reconstruct_pipeline.ipynb

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   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from skimage import io\n",
    "import pix2vertex as p2v\n",
    "\n",
    "matplotlib.rcParams['figure.figsize'] = (13,7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initializations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "detector = p2v.Detector()\n",
    "reconstructor = p2v.Reconstructor(detector=detector)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "im_path = 'examples/sample.jpg' # im_path can be a URL as well!\n",
    "img = io.imread(im_path) \n",
    "fig = plt.figure()\n",
    "plt.imshow(img)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "img_crop = detector.detect_and_crop(img)\n",
    "fig = plt.figure()\n",
    "plt.imshow(img_crop)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "net_res = reconstructor.run_net(img_crop)\n",
    "p2v.vis_net_result(img_crop,net_res)\n",
    "final_res = reconstructor.post_process(net_res)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Interactive Visualizations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot = p2v.vis_depth_interactive(final_res['Z_surface'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot = p2v.vis_pcloud_interactive(final_res,img_crop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fallback matplotlib visualization\n",
    "p2v.vis_depth_matplotlib(img_crop,final_res['Z_surface'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Saving Result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "p2v.save2stl(final_res['Z_surface'],'res.stl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create link to make accessible from notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import FileLink\n",
    "FileLink('res.stl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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