inference_demo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "source": [
    "from mmdet3d.apis import inference_detector, init_model\n",
    "from mmdet3d.registry import VISUALIZERS\n",
    "from mmdet3d.utils import register_all_modules"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "/home/PJLAB/zhuchenming/mmdet3d_refactor/mmengine/mmengine/model/utils.py:800: UserWarning: Cannot import torch.fx, `merge_dict` is a simple function to merge multiple dicts\n",
      "  warnings.warn('Cannot import torch.fx, `merge_dict` is a simple function '\n"
     ]
    }
   ],
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "# register all modules in mmdet3d into the registries\n",
    "register_all_modules()"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "/home/PJLAB/zhuchenming/mmdet3d_refactor/mmdetection3d/mmdet3d/models/backbones/mink_resnet.py:10: UserWarning: Please follow `getting_started.md` to install MinkowskiEngine.`\n",
      "  'Please follow `getting_started.md` to install MinkowskiEngine.`')\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "source": [
    "config_file = '../configs/second/hv_second_secfpn_6x8_80e_kitti-3d-car.py'\n",
    "# download the checkpoint from model zoo and put it in `checkpoints/`\n",
    "checkpoint_file = '../work_dirs/second/epoch_40.pth'"
   ],
   "outputs": [],
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "source": [
    "# build the model from a config file and a checkpoint file\n",
    "model = init_model(config_file, checkpoint_file, device='cuda:0')"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "/home/PJLAB/zhuchenming/mmdet3d_refactor/mmdetection3d/mmdet3d/models/dense_heads/anchor3d_head.py:93: UserWarning: dir_offset and dir_limit_offset will be depressed and be incorporated into box coder in the future\n",
      "  'dir_offset and dir_limit_offset will be depressed and be '\n"
     ]
    },
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "local loads checkpoint from path: /home/PJLAB/zhuchenming/checkpoints/hv_second_secfpn_6x8_80e_kitti-3d-3class_20210831_022017-ae782e87.pth\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "source": [
    "# init visualizer\n",
    "visualizer = VISUALIZERS.build(model.cfg.visualizer)\n",
    "visualizer.dataset_meta = {\n",
    "    'CLASSES': model.CLASSES,\n",
    "    'PALETTE': model.PALETTE\n",
    "}"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "/home/PJLAB/zhuchenming/mmdet3d_refactor/mmengine/mmengine/visualization/visualizer.py:167: UserWarning: `Visualizer` backend is not initialized because save_dir is None.\n",
      "  warnings.warn('`Visualizer` backend is not initialized '\n"
     ]
    },
    {
     "output_type": "display_data",
     "data": {
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       "<Figure size 432x288 with 1 Axes>"
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  {
   "cell_type": "code",
   "execution_count": 11,
   "source": [
    "# test a single sample\n",
    "pcd = './data/kitti/000008.bin'\n",
    "result, data = inference_detector(model, pcd)\n",
    "points = data['inputs']['points']\n",
    "data_input = dict(points=points)"
   ],
   "outputs": [],
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "source": [
    "# show the results\n",
    "out_dir = './'\n",
    "visualizer.add_datasample(\n",
    "    'result',\n",
    "    data_input,\n",
    "    pred_sample=result,\n",
    "    show=True,\n",
    "    wait_time=0,\n",
    "    out_file=out_dir,\n",
    "    vis_task='det')"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "\u001b[1;33m[Open3D WARNING] invalid color in PaintUniformColor, clipping to [0, 1]\n",
      "\u001b[0;m\u001b[1;33m[Open3D WARNING] invalid color in PaintUniformColor, clipping to [0, 1]\n",
      "\u001b[0;m"
     ]
    }
   ],
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