Extending the napari viewer with a widget, mousebinding and event callback

extending_napari_viewer.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import napari\n",
    "import numpy as np\n",
    "\n",
    "from enum import Enum\n",
    "from functools import partial\n",
    "from magicgui import magic_factory\n",
    "from skimage.filters import (\n",
    "    threshold_isodata,\n",
    "    threshold_li,\n",
    "    threshold_otsu,\n",
    "    threshold_triangle,\n",
    "    threshold_yen,\n",
    ")\n",
    "from skimage.measure import label\n",
    "from scipy.ndimage import center_of_mass\n",
    "DATA_PATH = '~/PhD/data/toy_data/easy-no-divide-swaps/Fluo-N2DL-HeLa.tif'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# very simple thresholding based segmentation widget\n",
    "class Threshold(Enum):\n",
    "    isodata = partial(threshold_isodata)\n",
    "    li = partial(threshold_li)\n",
    "    otsu = partial(threshold_otsu)\n",
    "    triangle = partial(threshold_triangle)\n",
    "    yen = partial(threshold_yen)\n",
    "\n",
    "@magic_factory\n",
    "def segment_by_threshold(\n",
    "    img_layer: \"napari.layers.Image\", threshold: Threshold\n",
    ") -> \"napari.types.LayerDataTuple\":\n",
    "\n",
    "    seg_labels = np.zeros_like(img_layer.data)\n",
    "    for i in range(len(img_layer.data)):\n",
    "        frame = img_layer.data[i]\n",
    "        # need to use threshold.value to get the function from the enum member\n",
    "        threshold_val = threshold.value(frame)\n",
    "        binarised_im = frame > threshold_val\n",
    "        seg_labels[i] = label(binarised_im)\n",
    "\n",
    "    seg_layer = (seg_labels, {\"name\": f\"{img_layer.name}_seg\"}, \"labels\")\n",
    "\n",
    "    return seg_layer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<napari._qt.widgets.qt_viewer_dock_widget.QtViewerDockWidget at 0x7fea109a3430>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
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     "text": [
      "ERROR:tornado.general:Uncaught exception in ZMQStream callback\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/draga/miniconda3/envs/janelia-talk/lib/python3.9/site-packages/zmq/eventloop/zmqstream.py\", line 556, in _run_callback\n",
      "    callback(*args, **kwargs)\n",
      "  File \"/home/draga/miniconda3/envs/janelia-talk/lib/python3.9/site-packages/jupyter_client/threaded.py\", line 123, in _handle_recv\n",
      "    msg_list = self.ioloop._asyncio_event_loop.run_until_complete(get_msg(future_msg))\n",
      "  File \"/home/draga/miniconda3/envs/janelia-talk/lib/python3.9/asyncio/base_events.py\", line 623, in run_until_complete\n",
      "    self._check_running()\n",
      "  File \"/home/draga/miniconda3/envs/janelia-talk/lib/python3.9/asyncio/base_events.py\", line 585, in _check_running\n",
      "    raise RuntimeError(\n",
      "RuntimeError: Cannot run the event loop while another loop is running\n",
      "ERROR:tornado.general:Uncaught exception in zmqstream callback\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/draga/miniconda3/envs/janelia-talk/lib/python3.9/site-packages/zmq/eventloop/zmqstream.py\", line 577, in _handle_events\n",
      "    self._handle_recv()\n",
      "  File \"/home/draga/miniconda3/envs/janelia-talk/lib/python3.9/site-packages/zmq/eventloop/zmqstream.py\", line 606, in _handle_recv\n",
      "    self._run_callback(callback, msg)\n",
      "  File \"/home/draga/miniconda3/envs/janelia-talk/lib/python3.9/site-packages/zmq/eventloop/zmqstream.py\", line 556, in _run_callback\n",
      "    callback(*args, **kwargs)\n",
      "  File \"/home/draga/miniconda3/envs/janelia-talk/lib/python3.9/site-packages/jupyter_client/threaded.py\", line 123, in _handle_recv\n",
      "    msg_list = self.ioloop._asyncio_event_loop.run_until_complete(get_msg(future_msg))\n",
      "  File \"/home/draga/miniconda3/envs/janelia-talk/lib/python3.9/asyncio/base_events.py\", line 623, in run_until_complete\n",
      "    self._check_running()\n",
      "  File \"/home/draga/miniconda3/envs/janelia-ta"
     ]
    }
   ],
   "source": [
    "viewer = napari.Viewer()\n",
    "cells_image = viewer.open(DATA_PATH)[0]\n",
    "\n",
    "widget = segment_by_threshold()\n",
    "viewer.window.add_dock_widget(widget)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "cell_labels = viewer.layers[-1]\n",
    "\n",
    "def move_point_to_label_center(event):\n",
    "    points_layer = event.source\n",
    "    layer_data = event.value\n",
    "    # round latest point so we can find the label value underneath\n",
    "    latest_point = np.round(layer_data[-1]).astype(cell_labels.data.dtype)\n",
    "    label_val_at_point = cell_labels.data[tuple(latest_point)]\n",
    "    # pass through just the frame we added the point to, so we can get center of mass\n",
    "    data_slice = latest_point[0]\n",
    "    label_center = center_of_mass(cells_image.data[data_slice], cell_labels.data[data_slice], label_val_at_point)\n",
    "    new_point = [data_slice, *label_center]\n",
    "    # block data event when we're changing the point to avoid an infinite loop\n",
    "    with points_layer.events.data.blocker():\n",
    "        points_layer.data[-1] = new_point\n",
    "    points_layer.refresh()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "points_layer = viewer.add_points(ndim=3)\n",
    "points_layer.events.data.connect(move_point_to_label_center)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add keybinding on labels layer to add point with same color as the label underneath\n",
    "@cell_labels.mouse_drag_callbacks.append\n",
    "def add_point_with_label_color(layer, event):\n",
    "    if (len(event.modifiers) == 1\n",
    "            and event.modifiers[0].name == 'Alt'):\n",
    "        # rounding mouse position to integer coordinates\n",
    "        data_pos = np.round(event.position).astype(layer.data.dtype)\n",
    "        label_color = layer.get_color(layer.data[tuple(data_pos)])   \n",
    "        # add points layer if it doesn't already exist\n",
    "        if 'cell_points' not in viewer.layers:\n",
    "            points_layer = viewer.add_points(name='cell_points', ndim=3)\n",
    "            points_layer.events.data.connect(move_point_to_label_center)\n",
    "            viewer.layers.selection.active = cell_labels\n",
    "        # add a point to the (potentially newly created points layer)\n",
    "        points_layer = viewer.layers['cell_points']\n",
    "        points_layer.current_face_color = label_color\n",
    "        points_layer.add(event.position)\n",
    "        points_layer.selected_data.clear()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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