv2d(\n",
      "            512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
      "            (norm): FrozenBatchNorm2d(num_features=2048, eps=1e-05)\n",
      "          )\n",
      "        )\n",
      "      )\n",
      "    )\n",
      "  )\n",
      "  (proposal_generator): RPN(\n",
      "    (rpn_head): StandardRPNHead(\n",
      "      (conv): Conv2d(\n",
      "        256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)\n",
      "        (activation): ReLU()\n",
      "      )\n",
      "      (objectness_logits): Conv2d(256, 3, kernel_size=(1, 1), stride=(1, 1))\n",
      "      (anchor_deltas): Conv2d(256, 12, kernel_size=(1, 1), stride=(1, 1))\n",
      "    )\n",
      "    (anchor_generator): DefaultAnchorGenerator(\n",
      "      (cell_anchors): BufferList()\n",
      "    )\n",
      "  )\n",
      "  (roi_heads): StandardROIHeads(\n",
      "    (box_pooler): ROIPooler(\n",
      "      (level_poolers): ModuleList(\n",
      "        (0): ROIAlign(output_size=(7, 7), spatial_scale=0.25, sampling_ratio=0, aligned=True)\n",
      "        (1): ROIAlign(output_size=(7, 7), spatial_scale=0.125, sampling_ratio=0, aligned=True)\n",
      "        (2): ROIAlign(output_size=(7, 7), spatial_scale=0.0625, sampling_ratio=0, aligned=True)\n",
      "        (3): ROIAlign(output_size=(7, 7), spatial_scale=0.03125, sampling_ratio=0, aligned=True)\n",
      "      )\n",
      "    )\n",
      "    (box_head): FastRCNNConvFCHead(\n",
      "      (flatten): Flatten(start_dim=1, end_dim=-1)\n",
      "      (fc1): Linear(in_features=12544, out_features=1024, bias=True)\n",
      "      (fc_relu1): ReLU()\n",
      "      (fc2): Linear(in_features=1024, out_features=1024, bias=True)\n",
      "      (fc_relu2): ReLU()\n",
      "    )\n",
      "    (box_predictor): FastRCNNOutputLayers(\n",
      "      (cls_score): Linear(in_features=1024, out_features=48, bias=True)\n",
      "      (bbox_pred): Linear(in_features=1024, out_features=188, bias=True)\n",
      "    )\n",
      "  )\n",
      ")\n",
      "\u001b[5m\u001b[31mWARNING\u001b[0m \u001b[32m[03/11 13:13:23 d2.data.datasets.coco]: \u001b[0m\n",
      "Category ids in annotations are not in [1, #categories]! We'll apply a mapping for you.\n",
      "\n",
      "\u001b[32m[03/11 13:13:23 d2.data.datasets.coco]: \u001b[0mLoaded 4563 images in COCO format from car-damage-detection-2/train/_annotations.coco.json\n",
      "\u001b[32m[03/11 13:13:23 d2.data.build]: \u001b[0mRemoved 0 images with no usable annotations. 4563 images left.\n",
      "\u001b[32m[03/11 13:13:23 d2.data.build]: \u001b[0mDistribution of instances among all 47 categories:\n",
      "\u001b[36m|   category    | #instances   |   category    | #instances   |   category    | #instances   |\n",
      "|:-------------:|:-------------|:-------------:|:-------------|:-------------:|:-------------|\n",
      "| Car-Damage-.. | 0            | Bodypanel-D.. | 1            | Front-Winds.. | 46           |\n",
      "| Headlight-D.. | 98           | Rear-windsc.. | 75           | RunningBoar.. | 48           |\n",
      "| Sidemirror-.. | 34           | Signlight-D.. | 9            | Taillight-D.. | 48           |\n",
      "|  back-bumper  | 102          |  back-glass   | 106          |  bonnet-dent  | 239          |\n",
      "|   boot-dent   | 37           |  broken_lamp  | 361          |     crack     | 454          |\n",
      "| damaged-door  | 104          | damaged-fro.. | 107          | damaged-hea.. | 153          |\n",
      "| damaged-hood  | 112          | damaged-rea.. | 89           | damaged-rea.. | 96           |\n",
      "| damaged-tai.. | 114          | damaged-trunk | 82           | damaged-win.. | 102          |\n",
      "| damaged-win.. | 138          |     dent      | 1385         | dent-or-scr.. | 255          |\n",
      "|     door      | 204          | doorouter-d.. | 310          |  fender-dent  | 179          |\n",
      "|   flat_tire   | 162          | front-bumper  | 133          | front-bumpe.. | 286          |\n",
      "|  front-glass  | 152          |   headlight   | 245          |     hood      | 149          |\n",
      "|    mirror     | 241          |  pillar-dent  | 15           | quaterpanel.. | 131          |\n",
      "| rear-bumper.. | 179          |   roof-dent   | 51           |    scratch    | 1891         |\n",
      "| shattered_g.. | 308          |   taillight   | 237          |     trunk     | 111          |\n",
      "|     wheel     | 136          |    window     | 112          |               |              |\n",
      "|     total     | 9627         |               |              |               |              |\u001b[0m\n",
      "\u001b[32m[03/11 13:13:23 d2.data.dataset_mapper]: \u001b[0m[DatasetMapper] Augmentations used in training: [ResizeShortestEdge(short_edge_length=(640, 672, 704, 736, 768, 800), max_size=1333, sample_style='choice'), RandomFlip()]\n",
      "\u001b[32m[03/11 13:13:23 d2.data.build]: \u001b[0mUsing training sampler TrainingSampler\n",
      "\u001b[32m[03/11 13:13:23 d2.data.common]: \u001b[0mSerializing the dataset using: <class 'detectron2.data.common._TorchSerializedList'>\n",
      "\u001b[32m[03/11 13:13:23 d2.data.common]: \u001b[0mSerializing 4563 elements to byte tensors and concatenating them all ...\n",
      "\u001b[32m[03/11 13:13:23 d2.data.common]: \u001b[0mSerialized dataset takes 6.23 MiB\n",
      "\u001b[32m[03/11 13:13:23 d2.data.build]: \u001b[0mMaking batched data loader with batch_size=2\n",
      "\u001b[5m\u001b[31mWARNING\u001b[0m \u001b[32m[03/11 13:13:23 d2.solver.build]: \u001b[0mSOLVER.STEPS contains values larger than SOLVER.MAX_ITER. These values will be ignored.\n",
      "\u001b[32m[03/11 13:13:23 d2.checkpoint.detection_checkpoint]: \u001b[0m[DetectionCheckpointer] Loading from https://dl.fbaipublicfiles.com/detectron2/COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Skip loading parameter 'roi_heads.box_predictor.cls_score.weight' to the model due to incompatible shapes: (81, 1024) in the checkpoint but (48, 1024) in the model! You might want to double check if this is expected.\n",
      "Skip loading parameter 'roi_heads.box_predictor.cls_score.bias' to the model due to incompatible shapes: (81,) in the checkpoint but (48,) in the model! You might want to double check if this is expected.\n",
      "Skip loading parameter 'roi_heads.box_predictor.bbox_pred.weight' to the model due to incompatible shapes: (320, 1024) in the checkpoint but (188, 1024) in the model! You might want to double check if this is expected.\n",
      "Skip loading parameter 'roi_heads.box_predictor.bbox_pred.bias' to the model due to incompatible shapes: (320,) in the checkpoint but (188,) in the model! You might want to double check if this is expected.\n",
      "Some model parameters or buffers are not found in the checkpoint:\n",
      "\u001b[34mroi_heads.box_predictor.bbox_pred.{bias, weight}\u001b[0m\n",
      "\u001b[34mroi_heads.box_predictor.cls_score.{bias, weight}\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m[03/11 13:13:24 d2.engine.train_loop]: \u001b[0mStarting training from iteration 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/mcw/miniconda3/envs/rohithk/lib/python3.12/site-packages/torch/functional.py:539: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /pytorch/aten/src/ATen/native/TensorShape.cpp:3637.)\n",
      "  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m[03/11 13:13:39 d2.utils.events]: \u001b[0m eta: 1:03:23  iter: 19  total_loss: 4.141  loss_cls: 3.863  loss_box_reg: 0.165  loss_rpn_cls: 0.0805  loss_rpn_loc: 0.01811    time: 0.5796  last_time: 0.5409  data_time: 0.0257  last_data_time: 0.0174   lr: 4.9953e-06  max_mem: 1739M\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-03-11 13:13:40.846796: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
      "E0000 00:00:1741679021.006687 1797043 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
      "E0000 00:00:1741679021.033001 1797043 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
      "2025-03-11 13:13:41.327110: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "\u001b[32m[03/11 13:14:11 d2.utils.events]: \u001b[0m eta: 1:01:53  iter: 59  total_loss: 3.615  loss_cls: 3.289  loss_box_reg: 0.128  loss_rpn_cls: 0.07853  loss_rpn_loc: 0.01824    time: 0.5722  last_time: 0.6104  data_time: 0.0132  last_data_time: 0.0031   lr: 1.4985e-05  max_mem: 1739M\n",
      "\u001b[32m[03/11 13:14:22 d2.utils.events]: \u001b[0m eta: 1:01:29  iter: 79  total_loss: 2.856  loss_cls: 2.648  loss_box_reg: 0.1373  loss_rpn_cls: 0.03618  loss_rpn_loc: 0.01702    time: 0.5717  last_time: 0.6092  data_time: 0.0153  last_data_time: 0.0145   lr: 1.998e-05  max_mem: 1740M\n",
      "\u001b[32m[03/11 13:14:34 d2.utils.events]: \u001b[0m eta: 1:00:53  iter: 99  total_loss: 2.16  loss_cls: 1.83  loss_box_reg: 0.1615  loss_rpn_cls: 0.08883  loss_rpn_loc: 0.02448    time: 0.5693  last_time: 0.5638  data_time: 0.0156  last_data_time: 0.0180   lr: 2.4975e-05  max_mem: 1740M\n",
      "\u001b[32m[03/11 13:14:45 d2.utils.events]: \u001b[0m eta: 1:01:06  iter: 119  total_loss: 1.021  loss_cls: 0.7497  loss_box_reg: 0.1125  loss_rpn_cls: 0.03447  loss_rpn_loc: 0.02233    time: 0.5707  last_time: 0.6198  data_time: 0.0168  last_data_time: 0.0306   lr: 2.997e-05  max_mem: 1740M\n",
      "\u001b[32m[03/11 13:14:56 d2.utils.events]: \u001b[0m eta: 1:00:59  iter: 139  total_loss: 0.6293  loss_cls: 0.3961  loss_box_reg: 0.1447  loss_rpn_cls: 0.04623  loss_rpn_loc: 0.01231    time: 0.5698  last_time: 0.5499  data_time: 0.0130  last_data_time: 0.0149   lr: 3.4965e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:15:08 d2.utils.events]: \u001b[0m eta: 1:00:52  iter: 159  total_loss: 0.6019  loss_cls: 0.3314  loss_box_reg: 0.1618  loss_rpn_cls: 0.05474  loss_rpn_loc: 0.02107    time: 0.5700  last_time: 0.6237  data_time: 0.0133  last_data_time: 0.0041   lr: 3.996e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:15:19 d2.utils.events]: \u001b[0m eta: 1:00:40  iter: 179  total_loss: 0.6928  loss_cls: 0.3405  loss_box_reg: 0.1486  loss_rpn_cls: 0.0578  loss_rpn_loc: 0.02111    time: 0.5689  last_time: 0.5986  data_time: 0.0139  last_data_time: 0.0173   lr: 4.4955e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:15:31 d2.utils.events]: \u001b[0m eta: 1:00:25  iter: 199  total_loss: 0.5319  loss_cls: 0.3114  loss_box_reg: 0.1541  loss_rpn_cls: 0.06768  loss_rpn_loc: 0.01688    time: 0.5693  last_time: 0.5426  data_time: 0.0119  last_data_time: 0.0143   lr: 4.995e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:15:42 d2.utils.events]: \u001b[0m eta: 1:00:21  iter: 219  total_loss: 0.4572  loss_cls: 0.2309  loss_box_reg: 0.1303  loss_rpn_cls: 0.03055  loss_rpn_loc: 0.01738    time: 0.5694  last_time: 0.5837  data_time: 0.0121  last_data_time: 0.0040   lr: 5.4945e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:15:53 d2.utils.events]: \u001b[0m eta: 1:00:11  iter: 239  total_loss: 0.4478  loss_cls: 0.2554  loss_box_reg: 0.1221  loss_rpn_cls: 0.01931  loss_rpn_loc: 0.0131    time: 0.5688  last_time: 0.6330  data_time: 0.0139  last_data_time: 0.0037   lr: 5.994e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:16:05 d2.utils.events]: \u001b[0m eta: 1:00:04  iter: 259  total_loss: 0.4475  loss_cls: 0.247  loss_box_reg: 0.1369  loss_rpn_cls: 0.03877  loss_rpn_loc: 0.01462    time: 0.5697  last_time: 0.6006  data_time: 0.0118  last_data_time: 0.0166   lr: 6.4935e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:16:16 d2.utils.events]: \u001b[0m eta: 0:59:48  iter: 279  total_loss: 0.4743  loss_cls: 0.2453  loss_box_reg: 0.1194  loss_rpn_cls: 0.04227  loss_rpn_loc: 0.01595    time: 0.5699  last_time: 0.5028  data_time: 0.0154  last_data_time: 0.0169   lr: 6.993e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:16:28 d2.utils.events]: \u001b[0m eta: 0:59:47  iter: 299  total_loss: 0.4515  loss_cls: 0.2678  loss_box_reg: 0.1363  loss_rpn_cls: 0.03489  loss_rpn_loc: 0.01459    time: 0.5705  last_time: 0.5289  data_time: 0.0107  last_data_time: 0.0130   lr: 7.4925e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:16:39 d2.utils.events]: \u001b[0m eta: 0:59:39  iter: 319  total_loss: 0.4338  loss_cls: 0.2544  loss_box_reg: 0.1546  loss_rpn_cls: 0.0233  loss_rpn_loc: 0.0101    time: 0.5706  last_time: 0.5067  data_time: 0.0151  last_data_time: 0.0288   lr: 7.992e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:16:50 d2.utils.events]: \u001b[0m eta: 0:59:13  iter: 339  total_loss: 0.4122  loss_cls: 0.2403  loss_box_reg: 0.1223  loss_rpn_cls: 0.0349  loss_rpn_loc: 0.01276    time: 0.5695  last_time: 0.5175  data_time: 0.0182  last_data_time: 0.0138   lr: 8.4915e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:17:02 d2.utils.events]: \u001b[0m eta: 0:59:01  iter: 359  total_loss: 0.4448  loss_cls: 0.2717  loss_box_reg: 0.1246  loss_rpn_cls: 0.02557  loss_rpn_loc: 0.01516    time: 0.5697  last_time: 0.5282  data_time: 0.0090  last_data_time: 0.0037   lr: 8.991e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:17:14 d2.utils.events]: \u001b[0m eta: 0:58:53  iter: 379  total_loss: 0.6362  loss_cls: 0.3344  loss_box_reg: 0.1907  loss_rpn_cls: 0.02946  loss_rpn_loc: 0.02121    time: 0.5703  last_time: 0.6056  data_time: 0.0151  last_data_time: 0.0036   lr: 9.4905e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:17:25 d2.utils.events]: \u001b[0m eta: 0:58:42  iter: 399  total_loss: 0.4748  loss_cls: 0.2683  loss_box_reg: 0.1348  loss_rpn_cls: 0.03399  loss_rpn_loc: 0.01603    time: 0.5702  last_time: 0.5070  data_time: 0.0139  last_data_time: 0.0264   lr: 9.99e-05  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:17:36 d2.utils.events]: \u001b[0m eta: 0:58:30  iter: 419  total_loss: 0.3904  loss_cls: 0.2288  loss_box_reg: 0.1262  loss_rpn_cls: 0.02209  loss_rpn_loc: 0.01226    time: 0.5700  last_time: 0.6149  data_time: 0.0161  last_data_time: 0.0176   lr: 0.0001049  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:17:47 d2.utils.events]: \u001b[0m eta: 0:58:15  iter: 439  total_loss: 0.4472  loss_cls: 0.2599  loss_box_reg: 0.1394  loss_rpn_cls: 0.02838  loss_rpn_loc: 0.01496    time: 0.5689  last_time: 0.4144  data_time: 0.0143  last_data_time: 0.0129   lr: 0.00010989  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:17:59 d2.utils.events]: \u001b[0m eta: 0:58:04  iter: 459  total_loss: 0.4953  loss_cls: 0.276  loss_box_reg: 0.1675  loss_rpn_cls: 0.02526  loss_rpn_loc: 0.01192    time: 0.5689  last_time: 0.5312  data_time: 0.0151  last_data_time: 0.0047   lr: 0.00011489  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:18:10 d2.utils.events]: \u001b[0m eta: 0:57:53  iter: 479  total_loss: 0.38  loss_cls: 0.197  loss_box_reg: 0.1142  loss_rpn_cls: 0.03655  loss_rpn_loc: 0.01411    time: 0.5692  last_time: 0.5425  data_time: 0.0113  last_data_time: 0.0154   lr: 0.00011988  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:18:22 d2.utils.events]: \u001b[0m eta: 0:57:44  iter: 499  total_loss: 0.4544  loss_cls: 0.2292  loss_box_reg: 0.1421  loss_rpn_cls: 0.02616  loss_rpn_loc: 0.01545    time: 0.5706  last_time: 0.6864  data_time: 0.0106  last_data_time: 0.0103   lr: 0.00012488  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:18:35 d2.utils.events]: \u001b[0m eta: 0:57:41  iter: 519  total_loss: 0.4314  loss_cls: 0.2595  loss_box_reg: 0.1339  loss_rpn_cls: 0.04412  loss_rpn_loc: 0.0145    time: 0.5727  last_time: 0.5719  data_time: 0.0166  last_data_time: 0.0342   lr: 0.00012987  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:18:48 d2.utils.events]: \u001b[0m eta: 0:57:48  iter: 539  total_loss: 0.4026  loss_cls: 0.2314  loss_box_reg: 0.1254  loss_rpn_cls: 0.03198  loss_rpn_loc: 0.01377    time: 0.5757  last_time: 0.6204  data_time: 0.0146  last_data_time: 0.0247   lr: 0.00013487  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:19:01 d2.utils.events]: \u001b[0m eta: 0:57:39  iter: 559  total_loss: 0.4811  loss_cls: 0.2701  loss_box_reg: 0.1601  loss_rpn_cls: 0.04138  loss_rpn_loc: 0.01317    time: 0.5778  last_time: 0.7493  data_time: 0.0131  last_data_time: 0.0203   lr: 0.00013986  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:19:13 d2.utils.events]: \u001b[0m eta: 0:57:38  iter: 579  total_loss: 0.568  loss_cls: 0.3374  loss_box_reg: 0.1837  loss_rpn_cls: 0.0343  loss_rpn_loc: 0.01736    time: 0.5802  last_time: 0.7096  data_time: 0.0136  last_data_time: 0.0031   lr: 0.00014486  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:19:26 d2.utils.events]: \u001b[0m eta: 0:57:46  iter: 599  total_loss: 0.5907  loss_cls: 0.3489  loss_box_reg: 0.1917  loss_rpn_cls: 0.03407  loss_rpn_loc: 0.01517    time: 0.5819  last_time: 0.5969  data_time: 0.0144  last_data_time: 0.0034   lr: 0.00014985  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:19:39 d2.utils.events]: \u001b[0m eta: 0:57:36  iter: 619  total_loss: 0.4871  loss_cls: 0.2635  loss_box_reg: 0.1543  loss_rpn_cls: 0.03291  loss_rpn_loc: 0.01766    time: 0.5832  last_time: 0.5496  data_time: 0.0125  last_data_time: 0.0125   lr: 0.00015485  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:19:52 d2.utils.events]: \u001b[0m eta: 0:57:35  iter: 639  total_loss: 0.3161  loss_cls: 0.175  loss_box_reg: 0.1109  loss_rpn_cls: 0.02443  loss_rpn_loc: 0.01202    time: 0.5856  last_time: 0.7337  data_time: 0.0147  last_data_time: 0.0251   lr: 0.00015984  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:20:05 d2.utils.events]: \u001b[0m eta: 0:57:31  iter: 659  total_loss: 0.4602  loss_cls: 0.2632  loss_box_reg: 0.1609  loss_rpn_cls: 0.02181  loss_rpn_loc: 0.01192    time: 0.5874  last_time: 0.6181  data_time: 0.0164  last_data_time: 0.0235   lr: 0.00016484  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:20:18 d2.utils.events]: \u001b[0m eta: 0:57:28  iter: 679  total_loss: 0.5793  loss_cls: 0.2995  loss_box_reg: 0.1903  loss_rpn_cls: 0.04679  loss_rpn_loc: 0.01904    time: 0.5904  last_time: 0.6226  data_time: 0.0128  last_data_time: 0.0099   lr: 0.00016983  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:20:31 d2.utils.events]: \u001b[0m eta: 0:57:28  iter: 699  total_loss: 0.4834  loss_cls: 0.2344  loss_box_reg: 0.1507  loss_rpn_cls: 0.02447  loss_rpn_loc: 0.01295    time: 0.5920  last_time: 0.5960  data_time: 0.0143  last_data_time: 0.0031   lr: 0.00017483  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:20:45 d2.utils.events]: \u001b[0m eta: 0:57:25  iter: 719  total_loss: 0.3622  loss_cls: 0.2061  loss_box_reg: 0.1247  loss_rpn_cls: 0.02802  loss_rpn_loc: 0.008502    time: 0.5937  last_time: 0.7363  data_time: 0.0077  last_data_time: 0.0195   lr: 0.00017982  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:20:58 d2.utils.events]: \u001b[0m eta: 0:57:21  iter: 739  total_loss: 0.5325  loss_cls: 0.3038  loss_box_reg: 0.1719  loss_rpn_cls: 0.03916  loss_rpn_loc: 0.01357    time: 0.5955  last_time: 0.6822  data_time: 0.0169  last_data_time: 0.0079   lr: 0.00018482  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:21:11 d2.utils.events]: \u001b[0m eta: 0:57:24  iter: 759  total_loss: 0.509  loss_cls: 0.2597  loss_box_reg: 0.156  loss_rpn_cls: 0.0312  loss_rpn_loc: 0.01968    time: 0.5975  last_time: 0.6491  data_time: 0.0155  last_data_time: 0.0191   lr: 0.00018981  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:21:24 d2.utils.events]: \u001b[0m eta: 0:57:18  iter: 779  total_loss: 0.4814  loss_cls: 0.261  loss_box_reg: 0.151  loss_rpn_cls: 0.04476  loss_rpn_loc: 0.01327    time: 0.5983  last_time: 0.6111  data_time: 0.0098  last_data_time: 0.0067   lr: 0.00019481  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:21:35 d2.utils.events]: \u001b[0m eta: 0:57:04  iter: 799  total_loss: 0.3863  loss_cls: 0.2068  loss_box_reg: 0.1061  loss_rpn_cls: 0.02906  loss_rpn_loc: 0.01411    time: 0.5975  last_time: 0.5501  data_time: 0.0109  last_data_time: 0.0040   lr: 0.0001998  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:21:47 d2.utils.events]: \u001b[0m eta: 0:56:43  iter: 819  total_loss: 0.4274  loss_cls: 0.2367  loss_box_reg: 0.1452  loss_rpn_cls: 0.02392  loss_rpn_loc: 0.01603    time: 0.5969  last_time: 0.5274  data_time: 0.0154  last_data_time: 0.0070   lr: 0.0002048  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:21:58 d2.utils.events]: \u001b[0m eta: 0:56:19  iter: 839  total_loss: 0.5436  loss_cls: 0.2743  loss_box_reg: 0.1866  loss_rpn_cls: 0.03883  loss_rpn_loc: 0.01441    time: 0.5961  last_time: 0.5751  data_time: 0.0126  last_data_time: 0.0036   lr: 0.00020979  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:22:09 d2.utils.events]: \u001b[0m eta: 0:56:03  iter: 859  total_loss: 0.4477  loss_cls: 0.249  loss_box_reg: 0.1479  loss_rpn_cls: 0.02421  loss_rpn_loc: 0.01859    time: 0.5954  last_time: 0.5164  data_time: 0.0147  last_data_time: 0.0051   lr: 0.00021479  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:22:21 d2.utils.events]: \u001b[0m eta: 0:55:52  iter: 879  total_loss: 0.5093  loss_cls: 0.2903  loss_box_reg: 0.1555  loss_rpn_cls: 0.02576  loss_rpn_loc: 0.01807    time: 0.5953  last_time: 0.6072  data_time: 0.0161  last_data_time: 0.0247   lr: 0.00021978  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:22:33 d2.utils.events]: \u001b[0m eta: 0:55:41  iter: 899  total_loss: 0.4354  loss_cls: 0.2673  loss_box_reg: 0.1508  loss_rpn_cls: 0.02052  loss_rpn_loc: 0.01371    time: 0.5950  last_time: 0.5328  data_time: 0.0152  last_data_time: 0.0036   lr: 0.00022478  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:22:44 d2.utils.events]: \u001b[0m eta: 0:55:27  iter: 919  total_loss: 0.596  loss_cls: 0.3425  loss_box_reg: 0.1986  loss_rpn_cls: 0.03743  loss_rpn_loc: 0.02387    time: 0.5942  last_time: 0.4378  data_time: 0.0116  last_data_time: 0.0035   lr: 0.00022977  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:22:55 d2.utils.events]: \u001b[0m eta: 0:55:10  iter: 939  total_loss: 0.5675  loss_cls: 0.2846  loss_box_reg: 0.2044  loss_rpn_cls: 0.0419  loss_rpn_loc: 0.0185    time: 0.5934  last_time: 0.5991  data_time: 0.0134  last_data_time: 0.0037   lr: 0.00023477  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:23:07 d2.utils.events]: \u001b[0m eta: 0:54:58  iter: 959  total_loss: 0.4389  loss_cls: 0.2257  loss_box_reg: 0.1531  loss_rpn_cls: 0.02941  loss_rpn_loc: 0.01424    time: 0.5931  last_time: 0.5441  data_time: 0.0192  last_data_time: 0.0036   lr: 0.00023976  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:23:18 d2.utils.events]: \u001b[0m eta: 0:54:44  iter: 979  total_loss: 0.4807  loss_cls: 0.2839  loss_box_reg: 0.168  loss_rpn_cls: 0.02356  loss_rpn_loc: 0.01101    time: 0.5925  last_time: 0.5698  data_time: 0.0144  last_data_time: 0.0141   lr: 0.00024476  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:23:29 d2.utils.events]: \u001b[0m eta: 0:54:30  iter: 999  total_loss: 0.4418  loss_cls: 0.2668  loss_box_reg: 0.151  loss_rpn_cls: 0.03387  loss_rpn_loc: 0.0122    time: 0.5921  last_time: 0.4960  data_time: 0.0129  last_data_time: 0.0194   lr: 0.00024975  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:23:41 d2.utils.events]: \u001b[0m eta: 0:54:15  iter: 1019  total_loss: 0.3171  loss_cls: 0.1631  loss_box_reg: 0.1333  loss_rpn_cls: 0.01403  loss_rpn_loc: 0.008105    time: 0.5916  last_time: 0.5333  data_time: 0.0169  last_data_time: 0.0341   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:23:52 d2.utils.events]: \u001b[0m eta: 0:54:06  iter: 1039  total_loss: 0.6219  loss_cls: 0.3445  loss_box_reg: 0.2227  loss_rpn_cls: 0.0351  loss_rpn_loc: 0.01778    time: 0.5912  last_time: 0.6062  data_time: 0.0145  last_data_time: 0.0263   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:24:04 d2.utils.events]: \u001b[0m eta: 0:53:53  iter: 1059  total_loss: 0.4714  loss_cls: 0.2599  loss_box_reg: 0.1745  loss_rpn_cls: 0.03187  loss_rpn_loc: 0.01306    time: 0.5908  last_time: 0.5899  data_time: 0.0126  last_data_time: 0.0160   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:24:15 d2.utils.events]: \u001b[0m eta: 0:53:42  iter: 1079  total_loss: 0.599  loss_cls: 0.3161  loss_box_reg: 0.2207  loss_rpn_cls: 0.02888  loss_rpn_loc: 0.01703    time: 0.5906  last_time: 0.5641  data_time: 0.0164  last_data_time: 0.0149   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:24:26 d2.utils.events]: \u001b[0m eta: 0:53:27  iter: 1099  total_loss: 0.4382  loss_cls: 0.246  loss_box_reg: 0.142  loss_rpn_cls: 0.01904  loss_rpn_loc: 0.01286    time: 0.5900  last_time: 0.5436  data_time: 0.0176  last_data_time: 0.0297   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:24:38 d2.utils.events]: \u001b[0m eta: 0:53:12  iter: 1119  total_loss: 0.5803  loss_cls: 0.3035  loss_box_reg: 0.2  loss_rpn_cls: 0.03529  loss_rpn_loc: 0.01542    time: 0.5895  last_time: 0.5566  data_time: 0.0138  last_data_time: 0.0224   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:24:49 d2.utils.events]: \u001b[0m eta: 0:53:00  iter: 1139  total_loss: 0.3997  loss_cls: 0.2317  loss_box_reg: 0.1353  loss_rpn_cls: 0.026  loss_rpn_loc: 0.01458    time: 0.5890  last_time: 0.5672  data_time: 0.0134  last_data_time: 0.0114   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:25:00 d2.utils.events]: \u001b[0m eta: 0:52:44  iter: 1159  total_loss: 0.4237  loss_cls: 0.2263  loss_box_reg: 0.1374  loss_rpn_cls: 0.02478  loss_rpn_loc: 0.01323    time: 0.5887  last_time: 0.4412  data_time: 0.0154  last_data_time: 0.0039   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:25:12 d2.utils.events]: \u001b[0m eta: 0:52:32  iter: 1179  total_loss: 0.4956  loss_cls: 0.2703  loss_box_reg: 0.1868  loss_rpn_cls: 0.02584  loss_rpn_loc: 0.01714    time: 0.5885  last_time: 0.5691  data_time: 0.0152  last_data_time: 0.0264   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:25:23 d2.utils.events]: \u001b[0m eta: 0:52:25  iter: 1199  total_loss: 0.4309  loss_cls: 0.2262  loss_box_reg: 0.1436  loss_rpn_cls: 0.03659  loss_rpn_loc: 0.02206    time: 0.5882  last_time: 0.6201  data_time: 0.0166  last_data_time: 0.0045   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:25:35 d2.utils.events]: \u001b[0m eta: 0:52:13  iter: 1219  total_loss: 0.5347  loss_cls: 0.2938  loss_box_reg: 0.1653  loss_rpn_cls: 0.03318  loss_rpn_loc: 0.01682    time: 0.5881  last_time: 0.6230  data_time: 0.0171  last_data_time: 0.0160   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:25:46 d2.utils.events]: \u001b[0m eta: 0:52:02  iter: 1239  total_loss: 0.4202  loss_cls: 0.2508  loss_box_reg: 0.1384  loss_rpn_cls: 0.03071  loss_rpn_loc: 0.01182    time: 0.5879  last_time: 0.5800  data_time: 0.0150  last_data_time: 0.0085   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:25:58 d2.utils.events]: \u001b[0m eta: 0:51:51  iter: 1259  total_loss: 0.4448  loss_cls: 0.2496  loss_box_reg: 0.1612  loss_rpn_cls: 0.02951  loss_rpn_loc: 0.01244    time: 0.5878  last_time: 0.4867  data_time: 0.0154  last_data_time: 0.0134   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:26:10 d2.utils.events]: \u001b[0m eta: 0:51:39  iter: 1279  total_loss: 0.4487  loss_cls: 0.2438  loss_box_reg: 0.1568  loss_rpn_cls: 0.01994  loss_rpn_loc: 0.01319    time: 0.5875  last_time: 0.6207  data_time: 0.0185  last_data_time: 0.0261   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:26:21 d2.utils.events]: \u001b[0m eta: 0:51:27  iter: 1299  total_loss: 0.4641  loss_cls: 0.2742  loss_box_reg: 0.1618  loss_rpn_cls: 0.0213  loss_rpn_loc: 0.01449    time: 0.5872  last_time: 0.5156  data_time: 0.0164  last_data_time: 0.0245   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:26:33 d2.utils.events]: \u001b[0m eta: 0:51:18  iter: 1319  total_loss: 0.4047  loss_cls: 0.2381  loss_box_reg: 0.1296  loss_rpn_cls: 0.02039  loss_rpn_loc: 0.01217    time: 0.5873  last_time: 0.5838  data_time: 0.0151  last_data_time: 0.0237   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:26:44 d2.utils.events]: \u001b[0m eta: 0:51:06  iter: 1339  total_loss: 0.3967  loss_cls: 0.2043  loss_box_reg: 0.1331  loss_rpn_cls: 0.02392  loss_rpn_loc: 0.01375    time: 0.5872  last_time: 0.5269  data_time: 0.0142  last_data_time: 0.0258   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:26:56 d2.utils.events]: \u001b[0m eta: 0:50:55  iter: 1359  total_loss: 0.436  loss_cls: 0.2515  loss_box_reg: 0.1427  loss_rpn_cls: 0.01417  loss_rpn_loc: 0.01152    time: 0.5871  last_time: 0.5559  data_time: 0.0144  last_data_time: 0.0032   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:27:07 d2.utils.events]: \u001b[0m eta: 0:50:42  iter: 1379  total_loss: 0.4738  loss_cls: 0.2728  loss_box_reg: 0.1875  loss_rpn_cls: 0.01735  loss_rpn_loc: 0.01447    time: 0.5867  last_time: 0.3957  data_time: 0.0168  last_data_time: 0.0147   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:27:19 d2.utils.events]: \u001b[0m eta: 0:50:35  iter: 1399  total_loss: 0.4412  loss_cls: 0.2471  loss_box_reg: 0.1734  loss_rpn_cls: 0.02005  loss_rpn_loc: 0.01315    time: 0.5868  last_time: 0.6124  data_time: 0.0145  last_data_time: 0.0043   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:27:30 d2.utils.events]: \u001b[0m eta: 0:50:19  iter: 1419  total_loss: 0.55  loss_cls: 0.3167  loss_box_reg: 0.1884  loss_rpn_cls: 0.02709  loss_rpn_loc: 0.01002    time: 0.5863  last_time: 0.5727  data_time: 0.0125  last_data_time: 0.0157   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:27:41 d2.utils.events]: \u001b[0m eta: 0:50:04  iter: 1439  total_loss: 0.467  loss_cls: 0.2576  loss_box_reg: 0.1557  loss_rpn_cls: 0.02527  loss_rpn_loc: 0.01083    time: 0.5860  last_time: 0.5634  data_time: 0.0154  last_data_time: 0.0174   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:27:53 d2.utils.events]: \u001b[0m eta: 0:49:53  iter: 1459  total_loss: 0.5302  loss_cls: 0.262  loss_box_reg: 0.1667  loss_rpn_cls: 0.02463  loss_rpn_loc: 0.01595    time: 0.5859  last_time: 0.5500  data_time: 0.0116  last_data_time: 0.0068   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:28:05 d2.utils.events]: \u001b[0m eta: 0:49:44  iter: 1479  total_loss: 0.4557  loss_cls: 0.2363  loss_box_reg: 0.1889  loss_rpn_cls: 0.02498  loss_rpn_loc: 0.01227    time: 0.5859  last_time: 0.6419  data_time: 0.0135  last_data_time: 0.0094   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:28:16 d2.utils.events]: \u001b[0m eta: 0:49:29  iter: 1499  total_loss: 0.4807  loss_cls: 0.2597  loss_box_reg: 0.1732  loss_rpn_cls: 0.02571  loss_rpn_loc: 0.01308    time: 0.5858  last_time: 0.5479  data_time: 0.0150  last_data_time: 0.0325   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:28:24 d2.utils.events]: \u001b[0m eta: 0:49:10  iter: 1519  total_loss: 0.4827  loss_cls: 0.2572  loss_box_reg: 0.1695  loss_rpn_cls: 0.02552  loss_rpn_loc: 0.01574    time: 0.5832  last_time: 0.1796  data_time: 0.0177  last_data_time: 0.0157   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:28:28 d2.utils.events]: \u001b[0m eta: 0:48:42  iter: 1539  total_loss: 0.5546  loss_cls: 0.3129  loss_box_reg: 0.1888  loss_rpn_cls: 0.02074  loss_rpn_loc: 0.01356    time: 0.5781  last_time: 0.1617  data_time: 0.0126  last_data_time: 0.0084   lr: 0.00025  max_mem: 1741M\n",
      "\u001b[32m[03/11 13:28:32 d2.utils.events]: \u001b[0m eta: 0:48:21  iter: 1559  total_loss: 0.5067  loss_cls: 0.2657  loss_box_reg: 0.1864  loss_rpn_cls: 0.02776  loss_rpn_loc: 0.01274    time: 0.5730  last_time: 0.1813  data_time: 0.0127  last_data_time: 0.0047   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:28:35 d2.utils.events]: \u001b[0m eta: 0:47:57  iter: 1579  total_loss: 0.5155  loss_cls: 0.2916  loss_box_reg: 0.1869  loss_rpn_cls: 0.02371  loss_rpn_loc: 0.01484    time: 0.5680  last_time: 0.1471  data_time: 0.0139  last_data_time: 0.0202   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:28:39 d2.utils.events]: \u001b[0m eta: 0:47:32  iter: 1599  total_loss: 0.5715  loss_cls: 0.3069  loss_box_reg: 0.2143  loss_rpn_cls: 0.02308  loss_rpn_loc: 0.01298    time: 0.5632  last_time: 0.1825  data_time: 0.0123  last_data_time: 0.0095   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:28:43 d2.utils.events]: \u001b[0m eta: 0:47:11  iter: 1619  total_loss: 0.4783  loss_cls: 0.2588  loss_box_reg: 0.1497  loss_rpn_cls: 0.02525  loss_rpn_loc: 0.01452    time: 0.5585  last_time: 0.2031  data_time: 0.0118  last_data_time: 0.0203   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:28:47 d2.utils.events]: \u001b[0m eta: 0:46:43  iter: 1639  total_loss: 0.5011  loss_cls: 0.2666  loss_box_reg: 0.1726  loss_rpn_cls: 0.01974  loss_rpn_loc: 0.01097    time: 0.5542  last_time: 0.1809  data_time: 0.0113  last_data_time: 0.0076   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:28:51 d2.utils.events]: \u001b[0m eta: 0:46:18  iter: 1659  total_loss: 0.426  loss_cls: 0.2434  loss_box_reg: 0.1638  loss_rpn_cls: 0.02918  loss_rpn_loc: 0.01894    time: 0.5499  last_time: 0.2186  data_time: 0.0159  last_data_time: 0.0097   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:28:55 d2.utils.events]: \u001b[0m eta: 0:45:55  iter: 1679  total_loss: 0.4295  loss_cls: 0.2439  loss_box_reg: 0.1682  loss_rpn_cls: 0.02175  loss_rpn_loc: 0.01229    time: 0.5457  last_time: 0.2154  data_time: 0.0151  last_data_time: 0.0154   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:28:58 d2.utils.events]: \u001b[0m eta: 0:45:32  iter: 1699  total_loss: 0.3937  loss_cls: 0.2198  loss_box_reg: 0.1263  loss_rpn_cls: 0.02336  loss_rpn_loc: 0.01017    time: 0.5413  last_time: 0.1676  data_time: 0.0054  last_data_time: 0.0032   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:29:02 d2.utils.events]: \u001b[0m eta: 0:45:09  iter: 1719  total_loss: 0.4355  loss_cls: 0.2361  loss_box_reg: 0.1504  loss_rpn_cls: 0.01754  loss_rpn_loc: 0.01306    time: 0.5372  last_time: 0.1753  data_time: 0.0089  last_data_time: 0.0035   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:29:10 d2.utils.events]: \u001b[0m eta: 0:44:44  iter: 1739  total_loss: 0.5504  loss_cls: 0.2942  loss_box_reg: 0.2042  loss_rpn_cls: 0.02197  loss_rpn_loc: 0.01784    time: 0.5357  last_time: 0.5449  data_time: 0.0089  last_data_time: 0.0034   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:29:22 d2.utils.events]: \u001b[0m eta: 0:44:31  iter: 1759  total_loss: 0.5814  loss_cls: 0.333  loss_box_reg: 0.1897  loss_rpn_cls: 0.0254  loss_rpn_loc: 0.01132    time: 0.5362  last_time: 0.6350  data_time: 0.0116  last_data_time: 0.0034   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:29:33 d2.utils.events]: \u001b[0m eta: 0:44:18  iter: 1779  total_loss: 0.5454  loss_cls: 0.2973  loss_box_reg: 0.1938  loss_rpn_cls: 0.02894  loss_rpn_loc: 0.01423    time: 0.5366  last_time: 0.6108  data_time: 0.0154  last_data_time: 0.0261   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:29:45 d2.utils.events]: \u001b[0m eta: 0:44:08  iter: 1799  total_loss: 0.4214  loss_cls: 0.2286  loss_box_reg: 0.1561  loss_rpn_cls: 0.017  loss_rpn_loc: 0.007585    time: 0.5370  last_time: 0.6232  data_time: 0.0145  last_data_time: 0.0173   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:29:56 d2.utils.events]: \u001b[0m eta: 0:43:55  iter: 1819  total_loss: 0.4775  loss_cls: 0.2537  loss_box_reg: 0.1972  loss_rpn_cls: 0.02273  loss_rpn_loc: 0.01475    time: 0.5371  last_time: 0.5549  data_time: 0.0129  last_data_time: 0.0041   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:30:07 d2.utils.events]: \u001b[0m eta: 0:43:46  iter: 1839  total_loss: 0.4953  loss_cls: 0.2532  loss_box_reg: 0.1761  loss_rpn_cls: 0.0237  loss_rpn_loc: 0.01462    time: 0.5375  last_time: 0.5935  data_time: 0.0095  last_data_time: 0.0153   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:30:19 d2.utils.events]: \u001b[0m eta: 0:43:36  iter: 1859  total_loss: 0.3919  loss_cls: 0.202  loss_box_reg: 0.1442  loss_rpn_cls: 0.0157  loss_rpn_loc: 0.01433    time: 0.5379  last_time: 0.5689  data_time: 0.0149  last_data_time: 0.0035   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:30:30 d2.utils.events]: \u001b[0m eta: 0:43:19  iter: 1879  total_loss: 0.4606  loss_cls: 0.2734  loss_box_reg: 0.1538  loss_rpn_cls: 0.02104  loss_rpn_loc: 0.0145    time: 0.5382  last_time: 0.6475  data_time: 0.0114  last_data_time: 0.0095   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:30:41 d2.utils.events]: \u001b[0m eta: 0:43:06  iter: 1899  total_loss: 0.4398  loss_cls: 0.2483  loss_box_reg: 0.1703  loss_rpn_cls: 0.02124  loss_rpn_loc: 0.01031    time: 0.5385  last_time: 0.5646  data_time: 0.0157  last_data_time: 0.0228   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:30:53 d2.utils.events]: \u001b[0m eta: 0:42:57  iter: 1919  total_loss: 0.4526  loss_cls: 0.2462  loss_box_reg: 0.1574  loss_rpn_cls: 0.02026  loss_rpn_loc: 0.01078    time: 0.5389  last_time: 0.5837  data_time: 0.0131  last_data_time: 0.0256   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:31:04 d2.utils.events]: \u001b[0m eta: 0:42:50  iter: 1939  total_loss: 0.5494  loss_cls: 0.2775  loss_box_reg: 0.2031  loss_rpn_cls: 0.02607  loss_rpn_loc: 0.01333    time: 0.5393  last_time: 0.5686  data_time: 0.0132  last_data_time: 0.0135   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:31:16 d2.utils.events]: \u001b[0m eta: 0:42:37  iter: 1959  total_loss: 0.4687  loss_cls: 0.2547  loss_box_reg: 0.185  loss_rpn_cls: 0.01639  loss_rpn_loc: 0.009176    time: 0.5396  last_time: 0.5377  data_time: 0.0159  last_data_time: 0.0157   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:31:27 d2.utils.events]: \u001b[0m eta: 0:42:28  iter: 1979  total_loss: 0.5218  loss_cls: 0.2771  loss_box_reg: 0.1768  loss_rpn_cls: 0.02688  loss_rpn_loc: 0.01908    time: 0.5400  last_time: 0.5608  data_time: 0.0126  last_data_time: 0.0152   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:31:39 d2.utils.events]: \u001b[0m eta: 0:42:17  iter: 1999  total_loss: 0.4145  loss_cls: 0.2186  loss_box_reg: 0.157  loss_rpn_cls: 0.02423  loss_rpn_loc: 0.0127    time: 0.5405  last_time: 0.6255  data_time: 0.0103  last_data_time: 0.0091   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:31:52 d2.utils.events]: \u001b[0m eta: 0:42:10  iter: 2019  total_loss: 0.4659  loss_cls: 0.236  loss_box_reg: 0.1654  loss_rpn_cls: 0.02368  loss_rpn_loc: 0.01424    time: 0.5415  last_time: 0.6961  data_time: 0.0121  last_data_time: 0.0119   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:32:06 d2.utils.events]: \u001b[0m eta: 0:42:04  iter: 2039  total_loss: 0.3699  loss_cls: 0.2042  loss_box_reg: 0.1328  loss_rpn_cls: 0.02325  loss_rpn_loc: 0.01311    time: 0.5430  last_time: 0.7852  data_time: 0.0161  last_data_time: 0.0226   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:32:19 d2.utils.events]: \u001b[0m eta: 0:41:55  iter: 2059  total_loss: 0.4074  loss_cls: 0.2255  loss_box_reg: 0.1354  loss_rpn_cls: 0.02008  loss_rpn_loc: 0.008234    time: 0.5443  last_time: 0.3692  data_time: 0.0159  last_data_time: 0.0144   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:32:33 d2.utils.events]: \u001b[0m eta: 0:41:47  iter: 2079  total_loss: 0.3953  loss_cls: 0.2095  loss_box_reg: 0.1378  loss_rpn_cls: 0.02616  loss_rpn_loc: 0.01175    time: 0.5455  last_time: 0.6594  data_time: 0.0160  last_data_time: 0.0045   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:32:46 d2.utils.events]: \u001b[0m eta: 0:41:42  iter: 2099  total_loss: 0.6281  loss_cls: 0.3268  loss_box_reg: 0.2024  loss_rpn_cls: 0.02279  loss_rpn_loc: 0.01233    time: 0.5466  last_time: 0.6435  data_time: 0.0122  last_data_time: 0.0031   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:33:00 d2.utils.events]: \u001b[0m eta: 0:41:36  iter: 2119  total_loss: 0.4632  loss_cls: 0.24  loss_box_reg: 0.1713  loss_rpn_cls: 0.02365  loss_rpn_loc: 0.008885    time: 0.5478  last_time: 0.6503  data_time: 0.0163  last_data_time: 0.0250   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:33:13 d2.utils.events]: \u001b[0m eta: 0:41:29  iter: 2139  total_loss: 0.4658  loss_cls: 0.2427  loss_box_reg: 0.1853  loss_rpn_cls: 0.0203  loss_rpn_loc: 0.01487    time: 0.5491  last_time: 0.8627  data_time: 0.0149  last_data_time: 0.0327   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:33:26 d2.utils.events]: \u001b[0m eta: 0:41:24  iter: 2159  total_loss: 0.4534  loss_cls: 0.2464  loss_box_reg: 0.1634  loss_rpn_cls: 0.01844  loss_rpn_loc: 0.01017    time: 0.5499  last_time: 0.6612  data_time: 0.0139  last_data_time: 0.0137   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:33:39 d2.utils.events]: \u001b[0m eta: 0:41:17  iter: 2179  total_loss: 0.4642  loss_cls: 0.2591  loss_box_reg: 0.1609  loss_rpn_cls: 0.01865  loss_rpn_loc: 0.01283    time: 0.5508  last_time: 0.6418  data_time: 0.0137  last_data_time: 0.0051   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:33:52 d2.utils.events]: \u001b[0m eta: 0:41:09  iter: 2199  total_loss: 0.4973  loss_cls: 0.2685  loss_box_reg: 0.184  loss_rpn_cls: 0.02279  loss_rpn_loc: 0.01226    time: 0.5515  last_time: 0.6128  data_time: 0.0138  last_data_time: 0.0218   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:34:05 d2.utils.events]: \u001b[0m eta: 0:40:59  iter: 2219  total_loss: 0.5567  loss_cls: 0.2795  loss_box_reg: 0.1954  loss_rpn_cls: 0.02678  loss_rpn_loc: 0.01815    time: 0.5524  last_time: 0.6605  data_time: 0.0118  last_data_time: 0.0032   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:34:18 d2.utils.events]: \u001b[0m eta: 0:40:54  iter: 2239  total_loss: 0.4992  loss_cls: 0.278  loss_box_reg: 0.1855  loss_rpn_cls: 0.02343  loss_rpn_loc: 0.01374    time: 0.5533  last_time: 0.7681  data_time: 0.0152  last_data_time: 0.0139   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:34:31 d2.utils.events]: \u001b[0m eta: 0:40:46  iter: 2259  total_loss: 0.5099  loss_cls: 0.2578  loss_box_reg: 0.1577  loss_rpn_cls: 0.02238  loss_rpn_loc: 0.01662    time: 0.5542  last_time: 0.6281  data_time: 0.0153  last_data_time: 0.0164   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:34:44 d2.utils.events]: \u001b[0m eta: 0:40:39  iter: 2279  total_loss: 0.5078  loss_cls: 0.2733  loss_box_reg: 0.1886  loss_rpn_cls: 0.02427  loss_rpn_loc: 0.0172    time: 0.5549  last_time: 0.7174  data_time: 0.0117  last_data_time: 0.0076   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:34:57 d2.utils.events]: \u001b[0m eta: 0:40:31  iter: 2299  total_loss: 0.5421  loss_cls: 0.3039  loss_box_reg: 0.2028  loss_rpn_cls: 0.01873  loss_rpn_loc: 0.01228    time: 0.5558  last_time: 0.5503  data_time: 0.0146  last_data_time: 0.0033   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:35:09 d2.utils.events]: \u001b[0m eta: 0:40:19  iter: 2319  total_loss: 0.4525  loss_cls: 0.2257  loss_box_reg: 0.141  loss_rpn_cls: 0.02284  loss_rpn_loc: 0.01098    time: 0.5561  last_time: 0.5125  data_time: 0.0132  last_data_time: 0.0031   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:35:20 d2.utils.events]: \u001b[0m eta: 0:40:13  iter: 2339  total_loss: 0.3338  loss_cls: 0.1966  loss_box_reg: 0.1193  loss_rpn_cls: 0.009989  loss_rpn_loc: 0.01017    time: 0.5563  last_time: 0.5469  data_time: 0.0157  last_data_time: 0.0039   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:35:31 d2.utils.events]: \u001b[0m eta: 0:40:01  iter: 2359  total_loss: 0.4503  loss_cls: 0.2431  loss_box_reg: 0.1814  loss_rpn_cls: 0.022  loss_rpn_loc: 0.01158    time: 0.5563  last_time: 0.6977  data_time: 0.0167  last_data_time: 0.0347   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:35:43 d2.utils.events]: \u001b[0m eta: 0:39:51  iter: 2379  total_loss: 0.4486  loss_cls: 0.2126  loss_box_reg: 0.1642  loss_rpn_cls: 0.03241  loss_rpn_loc: 0.01534    time: 0.5565  last_time: 0.5730  data_time: 0.0228  last_data_time: 0.0090   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:35:55 d2.utils.events]: \u001b[0m eta: 0:39:41  iter: 2399  total_loss: 0.4508  loss_cls: 0.251  loss_box_reg: 0.1526  loss_rpn_cls: 0.02557  loss_rpn_loc: 0.01286    time: 0.5571  last_time: 0.5598  data_time: 0.0155  last_data_time: 0.0033   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:36:07 d2.utils.events]: \u001b[0m eta: 0:39:31  iter: 2419  total_loss: 0.4279  loss_cls: 0.2316  loss_box_reg: 0.1777  loss_rpn_cls: 0.01746  loss_rpn_loc: 0.009922    time: 0.5572  last_time: 0.5188  data_time: 0.0096  last_data_time: 0.0151   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:36:18 d2.utils.events]: \u001b[0m eta: 0:39:23  iter: 2439  total_loss: 0.3249  loss_cls: 0.1904  loss_box_reg: 0.1097  loss_rpn_cls: 0.016  loss_rpn_loc: 0.009114    time: 0.5574  last_time: 0.5998  data_time: 0.0114  last_data_time: 0.0033   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:36:30 d2.utils.events]: \u001b[0m eta: 0:39:09  iter: 2459  total_loss: 0.3919  loss_cls: 0.2187  loss_box_reg: 0.1375  loss_rpn_cls: 0.01622  loss_rpn_loc: 0.0105    time: 0.5574  last_time: 0.5116  data_time: 0.0165  last_data_time: 0.0178   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:36:41 d2.utils.events]: \u001b[0m eta: 0:38:56  iter: 2479  total_loss: 0.5081  loss_cls: 0.2793  loss_box_reg: 0.1782  loss_rpn_cls: 0.02739  loss_rpn_loc: 0.01303    time: 0.5575  last_time: 0.5364  data_time: 0.0155  last_data_time: 0.0177   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:36:52 d2.utils.events]: \u001b[0m eta: 0:38:41  iter: 2499  total_loss: 0.5058  loss_cls: 0.2576  loss_box_reg: 0.164  loss_rpn_cls: 0.02411  loss_rpn_loc: 0.0156    time: 0.5574  last_time: 0.5102  data_time: 0.0106  last_data_time: 0.0068   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:37:05 d2.utils.events]: \u001b[0m eta: 0:38:41  iter: 2519  total_loss: 0.4258  loss_cls: 0.2431  loss_box_reg: 0.1465  loss_rpn_cls: 0.02424  loss_rpn_loc: 0.014    time: 0.5583  last_time: 0.6367  data_time: 0.0104  last_data_time: 0.0040   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:37:19 d2.utils.events]: \u001b[0m eta: 0:38:48  iter: 2539  total_loss: 0.4319  loss_cls: 0.2313  loss_box_reg: 0.1757  loss_rpn_cls: 0.02131  loss_rpn_loc: 0.01146    time: 0.5594  last_time: 0.6193  data_time: 0.0196  last_data_time: 0.0292   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:37:32 d2.utils.events]: \u001b[0m eta: 0:38:46  iter: 2559  total_loss: 0.3492  loss_cls: 0.2105  loss_box_reg: 0.1334  loss_rpn_cls: 0.01836  loss_rpn_loc: 0.01229    time: 0.5598  last_time: 0.8301  data_time: 0.0138  last_data_time: 0.0264   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:37:45 d2.utils.events]: \u001b[0m eta: 0:38:53  iter: 2579  total_loss: 0.3984  loss_cls: 0.2092  loss_box_reg: 0.1479  loss_rpn_cls: 0.0148  loss_rpn_loc: 0.01064    time: 0.5607  last_time: 0.6798  data_time: 0.0159  last_data_time: 0.0034   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:37:59 d2.utils.events]: \u001b[0m eta: 0:38:58  iter: 2599  total_loss: 0.4228  loss_cls: 0.2179  loss_box_reg: 0.1439  loss_rpn_cls: 0.01489  loss_rpn_loc: 0.007646    time: 0.5616  last_time: 0.7722  data_time: 0.0154  last_data_time: 0.0046   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:38:13 d2.utils.events]: \u001b[0m eta: 0:39:01  iter: 2619  total_loss: 0.3891  loss_cls: 0.207  loss_box_reg: 0.135  loss_rpn_cls: 0.0233  loss_rpn_loc: 0.01145    time: 0.5627  last_time: 0.6145  data_time: 0.0157  last_data_time: 0.0136   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:38:25 d2.utils.events]: \u001b[0m eta: 0:38:56  iter: 2639  total_loss: 0.5039  loss_cls: 0.2687  loss_box_reg: 0.1805  loss_rpn_cls: 0.02191  loss_rpn_loc: 0.01995    time: 0.5631  last_time: 0.6054  data_time: 0.0139  last_data_time: 0.0168   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:38:37 d2.utils.events]: \u001b[0m eta: 0:38:48  iter: 2659  total_loss: 0.3793  loss_cls: 0.202  loss_box_reg: 0.1531  loss_rpn_cls: 0.01708  loss_rpn_loc: 0.01307    time: 0.5632  last_time: 0.5411  data_time: 0.0140  last_data_time: 0.0129   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:38:48 d2.utils.events]: \u001b[0m eta: 0:38:39  iter: 2679  total_loss: 0.5548  loss_cls: 0.348  loss_box_reg: 0.1999  loss_rpn_cls: 0.02216  loss_rpn_loc: 0.01843    time: 0.5633  last_time: 0.5265  data_time: 0.0132  last_data_time: 0.0236   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:39:00 d2.utils.events]: \u001b[0m eta: 0:38:33  iter: 2699  total_loss: 0.3492  loss_cls: 0.1932  loss_box_reg: 0.1378  loss_rpn_cls: 0.01822  loss_rpn_loc: 0.009986    time: 0.5634  last_time: 0.5980  data_time: 0.0137  last_data_time: 0.0134   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:39:11 d2.utils.events]: \u001b[0m eta: 0:38:27  iter: 2719  total_loss: 0.4537  loss_cls: 0.2344  loss_box_reg: 0.1467  loss_rpn_cls: 0.01577  loss_rpn_loc: 0.01332    time: 0.5635  last_time: 0.5294  data_time: 0.0147  last_data_time: 0.0195   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:39:23 d2.utils.events]: \u001b[0m eta: 0:38:20  iter: 2739  total_loss: 0.4805  loss_cls: 0.2521  loss_box_reg: 0.1844  loss_rpn_cls: 0.02217  loss_rpn_loc: 0.01776    time: 0.5636  last_time: 0.4568  data_time: 0.0117  last_data_time: 0.0088   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:39:34 d2.utils.events]: \u001b[0m eta: 0:38:07  iter: 2759  total_loss: 0.3517  loss_cls: 0.1854  loss_box_reg: 0.1251  loss_rpn_cls: 0.01607  loss_rpn_loc: 0.01098    time: 0.5636  last_time: 0.5950  data_time: 0.0194  last_data_time: 0.0137   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:39:46 d2.utils.events]: \u001b[0m eta: 0:37:57  iter: 2779  total_loss: 0.4614  loss_cls: 0.2533  loss_box_reg: 0.1713  loss_rpn_cls: 0.01537  loss_rpn_loc: 0.009037    time: 0.5638  last_time: 0.5892  data_time: 0.0183  last_data_time: 0.0201   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:39:58 d2.utils.events]: \u001b[0m eta: 0:37:46  iter: 2799  total_loss: 0.6446  loss_cls: 0.3315  loss_box_reg: 0.2704  loss_rpn_cls: 0.02099  loss_rpn_loc: 0.0192    time: 0.5641  last_time: 0.5707  data_time: 0.0138  last_data_time: 0.0176   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:40:10 d2.utils.events]: \u001b[0m eta: 0:37:34  iter: 2819  total_loss: 0.4133  loss_cls: 0.2253  loss_box_reg: 0.1562  loss_rpn_cls: 0.01885  loss_rpn_loc: 0.01044    time: 0.5642  last_time: 0.5848  data_time: 0.0110  last_data_time: 0.0040   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:40:21 d2.utils.events]: \u001b[0m eta: 0:37:22  iter: 2839  total_loss: 0.337  loss_cls: 0.1728  loss_box_reg: 0.1256  loss_rpn_cls: 0.01543  loss_rpn_loc: 0.01131    time: 0.5642  last_time: 0.6126  data_time: 0.0158  last_data_time: 0.0173   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:40:33 d2.utils.events]: \u001b[0m eta: 0:37:10  iter: 2859  total_loss: 0.3356  loss_cls: 0.1861  loss_box_reg: 0.1213  loss_rpn_cls: 0.01409  loss_rpn_loc: 0.01365    time: 0.5644  last_time: 0.5943  data_time: 0.0148  last_data_time: 0.0179   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:40:45 d2.utils.events]: \u001b[0m eta: 0:37:00  iter: 2879  total_loss: 0.4696  loss_cls: 0.2407  loss_box_reg: 0.1676  loss_rpn_cls: 0.02817  loss_rpn_loc: 0.0163    time: 0.5645  last_time: 0.5638  data_time: 0.0141  last_data_time: 0.0192   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:40:56 d2.utils.events]: \u001b[0m eta: 0:36:50  iter: 2899  total_loss: 0.5085  loss_cls: 0.2473  loss_box_reg: 0.2134  loss_rpn_cls: 0.0239  loss_rpn_loc: 0.02161    time: 0.5647  last_time: 0.6196  data_time: 0.0156  last_data_time: 0.0152   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:41:08 d2.utils.events]: \u001b[0m eta: 0:36:39  iter: 2919  total_loss: 0.4219  loss_cls: 0.2078  loss_box_reg: 0.1476  loss_rpn_cls: 0.03247  loss_rpn_loc: 0.01055    time: 0.5649  last_time: 0.6318  data_time: 0.0136  last_data_time: 0.0040   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:41:20 d2.utils.events]: \u001b[0m eta: 0:36:31  iter: 2939  total_loss: 0.4514  loss_cls: 0.2548  loss_box_reg: 0.147  loss_rpn_cls: 0.02018  loss_rpn_loc: 0.01291    time: 0.5652  last_time: 0.6376  data_time: 0.0114  last_data_time: 0.0037   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:41:32 d2.utils.events]: \u001b[0m eta: 0:36:20  iter: 2959  total_loss: 0.5536  loss_cls: 0.3275  loss_box_reg: 0.1847  loss_rpn_cls: 0.02473  loss_rpn_loc: 0.01314    time: 0.5653  last_time: 0.5606  data_time: 0.0115  last_data_time: 0.0175   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:41:44 d2.utils.events]: \u001b[0m eta: 0:36:09  iter: 2979  total_loss: 0.4158  loss_cls: 0.2319  loss_box_reg: 0.1649  loss_rpn_cls: 0.01563  loss_rpn_loc: 0.01047    time: 0.5654  last_time: 0.5714  data_time: 0.0161  last_data_time: 0.0156   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:41:55 d2.utils.events]: \u001b[0m eta: 0:35:56  iter: 2999  total_loss: 0.349  loss_cls: 0.2131  loss_box_reg: 0.1462  loss_rpn_cls: 0.01481  loss_rpn_loc: 0.01033    time: 0.5655  last_time: 0.6238  data_time: 0.0124  last_data_time: 0.0118   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:42:07 d2.utils.events]: \u001b[0m eta: 0:35:38  iter: 3019  total_loss: 0.4817  loss_cls: 0.2526  loss_box_reg: 0.1775  loss_rpn_cls: 0.0255  loss_rpn_loc: 0.01341    time: 0.5655  last_time: 0.5636  data_time: 0.0163  last_data_time: 0.0084   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:42:18 d2.utils.events]: \u001b[0m eta: 0:35:21  iter: 3039  total_loss: 0.4366  loss_cls: 0.2578  loss_box_reg: 0.1543  loss_rpn_cls: 0.02184  loss_rpn_loc: 0.01237    time: 0.5656  last_time: 0.5900  data_time: 0.0130  last_data_time: 0.0037   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:42:30 d2.utils.events]: \u001b[0m eta: 0:35:03  iter: 3059  total_loss: 0.4459  loss_cls: 0.2527  loss_box_reg: 0.1647  loss_rpn_cls: 0.01634  loss_rpn_loc: 0.0153    time: 0.5657  last_time: 0.5145  data_time: 0.0163  last_data_time: 0.0037   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:42:42 d2.utils.events]: \u001b[0m eta: 0:34:40  iter: 3079  total_loss: 0.3805  loss_cls: 0.2057  loss_box_reg: 0.1393  loss_rpn_cls: 0.02119  loss_rpn_loc: 0.01097    time: 0.5659  last_time: 0.6090  data_time: 0.0168  last_data_time: 0.0152   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:42:54 d2.utils.events]: \u001b[0m eta: 0:34:24  iter: 3099  total_loss: 0.43  loss_cls: 0.2218  loss_box_reg: 0.1444  loss_rpn_cls: 0.01712  loss_rpn_loc: 0.01248    time: 0.5660  last_time: 0.4970  data_time: 0.0171  last_data_time: 0.0236   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:43:05 d2.utils.events]: \u001b[0m eta: 0:34:07  iter: 3119  total_loss: 0.4602  loss_cls: 0.2478  loss_box_reg: 0.1737  loss_rpn_cls: 0.01777  loss_rpn_loc: 0.01204    time: 0.5660  last_time: 0.5726  data_time: 0.0162  last_data_time: 0.0188   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:43:16 d2.utils.events]: \u001b[0m eta: 0:33:48  iter: 3139  total_loss: 0.3905  loss_cls: 0.2024  loss_box_reg: 0.14  loss_rpn_cls: 0.01755  loss_rpn_loc: 0.01452    time: 0.5660  last_time: 0.5973  data_time: 0.0147  last_data_time: 0.0077   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:43:28 d2.utils.events]: \u001b[0m eta: 0:33:32  iter: 3159  total_loss: 0.4556  loss_cls: 0.2625  loss_box_reg: 0.161  loss_rpn_cls: 0.02082  loss_rpn_loc: 0.01314    time: 0.5660  last_time: 0.5580  data_time: 0.0130  last_data_time: 0.0056   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:43:39 d2.utils.events]: \u001b[0m eta: 0:33:18  iter: 3179  total_loss: 0.4326  loss_cls: 0.2642  loss_box_reg: 0.1453  loss_rpn_cls: 0.02554  loss_rpn_loc: 0.01271    time: 0.5661  last_time: 0.5717  data_time: 0.0157  last_data_time: 0.0151   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:43:51 d2.utils.events]: \u001b[0m eta: 0:33:04  iter: 3199  total_loss: 0.4072  loss_cls: 0.2313  loss_box_reg: 0.1576  loss_rpn_cls: 0.02865  loss_rpn_loc: 0.01454    time: 0.5661  last_time: 0.6002  data_time: 0.0127  last_data_time: 0.0080   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:44:02 d2.utils.events]: \u001b[0m eta: 0:32:50  iter: 3219  total_loss: 0.3707  loss_cls: 0.2042  loss_box_reg: 0.1302  loss_rpn_cls: 0.01829  loss_rpn_loc: 0.01316    time: 0.5661  last_time: 0.5472  data_time: 0.0121  last_data_time: 0.0042   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:44:14 d2.utils.events]: \u001b[0m eta: 0:32:35  iter: 3239  total_loss: 0.4483  loss_cls: 0.23  loss_box_reg: 0.1484  loss_rpn_cls: 0.02356  loss_rpn_loc: 0.01635    time: 0.5663  last_time: 0.6450  data_time: 0.0171  last_data_time: 0.0032   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:44:25 d2.utils.events]: \u001b[0m eta: 0:32:17  iter: 3259  total_loss: 0.3723  loss_cls: 0.1892  loss_box_reg: 0.1261  loss_rpn_cls: 0.01879  loss_rpn_loc: 0.01081    time: 0.5663  last_time: 0.5805  data_time: 0.0139  last_data_time: 0.0037   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:44:37 d2.utils.events]: \u001b[0m eta: 0:32:04  iter: 3279  total_loss: 0.4063  loss_cls: 0.1828  loss_box_reg: 0.1236  loss_rpn_cls: 0.01643  loss_rpn_loc: 0.009464    time: 0.5664  last_time: 0.5619  data_time: 0.0163  last_data_time: 0.0276   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:44:48 d2.utils.events]: \u001b[0m eta: 0:31:46  iter: 3299  total_loss: 0.3853  loss_cls: 0.1802  loss_box_reg: 0.1492  loss_rpn_cls: 0.02023  loss_rpn_loc: 0.009923    time: 0.5664  last_time: 0.5768  data_time: 0.0152  last_data_time: 0.0143   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:45:00 d2.utils.events]: \u001b[0m eta: 0:31:36  iter: 3319  total_loss: 0.3746  loss_cls: 0.1939  loss_box_reg: 0.1485  loss_rpn_cls: 0.01345  loss_rpn_loc: 0.008159    time: 0.5665  last_time: 0.5514  data_time: 0.0157  last_data_time: 0.0268   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:45:11 d2.utils.events]: \u001b[0m eta: 0:31:25  iter: 3339  total_loss: 0.4128  loss_cls: 0.2248  loss_box_reg: 0.1507  loss_rpn_cls: 0.01782  loss_rpn_loc: 0.01186    time: 0.5665  last_time: 0.5405  data_time: 0.0181  last_data_time: 0.0150   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:45:23 d2.utils.events]: \u001b[0m eta: 0:31:12  iter: 3359  total_loss: 0.3974  loss_cls: 0.2193  loss_box_reg: 0.1538  loss_rpn_cls: 0.02017  loss_rpn_loc: 0.01518    time: 0.5665  last_time: 0.6560  data_time: 0.0141  last_data_time: 0.0289   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:45:31 d2.utils.events]: \u001b[0m eta: 0:31:00  iter: 3379  total_loss: 0.3522  loss_cls: 0.2038  loss_box_reg: 0.1339  loss_rpn_cls: 0.01968  loss_rpn_loc: 0.016    time: 0.5656  last_time: 0.1897  data_time: 0.0118  last_data_time: 0.0132   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:45:35 d2.utils.events]: \u001b[0m eta: 0:30:43  iter: 3399  total_loss: 0.4788  loss_cls: 0.2452  loss_box_reg: 0.1955  loss_rpn_cls: 0.02459  loss_rpn_loc: 0.01928    time: 0.5634  last_time: 0.2180  data_time: 0.0115  last_data_time: 0.0148   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:45:39 d2.utils.events]: \u001b[0m eta: 0:30:26  iter: 3419  total_loss: 0.4454  loss_cls: 0.2339  loss_box_reg: 0.1527  loss_rpn_cls: 0.01616  loss_rpn_loc: 0.01112    time: 0.5613  last_time: 0.2513  data_time: 0.0125  last_data_time: 0.0405   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:45:43 d2.utils.events]: \u001b[0m eta: 0:30:11  iter: 3439  total_loss: 0.4953  loss_cls: 0.2678  loss_box_reg: 0.2102  loss_rpn_cls: 0.02051  loss_rpn_loc: 0.01409    time: 0.5592  last_time: 0.1947  data_time: 0.0116  last_data_time: 0.0044   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:45:47 d2.utils.events]: \u001b[0m eta: 0:29:56  iter: 3459  total_loss: 0.3615  loss_cls: 0.1963  loss_box_reg: 0.1413  loss_rpn_cls: 0.0127  loss_rpn_loc: 0.007428    time: 0.5572  last_time: 0.2259  data_time: 0.0133  last_data_time: 0.0107   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:45:51 d2.utils.events]: \u001b[0m eta: 0:29:40  iter: 3479  total_loss: 0.373  loss_cls: 0.2168  loss_box_reg: 0.1325  loss_rpn_cls: 0.02023  loss_rpn_loc: 0.009175    time: 0.5552  last_time: 0.2065  data_time: 0.0117  last_data_time: 0.0170   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:45:59 d2.utils.events]: \u001b[0m eta: 0:29:29  iter: 3499  total_loss: 0.3848  loss_cls: 0.1996  loss_box_reg: 0.1403  loss_rpn_cls: 0.01293  loss_rpn_loc: 0.01072    time: 0.5542  last_time: 0.5527  data_time: 0.0131  last_data_time: 0.0150   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:46:13 d2.utils.events]: \u001b[0m eta: 0:29:19  iter: 3519  total_loss: 0.3123  loss_cls: 0.1723  loss_box_reg: 0.1038  loss_rpn_cls: 0.01251  loss_rpn_loc: 0.009386    time: 0.5549  last_time: 0.6496  data_time: 0.0133  last_data_time: 0.0059   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:46:26 d2.utils.events]: \u001b[0m eta: 0:29:06  iter: 3539  total_loss: 0.5349  loss_cls: 0.2713  loss_box_reg: 0.2074  loss_rpn_cls: 0.01827  loss_rpn_loc: 0.01599    time: 0.5555  last_time: 0.6718  data_time: 0.0142  last_data_time: 0.0200   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:46:39 d2.utils.events]: \u001b[0m eta: 0:28:56  iter: 3559  total_loss: 0.3959  loss_cls: 0.2252  loss_box_reg: 0.1443  loss_rpn_cls: 0.01184  loss_rpn_loc: 0.009197    time: 0.5561  last_time: 0.5411  data_time: 0.0174  last_data_time: 0.0114   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:46:52 d2.utils.events]: \u001b[0m eta: 0:28:43  iter: 3579  total_loss: 0.467  loss_cls: 0.2429  loss_box_reg: 0.1849  loss_rpn_cls: 0.01427  loss_rpn_loc: 0.01536    time: 0.5565  last_time: 0.5904  data_time: 0.0130  last_data_time: 0.0180   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:47:05 d2.utils.events]: \u001b[0m eta: 0:28:31  iter: 3599  total_loss: 0.5397  loss_cls: 0.2805  loss_box_reg: 0.2151  loss_rpn_cls: 0.01345  loss_rpn_loc: 0.01504    time: 0.5571  last_time: 0.7538  data_time: 0.0130  last_data_time: 0.0195   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:47:18 d2.utils.events]: \u001b[0m eta: 0:28:17  iter: 3619  total_loss: 0.4855  loss_cls: 0.2651  loss_box_reg: 0.1814  loss_rpn_cls: 0.015  loss_rpn_loc: 0.01403    time: 0.5577  last_time: 0.6234  data_time: 0.0152  last_data_time: 0.0070   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:47:31 d2.utils.events]: \u001b[0m eta: 0:28:06  iter: 3639  total_loss: 0.3402  loss_cls: 0.1822  loss_box_reg: 0.1216  loss_rpn_cls: 0.02054  loss_rpn_loc: 0.0159    time: 0.5582  last_time: 0.7170  data_time: 0.0127  last_data_time: 0.0231   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:47:44 d2.utils.events]: \u001b[0m eta: 0:27:55  iter: 3659  total_loss: 0.3828  loss_cls: 0.1784  loss_box_reg: 0.1244  loss_rpn_cls: 0.02  loss_rpn_loc: 0.011    time: 0.5585  last_time: 0.6301  data_time: 0.0097  last_data_time: 0.0032   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:47:57 d2.utils.events]: \u001b[0m eta: 0:27:48  iter: 3679  total_loss: 0.5798  loss_cls: 0.281  loss_box_reg: 0.1829  loss_rpn_cls: 0.02228  loss_rpn_loc: 0.01381    time: 0.5591  last_time: 0.5924  data_time: 0.0127  last_data_time: 0.0103   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:48:09 d2.utils.events]: \u001b[0m eta: 0:27:37  iter: 3699  total_loss: 0.5263  loss_cls: 0.274  loss_box_reg: 0.1997  loss_rpn_cls: 0.02061  loss_rpn_loc: 0.01267    time: 0.5595  last_time: 0.5872  data_time: 0.0206  last_data_time: 0.0177   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:48:23 d2.utils.events]: \u001b[0m eta: 0:27:31  iter: 3719  total_loss: 0.4612  loss_cls: 0.2324  loss_box_reg: 0.165  loss_rpn_cls: 0.02063  loss_rpn_loc: 0.01438    time: 0.5600  last_time: 0.6992  data_time: 0.0110  last_data_time: 0.0148   lr: 0.00025  max_mem: 1742M\n",
      "\u001b[32m[03/11 13:48:36 d2.utils.events]: \u001b[0m eta: 0:27:22  iter: 3739  total_loss: 0.4213  loss_cls: 0.2306  loss_box_reg: 0.1446  loss_rpn_cls: 0.01969  loss_rpn_loc: 0.01489    time: 0.5605  last_time: 0.8056  data_time: 0.0127  last_data_time: 0.0243   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:48:48 d2.utils.events]: \u001b[0m eta: 0:27:13  iter: 3759  total_loss: 0.4385  loss_cls: 0.2396  loss_box_reg: 0.1483  loss_rpn_cls: 0.01407  loss_rpn_loc: 0.009828    time: 0.5608  last_time: 0.5286  data_time: 0.0150  last_data_time: 0.0154   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:48:59 d2.utils.events]: \u001b[0m eta: 0:26:58  iter: 3779  total_loss: 0.4217  loss_cls: 0.2236  loss_box_reg: 0.1507  loss_rpn_cls: 0.02311  loss_rpn_loc: 0.01397    time: 0.5608  last_time: 0.5445  data_time: 0.0163  last_data_time: 0.0202   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:49:11 d2.utils.events]: \u001b[0m eta: 0:26:46  iter: 3799  total_loss: 0.5014  loss_cls: 0.25  loss_box_reg: 0.1615  loss_rpn_cls: 0.02668  loss_rpn_loc: 0.01464    time: 0.5609  last_time: 0.5894  data_time: 0.0175  last_data_time: 0.0222   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:49:22 d2.utils.events]: \u001b[0m eta: 0:26:33  iter: 3819  total_loss: 0.3896  loss_cls: 0.2334  loss_box_reg: 0.1332  loss_rpn_cls: 0.01975  loss_rpn_loc: 0.01046    time: 0.5609  last_time: 0.5605  data_time: 0.0134  last_data_time: 0.0057   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:49:34 d2.utils.events]: \u001b[0m eta: 0:26:23  iter: 3839  total_loss: 0.5198  loss_cls: 0.2756  loss_box_reg: 0.1764  loss_rpn_cls: 0.01973  loss_rpn_loc: 0.01203    time: 0.5610  last_time: 0.6606  data_time: 0.0156  last_data_time: 0.0283   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:49:45 d2.utils.events]: \u001b[0m eta: 0:26:11  iter: 3859  total_loss: 0.4411  loss_cls: 0.2361  loss_box_reg: 0.1523  loss_rpn_cls: 0.01691  loss_rpn_loc: 0.01211    time: 0.5610  last_time: 0.6265  data_time: 0.0117  last_data_time: 0.0282   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:49:57 d2.utils.events]: \u001b[0m eta: 0:26:00  iter: 3879  total_loss: 0.3198  loss_cls: 0.1784  loss_box_reg: 0.1238  loss_rpn_cls: 0.01652  loss_rpn_loc: 0.009377    time: 0.5611  last_time: 0.5506  data_time: 0.0176  last_data_time: 0.0154   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:50:08 d2.utils.events]: \u001b[0m eta: 0:25:47  iter: 3899  total_loss: 0.3925  loss_cls: 0.2065  loss_box_reg: 0.1394  loss_rpn_cls: 0.01507  loss_rpn_loc: 0.01152    time: 0.5612  last_time: 0.6439  data_time: 0.0129  last_data_time: 0.0135   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:50:20 d2.utils.events]: \u001b[0m eta: 0:25:35  iter: 3919  total_loss: 0.393  loss_cls: 0.1988  loss_box_reg: 0.1686  loss_rpn_cls: 0.01789  loss_rpn_loc: 0.01026    time: 0.5612  last_time: 0.6509  data_time: 0.0183  last_data_time: 0.0229   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:50:31 d2.utils.events]: \u001b[0m eta: 0:25:22  iter: 3939  total_loss: 0.3919  loss_cls: 0.1953  loss_box_reg: 0.1455  loss_rpn_cls: 0.01516  loss_rpn_loc: 0.008162    time: 0.5613  last_time: 0.5642  data_time: 0.0152  last_data_time: 0.0321   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:50:43 d2.utils.events]: \u001b[0m eta: 0:25:10  iter: 3959  total_loss: 0.4157  loss_cls: 0.242  loss_box_reg: 0.1524  loss_rpn_cls: 0.01603  loss_rpn_loc: 0.009438    time: 0.5614  last_time: 0.5220  data_time: 0.0150  last_data_time: 0.0163   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:50:54 d2.utils.events]: \u001b[0m eta: 0:24:58  iter: 3979  total_loss: 0.3557  loss_cls: 0.2067  loss_box_reg: 0.1205  loss_rpn_cls: 0.01549  loss_rpn_loc: 0.0119    time: 0.5614  last_time: 0.5363  data_time: 0.0140  last_data_time: 0.0151   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:51:06 d2.utils.events]: \u001b[0m eta: 0:24:46  iter: 3999  total_loss: 0.3141  loss_cls: 0.1608  loss_box_reg: 0.1229  loss_rpn_cls: 0.0206  loss_rpn_loc: 0.01068    time: 0.5615  last_time: 0.6042  data_time: 0.0184  last_data_time: 0.0235   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:51:17 d2.utils.events]: \u001b[0m eta: 0:24:35  iter: 4019  total_loss: 0.4349  loss_cls: 0.248  loss_box_reg: 0.1553  loss_rpn_cls: 0.01757  loss_rpn_loc: 0.01211    time: 0.5616  last_time: 0.6181  data_time: 0.0086  last_data_time: 0.0038   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:51:29 d2.utils.events]: \u001b[0m eta: 0:24:24  iter: 4039  total_loss: 0.5212  loss_cls: 0.2796  loss_box_reg: 0.1907  loss_rpn_cls: 0.02009  loss_rpn_loc: 0.01591    time: 0.5617  last_time: 0.5923  data_time: 0.0111  last_data_time: 0.0076   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:51:40 d2.utils.events]: \u001b[0m eta: 0:24:12  iter: 4059  total_loss: 0.4677  loss_cls: 0.2631  loss_box_reg: 0.1612  loss_rpn_cls: 0.01741  loss_rpn_loc: 0.01047    time: 0.5617  last_time: 0.5420  data_time: 0.0136  last_data_time: 0.0087   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:51:51 d2.utils.events]: \u001b[0m eta: 0:23:58  iter: 4079  total_loss: 0.3553  loss_cls: 0.1659  loss_box_reg: 0.1216  loss_rpn_cls: 0.01498  loss_rpn_loc: 0.01346    time: 0.5617  last_time: 0.6150  data_time: 0.0151  last_data_time: 0.0282   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:52:03 d2.utils.events]: \u001b[0m eta: 0:23:47  iter: 4099  total_loss: 0.4506  loss_cls: 0.2546  loss_box_reg: 0.1567  loss_rpn_cls: 0.01921  loss_rpn_loc: 0.01086    time: 0.5618  last_time: 0.6114  data_time: 0.0144  last_data_time: 0.0258   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:52:14 d2.utils.events]: \u001b[0m eta: 0:23:37  iter: 4119  total_loss: 0.4275  loss_cls: 0.2201  loss_box_reg: 0.1589  loss_rpn_cls: 0.02055  loss_rpn_loc: 0.01418    time: 0.5618  last_time: 0.5985  data_time: 0.0114  last_data_time: 0.0155   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:52:26 d2.utils.events]: \u001b[0m eta: 0:23:25  iter: 4139  total_loss: 0.468  loss_cls: 0.2399  loss_box_reg: 0.1772  loss_rpn_cls: 0.02147  loss_rpn_loc: 0.01687    time: 0.5619  last_time: 0.5741  data_time: 0.0144  last_data_time: 0.0339   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:52:37 d2.utils.events]: \u001b[0m eta: 0:23:13  iter: 4159  total_loss: 0.3469  loss_cls: 0.1849  loss_box_reg: 0.1199  loss_rpn_cls: 0.01745  loss_rpn_loc: 0.01237    time: 0.5619  last_time: 0.5990  data_time: 0.0131  last_data_time: 0.0323   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:52:48 d2.utils.events]: \u001b[0m eta: 0:22:59  iter: 4179  total_loss: 0.5078  loss_cls: 0.2552  loss_box_reg: 0.1964  loss_rpn_cls: 0.03006  loss_rpn_loc: 0.01861    time: 0.5618  last_time: 0.5869  data_time: 0.0134  last_data_time: 0.0304   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:53:00 d2.utils.events]: \u001b[0m eta: 0:22:48  iter: 4199  total_loss: 0.3472  loss_cls: 0.1922  loss_box_reg: 0.1265  loss_rpn_cls: 0.01648  loss_rpn_loc: 0.01043    time: 0.5618  last_time: 0.5978  data_time: 0.0126  last_data_time: 0.0095   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:53:11 d2.utils.events]: \u001b[0m eta: 0:22:37  iter: 4219  total_loss: 0.3499  loss_cls: 0.1787  loss_box_reg: 0.1277  loss_rpn_cls: 0.01191  loss_rpn_loc: 0.01042    time: 0.5620  last_time: 0.5759  data_time: 0.0144  last_data_time: 0.0039   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:53:23 d2.utils.events]: \u001b[0m eta: 0:22:25  iter: 4239  total_loss: 0.3608  loss_cls: 0.213  loss_box_reg: 0.138  loss_rpn_cls: 0.02047  loss_rpn_loc: 0.01363    time: 0.5620  last_time: 0.5346  data_time: 0.0159  last_data_time: 0.0031   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:53:34 d2.utils.events]: \u001b[0m eta: 0:22:15  iter: 4259  total_loss: 0.4119  loss_cls: 0.2251  loss_box_reg: 0.1271  loss_rpn_cls: 0.01571  loss_rpn_loc: 0.0115    time: 0.5621  last_time: 0.5485  data_time: 0.0179  last_data_time: 0.0267   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:53:46 d2.utils.events]: \u001b[0m eta: 0:22:05  iter: 4279  total_loss: 0.361  loss_cls: 0.1848  loss_box_reg: 0.1259  loss_rpn_cls: 0.01423  loss_rpn_loc: 0.007844    time: 0.5622  last_time: 0.5620  data_time: 0.0124  last_data_time: 0.0174   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:53:57 d2.utils.events]: \u001b[0m eta: 0:21:52  iter: 4299  total_loss: 0.3984  loss_cls: 0.2117  loss_box_reg: 0.1433  loss_rpn_cls: 0.01049  loss_rpn_loc: 0.0135    time: 0.5622  last_time: 0.5119  data_time: 0.0180  last_data_time: 0.0150   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:54:09 d2.utils.events]: \u001b[0m eta: 0:21:40  iter: 4319  total_loss: 0.4319  loss_cls: 0.2284  loss_box_reg: 0.1769  loss_rpn_cls: 0.0186  loss_rpn_loc: 0.01237    time: 0.5622  last_time: 0.5272  data_time: 0.0170  last_data_time: 0.0035   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:54:21 d2.utils.events]: \u001b[0m eta: 0:21:29  iter: 4339  total_loss: 0.3702  loss_cls: 0.2061  loss_box_reg: 0.1436  loss_rpn_cls: 0.01585  loss_rpn_loc: 0.009808    time: 0.5624  last_time: 0.6394  data_time: 0.0155  last_data_time: 0.0034   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:54:32 d2.utils.events]: \u001b[0m eta: 0:21:20  iter: 4359  total_loss: 0.3725  loss_cls: 0.1881  loss_box_reg: 0.142  loss_rpn_cls: 0.02259  loss_rpn_loc: 0.01304    time: 0.5624  last_time: 0.6135  data_time: 0.0132  last_data_time: 0.0042   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:54:43 d2.utils.events]: \u001b[0m eta: 0:21:09  iter: 4379  total_loss: 0.3884  loss_cls: 0.2181  loss_box_reg: 0.1397  loss_rpn_cls: 0.02341  loss_rpn_loc: 0.01394    time: 0.5624  last_time: 0.5916  data_time: 0.0120  last_data_time: 0.0182   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:54:55 d2.utils.events]: \u001b[0m eta: 0:21:01  iter: 4399  total_loss: 0.4175  loss_cls: 0.2023  loss_box_reg: 0.1694  loss_rpn_cls: 0.02442  loss_rpn_loc: 0.01495    time: 0.5625  last_time: 0.6076  data_time: 0.0136  last_data_time: 0.0278   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:55:07 d2.utils.events]: \u001b[0m eta: 0:20:52  iter: 4419  total_loss: 0.3677  loss_cls: 0.1847  loss_box_reg: 0.1238  loss_rpn_cls: 0.01989  loss_rpn_loc: 0.0146    time: 0.5626  last_time: 0.5696  data_time: 0.0167  last_data_time: 0.0066   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:55:18 d2.utils.events]: \u001b[0m eta: 0:20:44  iter: 4439  total_loss: 0.3885  loss_cls: 0.2135  loss_box_reg: 0.1377  loss_rpn_cls: 0.01748  loss_rpn_loc: 0.01295    time: 0.5627  last_time: 0.5915  data_time: 0.0130  last_data_time: 0.0174   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:55:30 d2.utils.events]: \u001b[0m eta: 0:20:35  iter: 4459  total_loss: 0.3417  loss_cls: 0.1819  loss_box_reg: 0.1219  loss_rpn_cls: 0.014  loss_rpn_loc: 0.0112    time: 0.5628  last_time: 0.6252  data_time: 0.0151  last_data_time: 0.0411   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:55:41 d2.utils.events]: \u001b[0m eta: 0:20:26  iter: 4479  total_loss: 0.5194  loss_cls: 0.2589  loss_box_reg: 0.2099  loss_rpn_cls: 0.01683  loss_rpn_loc: 0.0129    time: 0.5628  last_time: 0.6179  data_time: 0.0128  last_data_time: 0.0045   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:55:53 d2.utils.events]: \u001b[0m eta: 0:20:14  iter: 4499  total_loss: 0.4515  loss_cls: 0.247  loss_box_reg: 0.1602  loss_rpn_cls: 0.02414  loss_rpn_loc: 0.0127    time: 0.5629  last_time: 0.5202  data_time: 0.0176  last_data_time: 0.0307   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:56:04 d2.utils.events]: \u001b[0m eta: 0:20:00  iter: 4519  total_loss: 0.4277  loss_cls: 0.2352  loss_box_reg: 0.1487  loss_rpn_cls: 0.02807  loss_rpn_loc: 0.01854    time: 0.5629  last_time: 0.3071  data_time: 0.0165  last_data_time: 0.0034   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:56:16 d2.utils.events]: \u001b[0m eta: 0:19:45  iter: 4539  total_loss: 0.3756  loss_cls: 0.2099  loss_box_reg: 0.1279  loss_rpn_cls: 0.01871  loss_rpn_loc: 0.009872    time: 0.5630  last_time: 0.4311  data_time: 0.0116  last_data_time: 0.0034   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:56:27 d2.utils.events]: \u001b[0m eta: 0:19:32  iter: 4559  total_loss: 0.3513  loss_cls: 0.1971  loss_box_reg: 0.1291  loss_rpn_cls: 0.01309  loss_rpn_loc: 0.01027    time: 0.5630  last_time: 0.5463  data_time: 0.0133  last_data_time: 0.0168   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:56:38 d2.utils.events]: \u001b[0m eta: 0:19:17  iter: 4579  total_loss: 0.2817  loss_cls: 0.1706  loss_box_reg: 0.08648  loss_rpn_cls: 0.01504  loss_rpn_loc: 0.007767    time: 0.5630  last_time: 0.5803  data_time: 0.0129  last_data_time: 0.0204   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:56:50 d2.utils.events]: \u001b[0m eta: 0:19:02  iter: 4599  total_loss: 0.5249  loss_cls: 0.2919  loss_box_reg: 0.1998  loss_rpn_cls: 0.01401  loss_rpn_loc: 0.01185    time: 0.5630  last_time: 0.5382  data_time: 0.0154  last_data_time: 0.0045   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:57:01 d2.utils.events]: \u001b[0m eta: 0:18:50  iter: 4619  total_loss: 0.4232  loss_cls: 0.2173  loss_box_reg: 0.1528  loss_rpn_cls: 0.01895  loss_rpn_loc: 0.01014    time: 0.5630  last_time: 0.5045  data_time: 0.0110  last_data_time: 0.0147   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:57:13 d2.utils.events]: \u001b[0m eta: 0:18:37  iter: 4639  total_loss: 0.3627  loss_cls: 0.1957  loss_box_reg: 0.1553  loss_rpn_cls: 0.02049  loss_rpn_loc: 0.01178    time: 0.5631  last_time: 0.6342  data_time: 0.0160  last_data_time: 0.0266   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:57:25 d2.utils.events]: \u001b[0m eta: 0:18:23  iter: 4659  total_loss: 0.3421  loss_cls: 0.1711  loss_box_reg: 0.1255  loss_rpn_cls: 0.01469  loss_rpn_loc: 0.009974    time: 0.5632  last_time: 0.5742  data_time: 0.0176  last_data_time: 0.0048   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:57:36 d2.utils.events]: \u001b[0m eta: 0:18:09  iter: 4679  total_loss: 0.3886  loss_cls: 0.1938  loss_box_reg: 0.1327  loss_rpn_cls: 0.0156  loss_rpn_loc: 0.0109    time: 0.5632  last_time: 0.6150  data_time: 0.0188  last_data_time: 0.0317   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:57:48 d2.utils.events]: \u001b[0m eta: 0:17:56  iter: 4699  total_loss: 0.3882  loss_cls: 0.1965  loss_box_reg: 0.1588  loss_rpn_cls: 0.01794  loss_rpn_loc: 0.01302    time: 0.5633  last_time: 0.5259  data_time: 0.0140  last_data_time: 0.0044   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:57:59 d2.utils.events]: \u001b[0m eta: 0:17:43  iter: 4719  total_loss: 0.3177  loss_cls: 0.1656  loss_box_reg: 0.1077  loss_rpn_cls: 0.02163  loss_rpn_loc: 0.01081    time: 0.5633  last_time: 0.6242  data_time: 0.0159  last_data_time: 0.0158   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:58:11 d2.utils.events]: \u001b[0m eta: 0:17:30  iter: 4739  total_loss: 0.4386  loss_cls: 0.2172  loss_box_reg: 0.1874  loss_rpn_cls: 0.01709  loss_rpn_loc: 0.0141    time: 0.5635  last_time: 0.5923  data_time: 0.0179  last_data_time: 0.0292   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:58:23 d2.utils.events]: \u001b[0m eta: 0:17:17  iter: 4759  total_loss: 0.3155  loss_cls: 0.1578  loss_box_reg: 0.1215  loss_rpn_cls: 0.01702  loss_rpn_loc: 0.01186    time: 0.5635  last_time: 0.6479  data_time: 0.0149  last_data_time: 0.0318   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:58:34 d2.utils.events]: \u001b[0m eta: 0:17:06  iter: 4779  total_loss: 0.413  loss_cls: 0.2346  loss_box_reg: 0.134  loss_rpn_cls: 0.01914  loss_rpn_loc: 0.01385    time: 0.5635  last_time: 0.5680  data_time: 0.0152  last_data_time: 0.0169   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:58:45 d2.utils.events]: \u001b[0m eta: 0:16:54  iter: 4799  total_loss: 0.4048  loss_cls: 0.2015  loss_box_reg: 0.1465  loss_rpn_cls: 0.02644  loss_rpn_loc: 0.01314    time: 0.5636  last_time: 0.6192  data_time: 0.0137  last_data_time: 0.0159   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:58:57 d2.utils.events]: \u001b[0m eta: 0:16:43  iter: 4819  total_loss: 0.4233  loss_cls: 0.2309  loss_box_reg: 0.1497  loss_rpn_cls: 0.01353  loss_rpn_loc: 0.01101    time: 0.5636  last_time: 0.6553  data_time: 0.0097  last_data_time: 0.0033   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:59:10 d2.utils.events]: \u001b[0m eta: 0:16:32  iter: 4839  total_loss: 0.3371  loss_cls: 0.1642  loss_box_reg: 0.1314  loss_rpn_cls: 0.01282  loss_rpn_loc: 0.01098    time: 0.5641  last_time: 0.5799  data_time: 0.0145  last_data_time: 0.0149   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:59:23 d2.utils.events]: \u001b[0m eta: 0:16:22  iter: 4859  total_loss: 0.3734  loss_cls: 0.2063  loss_box_reg: 0.1441  loss_rpn_cls: 0.01592  loss_rpn_loc: 0.01052    time: 0.5644  last_time: 0.5853  data_time: 0.0179  last_data_time: 0.0163   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:59:36 d2.utils.events]: \u001b[0m eta: 0:16:12  iter: 4879  total_loss: 0.3939  loss_cls: 0.2293  loss_box_reg: 0.1319  loss_rpn_cls: 0.01641  loss_rpn_loc: 0.01327    time: 0.5648  last_time: 0.5801  data_time: 0.0108  last_data_time: 0.0135   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 13:59:50 d2.utils.events]: \u001b[0m eta: 0:16:01  iter: 4899  total_loss: 0.3108  loss_cls: 0.1836  loss_box_reg: 0.1116  loss_rpn_cls: 0.01234  loss_rpn_loc: 0.007536    time: 0.5652  last_time: 0.7024  data_time: 0.0165  last_data_time: 0.0282   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:00:03 d2.utils.events]: \u001b[0m eta: 0:15:52  iter: 4919  total_loss: 0.4051  loss_cls: 0.2317  loss_box_reg: 0.1561  loss_rpn_cls: 0.01105  loss_rpn_loc: 0.01218    time: 0.5656  last_time: 0.6290  data_time: 0.0131  last_data_time: 0.0109   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:00:17 d2.utils.events]: \u001b[0m eta: 0:15:43  iter: 4939  total_loss: 0.4161  loss_cls: 0.2009  loss_box_reg: 0.1686  loss_rpn_cls: 0.0205  loss_rpn_loc: 0.01936    time: 0.5660  last_time: 0.6510  data_time: 0.0169  last_data_time: 0.0032   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:00:30 d2.utils.events]: \u001b[0m eta: 0:15:34  iter: 4959  total_loss: 0.3596  loss_cls: 0.1843  loss_box_reg: 0.1265  loss_rpn_cls: 0.01557  loss_rpn_loc: 0.01031    time: 0.5664  last_time: 0.5316  data_time: 0.0146  last_data_time: 0.0140   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:00:43 d2.utils.events]: \u001b[0m eta: 0:15:23  iter: 4979  total_loss: 0.4543  loss_cls: 0.2364  loss_box_reg: 0.1894  loss_rpn_cls: 0.02631  loss_rpn_loc: 0.01706    time: 0.5667  last_time: 0.7371  data_time: 0.0130  last_data_time: 0.0206   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:00:56 d2.utils.events]: \u001b[0m eta: 0:15:12  iter: 4999  total_loss: 0.4546  loss_cls: 0.2479  loss_box_reg: 0.1684  loss_rpn_cls: 0.01459  loss_rpn_loc: 0.0116    time: 0.5670  last_time: 0.7421  data_time: 0.0147  last_data_time: 0.0037   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:01:09 d2.utils.events]: \u001b[0m eta: 0:15:02  iter: 5019  total_loss: 0.3551  loss_cls: 0.1831  loss_box_reg: 0.1201  loss_rpn_cls: 0.01617  loss_rpn_loc: 0.01454    time: 0.5673  last_time: 0.7865  data_time: 0.0167  last_data_time: 0.0189   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:01:23 d2.utils.events]: \u001b[0m eta: 0:14:54  iter: 5039  total_loss: 0.4551  loss_cls: 0.2335  loss_box_reg: 0.1523  loss_rpn_cls: 0.0157  loss_rpn_loc: 0.01402    time: 0.5678  last_time: 0.6776  data_time: 0.0146  last_data_time: 0.0274   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:01:36 d2.utils.events]: \u001b[0m eta: 0:14:44  iter: 5059  total_loss: 0.3841  loss_cls: 0.2033  loss_box_reg: 0.1315  loss_rpn_cls: 0.0166  loss_rpn_loc: 0.01147    time: 0.5682  last_time: 0.5729  data_time: 0.0126  last_data_time: 0.0242   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:01:50 d2.utils.events]: \u001b[0m eta: 0:14:34  iter: 5079  total_loss: 0.3028  loss_cls: 0.1782  loss_box_reg: 0.1086  loss_rpn_cls: 0.01571  loss_rpn_loc: 0.01197    time: 0.5687  last_time: 0.8314  data_time: 0.0175  last_data_time: 0.0188   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:02:04 d2.utils.events]: \u001b[0m eta: 0:14:24  iter: 5099  total_loss: 0.4518  loss_cls: 0.2327  loss_box_reg: 0.1701  loss_rpn_cls: 0.02183  loss_rpn_loc: 0.0158    time: 0.5693  last_time: 0.7421  data_time: 0.0127  last_data_time: 0.0158   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:02:16 d2.utils.events]: \u001b[0m eta: 0:14:12  iter: 5119  total_loss: 0.457  loss_cls: 0.2002  loss_box_reg: 0.1509  loss_rpn_cls: 0.02124  loss_rpn_loc: 0.01447    time: 0.5693  last_time: 0.7038  data_time: 0.0144  last_data_time: 0.0033   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:02:21 d2.utils.events]: \u001b[0m eta: 0:13:59  iter: 5139  total_loss: 0.4522  loss_cls: 0.2223  loss_box_reg: 0.1623  loss_rpn_cls: 0.0172  loss_rpn_loc: 0.01336    time: 0.5681  last_time: 0.2292  data_time: 0.0136  last_data_time: 0.0114   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:02:25 d2.utils.events]: \u001b[0m eta: 0:13:45  iter: 5159  total_loss: 0.3134  loss_cls: 0.1687  loss_box_reg: 0.14  loss_rpn_cls: 0.01476  loss_rpn_loc: 0.01728    time: 0.5666  last_time: 0.1922  data_time: 0.0115  last_data_time: 0.0173   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:02:29 d2.utils.events]: \u001b[0m eta: 0:13:32  iter: 5179  total_loss: 0.3436  loss_cls: 0.1831  loss_box_reg: 0.1333  loss_rpn_cls: 0.01303  loss_rpn_loc: 0.01196    time: 0.5652  last_time: 0.2004  data_time: 0.0143  last_data_time: 0.0202   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:02:33 d2.utils.events]: \u001b[0m eta: 0:13:18  iter: 5199  total_loss: 0.3812  loss_cls: 0.2003  loss_box_reg: 0.1352  loss_rpn_cls: 0.01573  loss_rpn_loc: 0.0149    time: 0.5637  last_time: 0.1971  data_time: 0.0143  last_data_time: 0.0080   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:02:36 d2.utils.events]: \u001b[0m eta: 0:13:03  iter: 5219  total_loss: 0.4116  loss_cls: 0.2035  loss_box_reg: 0.154  loss_rpn_cls: 0.0109  loss_rpn_loc: 0.009036    time: 0.5623  last_time: 0.2200  data_time: 0.0134  last_data_time: 0.0223   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:02:45 d2.utils.events]: \u001b[0m eta: 0:12:51  iter: 5239  total_loss: 0.3406  loss_cls: 0.1975  loss_box_reg: 0.1066  loss_rpn_cls: 0.01741  loss_rpn_loc: 0.01213    time: 0.5618  last_time: 0.5046  data_time: 0.0155  last_data_time: 0.0145   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:02:56 d2.utils.events]: \u001b[0m eta: 0:12:39  iter: 5259  total_loss: 0.348  loss_cls: 0.1933  loss_box_reg: 0.1109  loss_rpn_cls: 0.009938  loss_rpn_loc: 0.01059    time: 0.5618  last_time: 0.5961  data_time: 0.0119  last_data_time: 0.0052   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:03:08 d2.utils.events]: \u001b[0m eta: 0:12:28  iter: 5279  total_loss: 0.3516  loss_cls: 0.2071  loss_box_reg: 0.1238  loss_rpn_cls: 0.0122  loss_rpn_loc: 0.0104    time: 0.5620  last_time: 0.6246  data_time: 0.0149  last_data_time: 0.0066   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:03:20 d2.utils.events]: \u001b[0m eta: 0:12:17  iter: 5299  total_loss: 0.3307  loss_cls: 0.1954  loss_box_reg: 0.1158  loss_rpn_cls: 0.01577  loss_rpn_loc: 0.01392    time: 0.5620  last_time: 0.5526  data_time: 0.0130  last_data_time: 0.0031   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:03:32 d2.utils.events]: \u001b[0m eta: 0:12:05  iter: 5319  total_loss: 0.3592  loss_cls: 0.18  loss_box_reg: 0.1437  loss_rpn_cls: 0.01191  loss_rpn_loc: 0.01206    time: 0.5621  last_time: 0.5698  data_time: 0.0118  last_data_time: 0.0148   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:03:43 d2.utils.events]: \u001b[0m eta: 0:11:53  iter: 5339  total_loss: 0.353  loss_cls: 0.199  loss_box_reg: 0.1236  loss_rpn_cls: 0.01561  loss_rpn_loc: 0.01071    time: 0.5621  last_time: 0.5457  data_time: 0.0150  last_data_time: 0.0138   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:03:49 d2.utils.events]: \u001b[0m eta: 0:11:38  iter: 5359  total_loss: 0.4293  loss_cls: 0.2087  loss_box_reg: 0.1751  loss_rpn_cls: 0.01926  loss_rpn_loc: 0.01514    time: 0.5610  last_time: 0.5668  data_time: 0.0133  last_data_time: 0.0223   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:04:00 d2.utils.events]: \u001b[0m eta: 0:11:27  iter: 5379  total_loss: 0.2655  loss_cls: 0.1533  loss_box_reg: 0.1036  loss_rpn_cls: 0.01173  loss_rpn_loc: 0.01015    time: 0.5611  last_time: 0.5669  data_time: 0.0127  last_data_time: 0.0052   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:04:12 d2.utils.events]: \u001b[0m eta: 0:11:15  iter: 5399  total_loss: 0.3685  loss_cls: 0.1783  loss_box_reg: 0.1448  loss_rpn_cls: 0.0141  loss_rpn_loc: 0.01143    time: 0.5612  last_time: 0.5338  data_time: 0.0137  last_data_time: 0.0152   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:04:24 d2.utils.events]: \u001b[0m eta: 0:11:06  iter: 5419  total_loss: 0.3903  loss_cls: 0.2044  loss_box_reg: 0.1479  loss_rpn_cls: 0.01668  loss_rpn_loc: 0.01281    time: 0.5613  last_time: 0.6479  data_time: 0.0101  last_data_time: 0.0065   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:04:35 d2.utils.events]: \u001b[0m eta: 0:10:53  iter: 5439  total_loss: 0.412  loss_cls: 0.1796  loss_box_reg: 0.1334  loss_rpn_cls: 0.01972  loss_rpn_loc: 0.01077    time: 0.5614  last_time: 0.6146  data_time: 0.0117  last_data_time: 0.0041   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:04:47 d2.utils.events]: \u001b[0m eta: 0:10:40  iter: 5459  total_loss: 0.2924  loss_cls: 0.1552  loss_box_reg: 0.1136  loss_rpn_cls: 0.02098  loss_rpn_loc: 0.01172    time: 0.5614  last_time: 0.6365  data_time: 0.0124  last_data_time: 0.0486   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:04:58 d2.utils.events]: \u001b[0m eta: 0:10:28  iter: 5479  total_loss: 0.3075  loss_cls: 0.1547  loss_box_reg: 0.1103  loss_rpn_cls: 0.01381  loss_rpn_loc: 0.009328    time: 0.5614  last_time: 0.5710  data_time: 0.0164  last_data_time: 0.0153   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:05:09 d2.utils.events]: \u001b[0m eta: 0:10:16  iter: 5499  total_loss: 0.4002  loss_cls: 0.1862  loss_box_reg: 0.1447  loss_rpn_cls: 0.01847  loss_rpn_loc: 0.01323    time: 0.5615  last_time: 0.5138  data_time: 0.0131  last_data_time: 0.0133   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:05:21 d2.utils.events]: \u001b[0m eta: 0:10:05  iter: 5519  total_loss: 0.287  loss_cls: 0.1608  loss_box_reg: 0.1015  loss_rpn_cls: 0.01347  loss_rpn_loc: 0.01113    time: 0.5615  last_time: 0.5692  data_time: 0.0127  last_data_time: 0.0147   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:05:32 d2.utils.events]: \u001b[0m eta: 0:09:53  iter: 5539  total_loss: 0.3331  loss_cls: 0.1902  loss_box_reg: 0.1224  loss_rpn_cls: 0.01538  loss_rpn_loc: 0.01119    time: 0.5615  last_time: 0.5408  data_time: 0.0136  last_data_time: 0.0036   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:05:44 d2.utils.events]: \u001b[0m eta: 0:09:41  iter: 5559  total_loss: 0.3844  loss_cls: 0.2117  loss_box_reg: 0.1359  loss_rpn_cls: 0.02018  loss_rpn_loc: 0.01155    time: 0.5615  last_time: 0.5068  data_time: 0.0153  last_data_time: 0.0140   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:05:55 d2.utils.events]: \u001b[0m eta: 0:09:30  iter: 5579  total_loss: 0.3626  loss_cls: 0.1809  loss_box_reg: 0.1431  loss_rpn_cls: 0.01622  loss_rpn_loc: 0.01035    time: 0.5616  last_time: 0.4434  data_time: 0.0125  last_data_time: 0.0059   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:06:07 d2.utils.events]: \u001b[0m eta: 0:09:18  iter: 5599  total_loss: 0.4419  loss_cls: 0.2397  loss_box_reg: 0.1632  loss_rpn_cls: 0.0178  loss_rpn_loc: 0.01348    time: 0.5616  last_time: 0.5513  data_time: 0.0138  last_data_time: 0.0039   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:06:18 d2.utils.events]: \u001b[0m eta: 0:09:05  iter: 5619  total_loss: 0.3472  loss_cls: 0.1794  loss_box_reg: 0.1227  loss_rpn_cls: 0.01794  loss_rpn_loc: 0.008895    time: 0.5617  last_time: 0.6201  data_time: 0.0126  last_data_time: 0.0039   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:06:30 d2.utils.events]: \u001b[0m eta: 0:08:54  iter: 5639  total_loss: 0.3381  loss_cls: 0.1828  loss_box_reg: 0.1445  loss_rpn_cls: 0.01769  loss_rpn_loc: 0.01249    time: 0.5617  last_time: 0.4761  data_time: 0.0141  last_data_time: 0.0228   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:06:41 d2.utils.events]: \u001b[0m eta: 0:08:41  iter: 5659  total_loss: 0.3844  loss_cls: 0.1939  loss_box_reg: 0.1642  loss_rpn_cls: 0.01525  loss_rpn_loc: 0.01286    time: 0.5617  last_time: 0.5486  data_time: 0.0127  last_data_time: 0.0038   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:06:52 d2.utils.events]: \u001b[0m eta: 0:08:30  iter: 5679  total_loss: 0.4047  loss_cls: 0.1717  loss_box_reg: 0.1318  loss_rpn_cls: 0.02083  loss_rpn_loc: 0.01181    time: 0.5617  last_time: 0.5668  data_time: 0.0140  last_data_time: 0.0165   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:07:04 d2.utils.events]: \u001b[0m eta: 0:08:18  iter: 5699  total_loss: 0.3184  loss_cls: 0.1644  loss_box_reg: 0.1325  loss_rpn_cls: 0.01207  loss_rpn_loc: 0.007949    time: 0.5618  last_time: 0.5594  data_time: 0.0136  last_data_time: 0.0042   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:07:15 d2.utils.events]: \u001b[0m eta: 0:08:06  iter: 5719  total_loss: 0.3442  loss_cls: 0.1691  loss_box_reg: 0.1335  loss_rpn_cls: 0.01588  loss_rpn_loc: 0.009841    time: 0.5618  last_time: 0.6425  data_time: 0.0121  last_data_time: 0.0155   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:07:26 d2.utils.events]: \u001b[0m eta: 0:07:53  iter: 5739  total_loss: 0.3088  loss_cls: 0.1499  loss_box_reg: 0.1359  loss_rpn_cls: 0.01138  loss_rpn_loc: 0.01096    time: 0.5618  last_time: 0.5560  data_time: 0.0112  last_data_time: 0.0039   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:07:38 d2.utils.events]: \u001b[0m eta: 0:07:42  iter: 5759  total_loss: 0.3105  loss_cls: 0.1565  loss_box_reg: 0.1272  loss_rpn_cls: 0.01633  loss_rpn_loc: 0.01429    time: 0.5618  last_time: 0.6029  data_time: 0.0147  last_data_time: 0.0139   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:07:49 d2.utils.events]: \u001b[0m eta: 0:07:31  iter: 5779  total_loss: 0.4344  loss_cls: 0.2268  loss_box_reg: 0.1789  loss_rpn_cls: 0.01699  loss_rpn_loc: 0.009942    time: 0.5619  last_time: 0.6196  data_time: 0.0156  last_data_time: 0.0182   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:08:01 d2.utils.events]: \u001b[0m eta: 0:07:19  iter: 5799  total_loss: 0.3723  loss_cls: 0.1952  loss_box_reg: 0.1415  loss_rpn_cls: 0.02411  loss_rpn_loc: 0.0127    time: 0.5619  last_time: 0.6047  data_time: 0.0142  last_data_time: 0.0034   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:08:12 d2.utils.events]: \u001b[0m eta: 0:07:08  iter: 5819  total_loss: 0.3096  loss_cls: 0.1546  loss_box_reg: 0.08973  loss_rpn_cls: 0.01885  loss_rpn_loc: 0.01113    time: 0.5619  last_time: 0.6516  data_time: 0.0136  last_data_time: 0.0236   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:08:23 d2.utils.events]: \u001b[0m eta: 0:06:55  iter: 5839  total_loss: 0.3471  loss_cls: 0.1984  loss_box_reg: 0.1364  loss_rpn_cls: 0.01284  loss_rpn_loc: 0.01045    time: 0.5619  last_time: 0.5985  data_time: 0.0151  last_data_time: 0.0094   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:08:35 d2.utils.events]: \u001b[0m eta: 0:06:43  iter: 5859  total_loss: 0.3235  loss_cls: 0.1868  loss_box_reg: 0.1297  loss_rpn_cls: 0.01531  loss_rpn_loc: 0.0132    time: 0.5619  last_time: 0.5461  data_time: 0.0107  last_data_time: 0.0032   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:08:46 d2.utils.events]: \u001b[0m eta: 0:06:31  iter: 5879  total_loss: 0.348  loss_cls: 0.1822  loss_box_reg: 0.1324  loss_rpn_cls: 0.02175  loss_rpn_loc: 0.01171    time: 0.5620  last_time: 0.6026  data_time: 0.0151  last_data_time: 0.0036   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:08:58 d2.utils.events]: \u001b[0m eta: 0:06:18  iter: 5899  total_loss: 0.3625  loss_cls: 0.193  loss_box_reg: 0.1335  loss_rpn_cls: 0.02011  loss_rpn_loc: 0.01158    time: 0.5620  last_time: 0.5983  data_time: 0.0109  last_data_time: 0.0032   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:09:09 d2.utils.events]: \u001b[0m eta: 0:06:06  iter: 5919  total_loss: 0.3536  loss_cls: 0.1674  loss_box_reg: 0.1134  loss_rpn_cls: 0.02125  loss_rpn_loc: 0.01342    time: 0.5620  last_time: 0.5852  data_time: 0.0166  last_data_time: 0.0181   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:09:20 d2.utils.events]: \u001b[0m eta: 0:05:53  iter: 5939  total_loss: 0.4012  loss_cls: 0.2057  loss_box_reg: 0.161  loss_rpn_cls: 0.02048  loss_rpn_loc: 0.01369    time: 0.5621  last_time: 0.5931  data_time: 0.0123  last_data_time: 0.0302   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:09:32 d2.utils.events]: \u001b[0m eta: 0:05:41  iter: 5959  total_loss: 0.3462  loss_cls: 0.1656  loss_box_reg: 0.1196  loss_rpn_cls: 0.02139  loss_rpn_loc: 0.009602    time: 0.5621  last_time: 0.5659  data_time: 0.0155  last_data_time: 0.0092   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:09:43 d2.utils.events]: \u001b[0m eta: 0:05:29  iter: 5979  total_loss: 0.3353  loss_cls: 0.1661  loss_box_reg: 0.1362  loss_rpn_cls: 0.02016  loss_rpn_loc: 0.01201    time: 0.5621  last_time: 0.6259  data_time: 0.0132  last_data_time: 0.0216   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:09:55 d2.utils.events]: \u001b[0m eta: 0:05:18  iter: 5999  total_loss: 0.2997  loss_cls: 0.1602  loss_box_reg: 0.119  loss_rpn_cls: 0.0168  loss_rpn_loc: 0.008238    time: 0.5622  last_time: 0.6493  data_time: 0.0168  last_data_time: 0.0279   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:10:07 d2.utils.events]: \u001b[0m eta: 0:05:06  iter: 6019  total_loss: 0.3822  loss_cls: 0.198  loss_box_reg: 0.1498  loss_rpn_cls: 0.01585  loss_rpn_loc: 0.01111    time: 0.5623  last_time: 0.5627  data_time: 0.0140  last_data_time: 0.0146   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:10:18 d2.utils.events]: \u001b[0m eta: 0:04:54  iter: 6039  total_loss: 0.4603  loss_cls: 0.208  loss_box_reg: 0.1773  loss_rpn_cls: 0.0129  loss_rpn_loc: 0.0137    time: 0.5622  last_time: 0.5396  data_time: 0.0083  last_data_time: 0.0033   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:10:28 d2.utils.events]: \u001b[0m eta: 0:04:42  iter: 6059  total_loss: 0.3719  loss_cls: 0.172  loss_box_reg: 0.1617  loss_rpn_cls: 0.01313  loss_rpn_loc: 0.01339    time: 0.5622  last_time: 0.5408  data_time: 0.0074  last_data_time: 0.0031   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:10:39 d2.utils.events]: \u001b[0m eta: 0:04:29  iter: 6079  total_loss: 0.4192  loss_cls: 0.2183  loss_box_reg: 0.1563  loss_rpn_cls: 0.01802  loss_rpn_loc: 0.01231    time: 0.5621  last_time: 0.4639  data_time: 0.0061  last_data_time: 0.0033   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:10:52 d2.utils.events]: \u001b[0m eta: 0:04:17  iter: 6099  total_loss: 0.4394  loss_cls: 0.1753  loss_box_reg: 0.1568  loss_rpn_cls: 0.01637  loss_rpn_loc: 0.01108    time: 0.5623  last_time: 0.5568  data_time: 0.0089  last_data_time: 0.0095   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:11:03 d2.utils.events]: \u001b[0m eta: 0:04:06  iter: 6119  total_loss: 0.3445  loss_cls: 0.194  loss_box_reg: 0.1348  loss_rpn_cls: 0.01471  loss_rpn_loc: 0.01112    time: 0.5623  last_time: 0.5722  data_time: 0.0095  last_data_time: 0.0055   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:11:14 d2.utils.events]: \u001b[0m eta: 0:03:55  iter: 6139  total_loss: 0.4716  loss_cls: 0.2281  loss_box_reg: 0.1972  loss_rpn_cls: 0.01555  loss_rpn_loc: 0.01447    time: 0.5623  last_time: 0.5678  data_time: 0.0046  last_data_time: 0.0042   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:11:25 d2.utils.events]: \u001b[0m eta: 0:03:44  iter: 6159  total_loss: 0.4188  loss_cls: 0.2039  loss_box_reg: 0.1458  loss_rpn_cls: 0.01487  loss_rpn_loc: 0.01575    time: 0.5622  last_time: 0.5754  data_time: 0.0083  last_data_time: 0.0142   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:11:38 d2.utils.events]: \u001b[0m eta: 0:03:34  iter: 6179  total_loss: 0.3556  loss_cls: 0.1967  loss_box_reg: 0.1332  loss_rpn_cls: 0.01372  loss_rpn_loc: 0.009952    time: 0.5624  last_time: 0.7552  data_time: 0.0141  last_data_time: 0.0230   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:11:51 d2.utils.events]: \u001b[0m eta: 0:03:23  iter: 6199  total_loss: 0.255  loss_cls: 0.1379  loss_box_reg: 0.09469  loss_rpn_cls: 0.01586  loss_rpn_loc: 0.01083    time: 0.5628  last_time: 0.5875  data_time: 0.0141  last_data_time: 0.0035   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:12:04 d2.utils.events]: \u001b[0m eta: 0:03:13  iter: 6219  total_loss: 0.3439  loss_cls: 0.183  loss_box_reg: 0.1485  loss_rpn_cls: 0.01919  loss_rpn_loc: 0.01347    time: 0.5630  last_time: 0.6402  data_time: 0.0174  last_data_time: 0.0069   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:12:18 d2.utils.events]: \u001b[0m eta: 0:03:02  iter: 6239  total_loss: 0.4562  loss_cls: 0.2316  loss_box_reg: 0.165  loss_rpn_cls: 0.01751  loss_rpn_loc: 0.01483    time: 0.5634  last_time: 0.6980  data_time: 0.0164  last_data_time: 0.0116   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:12:31 d2.utils.events]: \u001b[0m eta: 0:02:51  iter: 6259  total_loss: 0.3365  loss_cls: 0.1982  loss_box_reg: 0.1228  loss_rpn_cls: 0.01919  loss_rpn_loc: 0.01367    time: 0.5637  last_time: 0.7200  data_time: 0.0134  last_data_time: 0.0078   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:12:43 d2.utils.events]: \u001b[0m eta: 0:02:39  iter: 6279  total_loss: 0.4675  loss_cls: 0.2483  loss_box_reg: 0.1855  loss_rpn_cls: 0.01407  loss_rpn_loc: 0.01416    time: 0.5639  last_time: 0.6682  data_time: 0.0126  last_data_time: 0.0167   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:12:56 d2.utils.events]: \u001b[0m eta: 0:02:28  iter: 6299  total_loss: 0.3704  loss_cls: 0.1995  loss_box_reg: 0.1195  loss_rpn_cls: 0.01776  loss_rpn_loc: 0.008886    time: 0.5641  last_time: 0.6587  data_time: 0.0135  last_data_time: 0.0198   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:13:09 d2.utils.events]: \u001b[0m eta: 0:02:17  iter: 6319  total_loss: 0.4007  loss_cls: 0.2147  loss_box_reg: 0.1464  loss_rpn_cls: 0.009271  loss_rpn_loc: 0.01249    time: 0.5644  last_time: 0.7289  data_time: 0.0131  last_data_time: 0.0042   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:13:22 d2.utils.events]: \u001b[0m eta: 0:02:06  iter: 6339  total_loss: 0.4915  loss_cls: 0.2673  loss_box_reg: 0.1695  loss_rpn_cls: 0.02041  loss_rpn_loc: 0.01533    time: 0.5647  last_time: 0.5681  data_time: 0.0118  last_data_time: 0.0099   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:13:35 d2.utils.events]: \u001b[0m eta: 0:01:55  iter: 6359  total_loss: 0.3651  loss_cls: 0.1933  loss_box_reg: 0.1285  loss_rpn_cls: 0.0251  loss_rpn_loc: 0.0123    time: 0.5649  last_time: 0.6823  data_time: 0.0147  last_data_time: 0.0093   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:13:48 d2.utils.events]: \u001b[0m eta: 0:01:44  iter: 6379  total_loss: 0.4321  loss_cls: 0.1971  loss_box_reg: 0.1653  loss_rpn_cls: 0.01304  loss_rpn_loc: 0.01405    time: 0.5652  last_time: 0.7220  data_time: 0.0096  last_data_time: 0.0097   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:14:01 d2.utils.events]: \u001b[0m eta: 0:01:32  iter: 6399  total_loss: 0.3729  loss_cls: 0.1822  loss_box_reg: 0.1351  loss_rpn_cls: 0.01298  loss_rpn_loc: 0.0112    time: 0.5655  last_time: 0.6285  data_time: 0.0118  last_data_time: 0.0226   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:14:14 d2.utils.events]: \u001b[0m eta: 0:01:21  iter: 6419  total_loss: 0.2904  loss_cls: 0.1605  loss_box_reg: 0.1189  loss_rpn_cls: 0.009752  loss_rpn_loc: 0.006988    time: 0.5657  last_time: 0.5302  data_time: 0.0132  last_data_time: 0.0036   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:14:28 d2.utils.events]: \u001b[0m eta: 0:01:09  iter: 6439  total_loss: 0.3885  loss_cls: 0.2198  loss_box_reg: 0.1357  loss_rpn_cls: 0.01089  loss_rpn_loc: 0.01201    time: 0.5660  last_time: 0.6463  data_time: 0.0144  last_data_time: 0.0214   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:14:41 d2.utils.events]: \u001b[0m eta: 0:00:58  iter: 6459  total_loss: 0.3811  loss_cls: 0.1982  loss_box_reg: 0.1527  loss_rpn_cls: 0.02149  loss_rpn_loc: 0.01121    time: 0.5664  last_time: 0.6789  data_time: 0.0154  last_data_time: 0.0132   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:14:54 d2.utils.events]: \u001b[0m eta: 0:00:46  iter: 6479  total_loss: 0.429  loss_cls: 0.1963  loss_box_reg: 0.1787  loss_rpn_cls: 0.01848  loss_rpn_loc: 0.01419    time: 0.5666  last_time: 0.5683  data_time: 0.0123  last_data_time: 0.0086   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:15:05 d2.utils.events]: \u001b[0m eta: 0:00:34  iter: 6499  total_loss: 0.3429  loss_cls: 0.1695  loss_box_reg: 0.1335  loss_rpn_cls: 0.01062  loss_rpn_loc: 0.01418    time: 0.5666  last_time: 0.4842  data_time: 0.0143  last_data_time: 0.0037   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:15:17 d2.utils.events]: \u001b[0m eta: 0:00:23  iter: 6519  total_loss: 0.3969  loss_cls: 0.2259  loss_box_reg: 0.1648  loss_rpn_cls: 0.01442  loss_rpn_loc: 0.01116    time: 0.5667  last_time: 0.6126  data_time: 0.0124  last_data_time: 0.0244   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:15:29 d2.utils.events]: \u001b[0m eta: 0:00:11  iter: 6539  total_loss: 0.3523  loss_cls: 0.1676  loss_box_reg: 0.1529  loss_rpn_cls: 0.01747  loss_rpn_loc: 0.009952    time: 0.5667  last_time: 0.5545  data_time: 0.0170  last_data_time: 0.0157   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:15:40 d2.utils.events]: \u001b[0m eta: 0:00:00  iter: 6558  total_loss: 0.3505  loss_cls: 0.1951  loss_box_reg: 0.1364  loss_rpn_cls: 0.01091  loss_rpn_loc: 0.009638    time: 0.5667  last_time: 0.6687  data_time: 0.0135  last_data_time: 0.0305   lr: 0.00025  max_mem: 1744M\n",
      "\u001b[32m[03/11 14:15:40 d2.engine.hooks]: \u001b[0mOverall training speed: 6557 iterations in 1:01:56 (0.5667 s / it)\n",
      "\u001b[32m[03/11 14:15:40 d2.engine.hooks]: \u001b[0mTotal training time: 1:02:12 (0:00:15 on hooks)\n",
      "\u001b[32m[03/11 14:15:45 d2.data.datasets.coco]: \u001b[0mLoading car-damage-detection-2/valid/_annotations.coco.json takes 5.04 seconds.\n",
      "\u001b[5m\u001b[31mWARNING\u001b[0m \u001b[32m[03/11 14:15:45 d2.data.datasets.coco]: \u001b[0m\n",
      "Category ids in annotations are not in [1, #categories]! We'll apply a mapping for you.\n",
      "\n",
      "\u001b[32m[03/11 14:15:45 d2.data.datasets.coco]: \u001b[0mLoaded 1335 images in COCO format from car-damage-detection-2/valid/_annotations.coco.json\n",
      "\u001b[32m[03/11 14:15:46 d2.data.build]: \u001b[0mDistribution of instances among all 47 categories:\n",
      "\u001b[36m|   category    | #instances   |   category    | #instances   |   category    | #instances   |\n",
      "|:-------------:|:-------------|:-------------:|:-------------|:-------------:|:-------------|\n",
      "| Car-Damage-.. | 0            | Bodypanel-D.. | 0            | Front-Winds.. | 20           |\n",
      "| Headlight-D.. | 26           | Rear-windsc.. | 19           | RunningBoar.. | 15           |\n",
      "| Sidemirror-.. | 11           | Signlight-D.. | 2            | Taillight-D.. | 13           |\n",
      "|  back-bumper  | 24           |  back-glass   | 32           |  bonnet-dent  | 72           |\n",
      "|   boot-dent   | 12           |  broken_lamp  | 107          |     crack     | 131          |\n",
      "| damaged-door  | 17           | damaged-fro.. | 27           | damaged-hea.. | 35           |\n",
      "| damaged-hood  | 26           | damaged-rea.. | 25           | damaged-rea.. | 22           |\n",
      "| damaged-tai.. | 27           | damaged-trunk | 18           | damaged-win.. | 40           |\n",
      "| damaged-win.. | 43           |     dent      | 337          | dent-or-scr.. | 60           |\n",
      "|     door      | 58           | doorouter-d.. | 84           |  fender-dent  | 60           |\n",
      "|   flat_tire   | 47           | front-bumper  | 38           | front-bumpe.. | 96           |\n",
      "|  front-glass  | 46           |   headlight   | 75           |     hood      | 45           |\n",
      "|    mirror     | 74           |  pillar-dent  | 3            | quaterpanel.. | 37           |\n",
      "| rear-bumper.. | 52           |   roof-dent   | 11           |    scratch    | 530          |\n",
      "| shattered_g.. | 109          |   taillight   | 58           |     trunk     | 37           |\n",
      "|     wheel     | 41           |    window     | 23           |               |              |\n",
      "|     total     | 2685         |               |              |               |              |\u001b[0m\n",
      "\u001b[32m[03/11 14:15:46 d2.data.dataset_mapper]: \u001b[0m[DatasetMapper] Augmentations used in inference: [ResizeShortestEdge(short_edge_length=(800, 800), max_size=1333, sample_style='choice')]\n",
      "\u001b[32m[03/11 14:15:46 d2.data.common]: \u001b[0mSerializing the dataset using: <class 'detectron2.data.common._TorchSerializedList'>\n",
      "\u001b[32m[03/11 14:15:46 d2.data.common]: \u001b[0mSerializing 1335 elements to byte tensors and concatenating them all ...\n",
      "\u001b[32m[03/11 14:15:46 d2.data.common]: \u001b[0mSerialized dataset takes 1.72 MiB\n",
      "\u001b[5m\u001b[31mWARNING\u001b[0m \u001b[32m[03/11 14:15:46 d2.engine.defaults]: \u001b[0mNo evaluator found. Use `DefaultTrainer.test(evaluators=)`, or implement its `build_evaluator` method.\n"
     ]
    }
   ],
   "source": [
    "from detectron2.data.datasets import register_coco_instances\n",
    "from detectron2.config import get_cfg\n",
    "from detectron2 import model_zoo\n",
    "import os\n",
    "from detectron2.engine import DefaultTrainer\n",
    "\n",
    "dataset_path = \"car-damage-detection-2\"  # Update with your correct dataset path\n",
    "\n",
    "# ✅ Register COCO dataset for instance segmentation\n",
    "register_coco_instances(\"car_damage_train\", {}, \n",
    "                        f\"{dataset_path}/train/_annotations.coco.json\", \n",
    "                        f\"{dataset_path}/train\")\n",
    "\n",
    "register_coco_instances(\"car_damage_val\", {}, \n",
    "                        f\"{dataset_path}/valid/_annotations.coco.json\", \n",
    "                        f\"{dataset_path}/valid\")\n",
    "\n",
    "register_coco_instances(\"car_damage_test\", {}, \n",
    "                        f\"{dataset_path}/test/_annotations.coco.json\", \n",
    "                        f\"{dataset_path}/test\")\n",
    "\n",
    "# ✅ Load configuration for Mask R-CNN\n",
    "cfg = get_cfg()\n",
    "cfg.merge_from_file(model_zoo.get_config_file(\"COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml\"))\n",
    "\n",
    "cfg.DATASETS.TRAIN = (\"car_damage_train\",)\n",
    "cfg.DATASETS.TEST = (\"car_damage_val\",)\n",
    "cfg.DATALOADER.NUM_WORKERS = 4\n",
    "cfg.INPUT.MASK_FORMAT = \"polygon\"  # ✅ This ensures segmentation masks are in polygon format\n",
    "\n",
    "cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url(\"COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml\")  \n",
    "cfg.SOLVER.IMS_PER_BATCH = 2\n",
    "cfg.SOLVER.BASE_LR = 0.00025  \n",
    "cfg.SOLVER.MAX_ITER = 6559  # Adjust based on dataset size\n",
    "cfg.MODEL.ROI_HEADS.BATCH_SIZE_PER_IMAGE = 512  \n",
    "cfg.MODEL.ROI_HEADS.NUM_CLASSES = 47  # Update this based on your dataset\n",
    "\n",
    "cfg.OUTPUT_DIR = \"./output\"\n",
    "os.makedirs(cfg.OUTPUT_DIR, exist_ok=True)\n",
    "\n",
    "# Train the model\n",
    "trainer = DefaultTrainer(cfg)\n",
    "trainer.resume_or_load(resume=False)\n",
    "trainer.train()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[5m\u001b[31mWARNING\u001b[0m \u001b[32m[03/11 14:16:24 d2.evaluation.coco_evaluation]: \u001b[0mCOCO Evaluator instantiated using config, this is deprecated behavior. Please pass in explicit arguments instead.\n",
      "\u001b[5m\u001b[31mWARNING\u001b[0m \u001b[32m[03/11 14:16:24 d2.data.datasets.coco]: \u001b[0m\n",
      "Category ids in annotations are not in [1, #categories]! We'll apply a mapping for you.\n",
      "\n",
      "\u001b[32m[03/11 14:16:24 d2.data.datasets.coco]: \u001b[0mLoaded 1335 images in COCO format from car-damage-detection-2/valid/_annotations.coco.json\n",
      "\u001b[32m[03/11 14:16:24 d2.data.dataset_mapper]: \u001b[0m[DatasetMapper] Augmentations used in inference: [ResizeShortestEdge(short_edge_length=(800, 800), max_size=1333, sample_style='choice')]\n",
      "\u001b[32m[03/11 14:16:24 d2.data.common]: \u001b[0mSerializing the dataset using: <class 'detectron2.data.common._TorchSerializedList'>\n",
      "\u001b[32m[03/11 14:16:24 d2.data.common]: \u001b[0mSerializing 1335 elements to byte tensors and concatenating them all ...\n",
      "\u001b[32m[03/11 14:16:24 d2.data.common]: \u001b[0mSerialized dataset takes 1.72 MiB\n",
      "\u001b[32m[03/11 14:16:24 d2.evaluation.evaluator]: \u001b[0mStart inference on 1335 batches\n",
      "\u001b[32m[03/11 14:16:26 d2.evaluation.evaluator]: \u001b[0mInference done 11/1335. Dataloading: 0.0022 s/iter. Inference: 0.1768 s/iter. Eval: 0.0003 s/iter. Total: 0.1793 s/iter. ETA=0:03:57\n",
      "\u001b[32m[03/11 14:16:31 d2.evaluation.evaluator]: \u001b[0mInference done 42/1335. Dataloading: 0.0044 s/iter. Inference: 0.1593 s/iter. Eval: 0.0003 s/iter. Total: 0.1643 s/iter. ETA=0:03:32\n",
      "\u001b[32m[03/11 14:16:36 d2.evaluation.evaluator]: \u001b[0mInference done 72/1335. Dataloading: 0.0046 s/iter. Inference: 0.1609 s/iter. Eval: 0.0004 s/iter. Total: 0.1661 s/iter. ETA=0:03:29\n",
      "\u001b[32m[03/11 14:16:42 d2.evaluation.evaluator]: \u001b[0mInference done 102/1335. Dataloading: 0.0045 s/iter. Inference: 0.1625 s/iter. Eval: 0.0004 s/iter. Total: 0.1676 s/iter. ETA=0:03:26\n",
      "\u001b[32m[03/11 14:16:47 d2.evaluation.evaluator]: \u001b[0mInference done 134/1335. Dataloading: 0.0048 s/iter. Inference: 0.1608 s/iter. Eval: 0.0004 s/iter. Total: 0.1661 s/iter. ETA=0:03:19\n",
      "\u001b[32m[03/11 14:16:52 d2.evaluation.evaluator]: \u001b[0mInference done 164/1335. Dataloading: 0.0052 s/iter. Inference: 0.1607 s/iter. Eval: 0.0004 s/iter. Total: 0.1665 s/iter. ETA=0:03:14\n",
      "\u001b[32m[03/11 14:16:57 d2.evaluation.evaluator]: \u001b[0mInference done 195/1335. Dataloading: 0.0053 s/iter. Inference: 0.1606 s/iter. Eval: 0.0004 s/iter. Total: 0.1664 s/iter. ETA=0:03:09\n",
      "\u001b[32m[03/11 14:17:02 d2.evaluation.evaluator]: \u001b[0mInference done 225/1335. Dataloading: 0.0056 s/iter. Inference: 0.1608 s/iter. Eval: 0.0004 s/iter. Total: 0.1668 s/iter. ETA=0:03:05\n",
      "\u001b[32m[03/11 14:17:07 d2.evaluation.evaluator]: \u001b[0mInference done 256/1335. Dataloading: 0.0057 s/iter. Inference: 0.1606 s/iter. Eval: 0.0004 s/iter. Total: 0.1667 s/iter. ETA=0:02:59\n",
      "\u001b[32m[03/11 14:17:12 d2.evaluation.evaluator]: \u001b[0mInference done 287/1335. Dataloading: 0.0058 s/iter. Inference: 0.1599 s/iter. Eval: 0.0004 s/iter. Total: 0.1662 s/iter. ETA=0:02:54\n",
      "\u001b[32m[03/11 14:17:17 d2.evaluation.evaluator]: \u001b[0mInference done 317/1335. Dataloading: 0.0059 s/iter. Inference: 0.1598 s/iter. Eval: 0.0004 s/iter. Total: 0.1662 s/iter. ETA=0:02:49\n",
      "\u001b[32m[03/11 14:17:22 d2.evaluation.evaluator]: \u001b[0mInference done 348/1335. Dataloading: 0.0062 s/iter. Inference: 0.1591 s/iter. Eval: 0.0004 s/iter. Total: 0.1658 s/iter. ETA=0:02:43\n",
      "\u001b[32m[03/11 14:17:27 d2.evaluation.evaluator]: \u001b[0mInference done 379/1335. Dataloading: 0.0062 s/iter. Inference: 0.1590 s/iter. Eval: 0.0004 s/iter. Total: 0.1657 s/iter. ETA=0:02:38\n",
      "\u001b[32m[03/11 14:17:32 d2.evaluation.evaluator]: \u001b[0mInference done 410/1335. Dataloading: 0.0064 s/iter. Inference: 0.1587 s/iter. Eval: 0.0004 s/iter. Total: 0.1656 s/iter. ETA=0:02:33\n",
      "\u001b[32m[03/11 14:17:38 d2.evaluation.evaluator]: \u001b[0mInference done 441/1335. Dataloading: 0.0065 s/iter. Inference: 0.1585 s/iter. Eval: 0.0004 s/iter. Total: 0.1656 s/iter. ETA=0:02:28\n",
      "\u001b[32m[03/11 14:17:43 d2.evaluation.evaluator]: \u001b[0mInference done 472/1335. Dataloading: 0.0066 s/iter. Inference: 0.1582 s/iter. Eval: 0.0005 s/iter. Total: 0.1654 s/iter. ETA=0:02:22\n",
      "\u001b[32m[03/11 14:17:48 d2.evaluation.evaluator]: \u001b[0mInference done 503/1335. Dataloading: 0.0065 s/iter. Inference: 0.1582 s/iter. Eval: 0.0005 s/iter. Total: 0.1653 s/iter. ETA=0:02:17\n",
      "\u001b[32m[03/11 14:17:53 d2.evaluation.evaluator]: \u001b[0mInference done 534/1335. Dataloading: 0.0067 s/iter. Inference: 0.1581 s/iter. Eval: 0.0005 s/iter. Total: 0.1653 s/iter. ETA=0:02:12\n",
      "\u001b[32m[03/11 14:17:58 d2.evaluation.evaluator]: \u001b[0mInference done 564/1335. Dataloading: 0.0068 s/iter. Inference: 0.1582 s/iter. Eval: 0.0005 s/iter. Total: 0.1656 s/iter. ETA=0:02:07\n",
      "\u001b[32m[03/11 14:18:03 d2.evaluation.evaluator]: \u001b[0mInference done 595/1335. Dataloading: 0.0067 s/iter. Inference: 0.1583 s/iter. Eval: 0.0004 s/iter. Total: 0.1655 s/iter. ETA=0:02:02\n",
      "\u001b[32m[03/11 14:18:08 d2.evaluation.evaluator]: \u001b[0mInference done 625/1335. Dataloading: 0.0067 s/iter. Inference: 0.1584 s/iter. Eval: 0.0004 s/iter. Total: 0.1657 s/iter. ETA=0:01:57\n",
      "\u001b[32m[03/11 14:18:13 d2.evaluation.evaluator]: \u001b[0mInference done 655/1335. Dataloading: 0.0067 s/iter. Inference: 0.1587 s/iter. Eval: 0.0004 s/iter. Total: 0.1660 s/iter. ETA=0:01:52\n",
      "\u001b[32m[03/11 14:18:18 d2.evaluation.evaluator]: \u001b[0mInference done 687/1335. Dataloading: 0.0066 s/iter. Inference: 0.1585 s/iter. Eval: 0.0004 s/iter. Total: 0.1657 s/iter. ETA=0:01:47\n",
      "\u001b[32m[03/11 14:18:23 d2.evaluation.evaluator]: \u001b[0mInference done 717/1335. Dataloading: 0.0066 s/iter. Inference: 0.1586 s/iter. Eval: 0.0004 s/iter. Total: 0.1658 s/iter. ETA=0:01:42\n",
      "\u001b[32m[03/11 14:18:28 d2.evaluation.evaluator]: \u001b[0mInference done 746/1335. Dataloading: 0.0067 s/iter. Inference: 0.1588 s/iter. Eval: 0.0005 s/iter. Total: 0.1661 s/iter. ETA=0:01:37\n",
      "\u001b[32m[03/11 14:18:34 d2.evaluation.evaluator]: \u001b[0mInference done 777/1335. Dataloading: 0.0066 s/iter. Inference: 0.1589 s/iter. Eval: 0.0005 s/iter. Total: 0.1661 s/iter. ETA=0:01:32\n",
      "\u001b[32m[03/11 14:18:39 d2.evaluation.evaluator]: \u001b[0mInference done 808/1335. Dataloading: 0.0066 s/iter. Inference: 0.1589 s/iter. Eval: 0.0005 s/iter. Total: 0.1661 s/iter. ETA=0:01:27\n",
      "\u001b[32m[03/11 14:18:44 d2.evaluation.evaluator]: \u001b[0mInference done 838/1335. Dataloading: 0.0066 s/iter. Inference: 0.1590 s/iter. Eval: 0.0005 s/iter. Total: 0.1662 s/iter. ETA=0:01:22\n",
      "\u001b[32m[03/11 14:18:49 d2.evaluation.evaluator]: \u001b[0mInference done 869/1335. Dataloading: 0.0066 s/iter. Inference: 0.1590 s/iter. Eval: 0.0005 s/iter. Total: 0.1662 s/iter. ETA=0:01:17\n",
      "\u001b[32m[03/11 14:18:54 d2.evaluation.evaluator]: \u001b[0mInference done 900/1335. Dataloading: 0.0065 s/iter. Inference: 0.1590 s/iter. Eval: 0.0005 s/iter. Total: 0.1661 s/iter. ETA=0:01:12\n",
      "\u001b[32m[03/11 14:18:59 d2.evaluation.evaluator]: \u001b[0mInference done 931/1335. Dataloading: 0.0065 s/iter. Inference: 0.1589 s/iter. Eval: 0.0005 s/iter. Total: 0.1660 s/iter. ETA=0:01:07\n",
      "\u001b[32m[03/11 14:19:04 d2.evaluation.evaluator]: \u001b[0mInference done 975/1335. Dataloading: 0.0064 s/iter. Inference: 0.1566 s/iter. Eval: 0.0005 s/iter. Total: 0.1636 s/iter. ETA=0:00:58\n",
      "\u001b[32m[03/11 14:19:09 d2.evaluation.evaluator]: \u001b[0mInference done 1058/1335. Dataloading: 0.0062 s/iter. Inference: 0.1489 s/iter. Eval: 0.0005 s/iter. Total: 0.1557 s/iter. ETA=0:00:43\n",
      "\u001b[32m[03/11 14:19:14 d2.evaluation.evaluator]: \u001b[0mInference done 1157/1335. Dataloading: 0.0059 s/iter. Inference: 0.1402 s/iter. Eval: 0.0005 s/iter. Total: 0.1467 s/iter. ETA=0:00:26\n",
      "\u001b[32m[03/11 14:19:19 d2.evaluation.evaluator]: \u001b[0mInference done 1252/1335. Dataloading: 0.0058 s/iter. Inference: 0.1332 s/iter. Eval: 0.0004 s/iter. Total: 0.1396 s/iter. ETA=0:00:11\n",
      "\u001b[32m[03/11 14:19:24 d2.evaluation.evaluator]: \u001b[0mTotal inference time: 0:02:58.299760 (0.134060 s / iter per device, on 1 devices)\n",
      "\u001b[32m[03/11 14:19:24 d2.evaluation.evaluator]: \u001b[0mTotal inference pure compute time: 0:02:50 (0.127854 s / iter per device, on 1 devices)\n",
      "\u001b[32m[03/11 14:19:24 d2.evaluation.coco_evaluation]: \u001b[0mPreparing results for COCO format ...\n",
      "\u001b[32m[03/11 14:19:24 d2.evaluation.coco_evaluation]: \u001b[0mSaving results to ./output/coco_instances_results.json\n",
      "\u001b[32m[03/11 14:19:24 d2.evaluation.coco_evaluation]: \u001b[0mEvaluating predictions with unofficial COCO API...\n",
      "Loading and preparing results...\n",
      "DONE (t=0.03s)\n",
      "creating index...\n",
      "index created!\n",
      "\u001b[32m[03/11 14:19:24 d2.evaluation.fast_eval_api]: \u001b[0mEvaluate annotation type *bbox*\n",
      "\u001b[32m[03/11 14:19:25 d2.evaluation.fast_eval_api]: \u001b[0mCOCOeval_opt.evaluate() finished in 1.50 seconds.\n",
      "\u001b[32m[03/11 14:19:25 d2.evaluation.fast_eval_api]: \u001b[0mAccumulating evaluation results...\n",
      "\u001b[32m[03/11 14:19:26 d2.evaluation.fast_eval_api]: \u001b[0mCOCOeval_opt.accumulate() finished in 0.29 seconds.\n",
      " Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.152\n",
      " Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.261\n",
      " Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.154\n",
      " Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.059\n",
      " Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.069\n",
      " Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.157\n",
      " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.280\n",
      " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.332\n",
      " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.332\n",
      " Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.173\n",
      " Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.133\n",
      " Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.338\n",
      "\u001b[32m[03/11 14:19:26 d2.evaluation.coco_evaluation]: \u001b[0mEvaluation results for bbox: \n",
      "|   AP   |  AP50  |  AP75  |  APs  |  APm  |  APl   |\n",
      "|:------:|:------:|:------:|:-----:|:-----:|:------:|\n",
      "| 15.192 | 26.099 | 15.416 | 5.854 | 6.896 | 15.683 |\n",
      "\u001b[32m[03/11 14:19:26 d2.evaluation.coco_evaluation]: \u001b[0mPer-category bbox AP: \n",
      "| category                  | AP     | category               | AP     | category                | AP     |\n",
      "|:--------------------------|:-------|:-----------------------|:-------|:------------------------|:-------|\n",
      "| Car-Damage-Detection-1KxY | nan    | Bodypanel-Dent         | nan    | Front-Windscreen-Damage | 0.000  |\n",
      "| Headlight-Damage          | 0.159  | Rear-windscreen-Damage | 4.691  | RunningBoard-Dent       | 0.000  |\n",
      "| Sidemirror-Damage         | 0.000  | Signlight-Damage       | 0.000  | Taillight-Damage        | 1.915  |\n",
      "| back-bumper               | 8.847  | back-glass             | 11.426 | bonnet-dent             | 10.204 |\n",
      "| boot-dent                 | 0.000  | broken_lamp            | 36.883 | crack                   | 2.864  |\n",
      "| damaged-door              | 13.800 | damaged-front-bumper   | 3.073  | damaged-head-light      | 11.636 |\n",
      "| damaged-hood              | 17.142 | damaged-rear-bumper    | 3.133  | damaged-rear-window     | 14.666 |\n",
      "| damaged-tail-light        | 16.352 | damaged-trunk          | 10.597 | damaged-window          | 19.566 |\n",
      "| damaged-windscreen        | 37.589 | dent                   | 13.316 | dent-or-scratch         | 6.310  |\n",
      "| door                      | 21.072 | doorouter-dent         | 3.954  | fender-dent             | 1.308  |\n",
      "| flat_tire                 | 59.129 | front-bumper           | 42.454 | front-bumper-dent       | 1.597  |\n",
      "| front-glass               | 57.342 | headlight              | 35.633 | hood                    | 37.329 |\n",
      "| mirror                    | 27.522 | pillar-dent            | 0.000  | quaterpanel-dent        | 1.707  |\n",
      "| rear-bumper-dent          | 2.136  | roof-dent              | 0.000  | scratch                 | 17.691 |\n",
      "| shattered_glass           | 76.606 | taillight              | 24.674 | trunk                   | 12.467 |\n",
      "| wheel                     | 16.615 | window                 | 0.247  |                         |        |\n",
      "OrderedDict({'bbox': {'AP': 15.192315251490218, 'AP50': 26.09904851628815, 'AP75': 15.41600895240057, 'APs': 5.854183373658784, 'APm': 6.896370698493549, 'APl': 15.682715604080741, 'AP-Car-Damage-Detection-1KxY': nan, 'AP-Bodypanel-Dent': nan, 'AP-Front-Windscreen-Damage': 0.0, 'AP-Headlight-Damage': 0.1593108463388712, 'AP-Rear-windscreen-Damage': 4.691162827661252, 'AP-RunningBoard-Dent': 0.0, 'AP-Sidemirror-Damage': 0.0, 'AP-Signlight-Damage': 0.0, 'AP-Taillight-Damage': 1.914916766401915, 'AP-back-bumper': 8.847349392038078, 'AP-back-glass': 11.426034550607701, 'AP-bonnet-dent': 10.204189369351237, 'AP-boot-dent': 0.0, 'AP-broken_lamp': 36.88316768929145, 'AP-crack': 2.8635407690407098, 'AP-damaged-door': 13.80030828149349, 'AP-damaged-front-bumper': 3.0731023412029024, 'AP-damaged-head-light': 11.635550338681925, 'AP-damaged-hood': 17.141505904385937, 'AP-damaged-rear-bumper': 3.1334921085118763, 'AP-damaged-rear-window': 14.666027490084637, 'AP-damaged-tail-light': 16.352172588990307, 'AP-damaged-trunk': 10.596880619881913, 'AP-damaged-window': 19.56569446714497, 'AP-damaged-windscreen': 37.589061721619835, 'AP-dent': 13.315959467524799, 'AP-dent-or-scratch': 6.30965738957492, 'AP-door': 21.07150291962098, 'AP-doorouter-dent': 3.9544504839721, 'AP-fender-dent': 1.3084292776307203, 'AP-flat_tire': 59.129479476480874, 'AP-front-bumper': 42.4542782772345, 'AP-front-bumper-dent': 1.5973533413501766, 'AP-front-glass': 57.3418142302566, 'AP-headlight': 35.63326750386732, 'AP-hood': 37.329282889292436, 'AP-mirror': 27.5220290803094, 'AP-pillar-dent': 0.0, 'AP-quaterpanel-dent': 1.7073314474304575, 'AP-rear-bumper-dent': 2.1355687413457223, 'AP-roof-dent': 0.0, 'AP-scratch': 17.690844156490396, 'AP-shattered_glass': 76.60646563056558, 'AP-taillight': 24.674298551307484, 'AP-trunk': 12.467003578451541, 'AP-wheel': 16.614779871534623, 'AP-window': 0.24692193009024696}})\n"
     ]
    }
   ],
   "source": [
    "from detectron2.evaluation import COCOEvaluator, inference_on_dataset\n",
    "from detectron2.data import build_detection_test_loader\n",
    "\n",
    "evaluator = COCOEvaluator(\"car_damage_val\", cfg, False, output_dir=\"./output/\")\n",
    "val_loader = build_detection_test_loader(cfg, \"car_damage_val\")\n",
    "print(inference_on_dataset(trainer.model, val_loader, evaluator))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m[03/11 14:21:32 d2.checkpoint.detection_checkpoint]: \u001b[0m[DetectionCheckpointer] Loading from ./output/model_final.pth ...\n",
      "Predicted Classes: ['shattered_glass']\n"
     ]
    },
    {
     "ename": "error",
     "evalue": "OpenCV(4.10.0) /io/opencv/modules/highgui/src/window.cpp:1367: error: (-2:Unspecified error) The function is not implemented. Rebuild the library with Windows, GTK+ 2.x or Cocoa support. If you are on Ubuntu or Debian, install libgtk2.0-dev and pkg-config, then re-run cmake or configure script in function 'cvWaitKey'\n",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31merror\u001b[0m                                     Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[8], line 31\u001b[0m\n\u001b[1;32m     29\u001b[0m v \u001b[38;5;241m=\u001b[39m v\u001b[38;5;241m.\u001b[39mdraw_instance_predictions(outputs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minstances\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mto(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcpu\u001b[39m\u001b[38;5;124m\"\u001b[39m))\n\u001b[1;32m     30\u001b[0m cv2\u001b[38;5;241m.\u001b[39mimwrite(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moutput.jpg\u001b[39m\u001b[38;5;124m\"\u001b[39m, v\u001b[38;5;241m.\u001b[39mget_image()[:, :, ::\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]) \n\u001b[0;32m---> 31\u001b[0m \u001b[43mcv2\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwaitKey\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "\u001b[0;31merror\u001b[0m: OpenCV(4.10.0) /io/opencv/modules/highgui/src/window.cpp:1367: error: (-2:Unspecified error) The function is not implemented. Rebuild the library with Windows, GTK+ 2.x or Cocoa support. If you are on Ubuntu or Debian, install libgtk2.0-dev and pkg-config, then re-run cmake or configure script in function 'cvWaitKey'\n"
     ]
    }
   ],
   "source": [
    "import cv2\n",
    "from detectron2.engine import DefaultPredictor\n",
    "from detectron2.utils.visualizer import Visualizer\n",
    "from detectron2.data import MetadataCatalog\n",
    "\n",
    "cfg.MODEL.WEIGHTS = \"./output/model_final.pth\"\n",
    "cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5\n",
    "predictor = DefaultPredictor(cfg)\n",
    "\n",
    "image_path = f\"{dataset_path}/test/000269_jpg.rf.df40944b29ad5d9b144b86af2baef5b8.jpg\" \n",
    "image = cv2.imread(image_path)\n",
    "outputs = predictor(image)\n",
    "\n",
    "v = Visualizer(image[:, :, ::-1], MetadataCatalog.get(\"car_damage_train\"), scale=0.8)\n",
    "pred_classes = outputs[\"instances\"].pred_classes.tolist()  \n",
    "\n",
    "metadata = MetadataCatalog.get(\"car_damage_train\")\n",
    "class_names = metadata.get(\"thing_classes\", None)\n",
    "\n",
    "if class_names:\n",
    "    pred_labels = [class_names[i] for i in pred_classes] \n",
    "else:\n",
    "    pred_labels = pred_classes\n",
    "\n",
    "print(\"Predicted Classes:\", pred_labels)\n",
    "\n",
    "v = v.draw_instance_predictions(outputs[\"instances\"].to(\"cpu\"))\n",
    "cv2.imwrite(\"output.jpg\", v.get_image()[:, :, ::-1]) \n",
    "cv2.waitKey(0)\n"
   ]
  }
 ],
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