inference_demo.ipynb 2.04 KB
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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [],
   "source": [
    "from mmdet3d.apis import init_detector, inference_detector, show_result_meshlab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [],
   "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'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [],
   "source": [
    "# build the model from a config file and a checkpoint file\n",
    "model = init_detector(config_file, checkpoint_file, device='cuda:0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [],
   "source": [
    "# test a single sample\n",
    "pcd = 'kitti_000008.bin'\n",
    "result, data = inference_detector(model, pcd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [],
   "source": [
    "# show the results\n",
    "out_dir = './'\n",
    "show_result_meshlab(data, result, out_dir)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
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  "pycharm": {
   "stem_cell": {
    "cell_type": "raw",
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    "metadata": {
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 "nbformat": 4,
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