Annotation tool 4 0

This merge finished the MVP version of the annotation tool

docs/notebooks/annotation_tool.ipynb

 {
  "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Image annotation tool\n",
-    "This notebook shows how the annotation interface can be used to create masks for images"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -15,113 +7,19 @@
    "outputs": [],
    "source": [
     "import qim3d\n",
+    "from scipy import ndimage\n",
     "import matplotlib.pyplot as plt\n",
-    "import matplotlib as mpl\n",
-    "import numpy as np\n",
-    "%matplotlib inline"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Load 2D example image\n",
-    "img = qim3d.examples.blobs_256x256\n",
+    "qim3d.io.logger.level(\"info\")\n",
+    "\n",
+    "# Load example image\n",
+    "img = qim3d.examples.bone_128x128x128\n",
     "\n",
-    "# Display image\n",
-    "plt.imshow(img)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
     "# Start annotation tool\n",
     "interface = qim3d.gui.annotation_tool.Interface()\n",
-    "interface.max_masks = 4\n",
     "\n",
     "# We can directly pass the image we loaded to the interface\n",
-    "interface.launch(img=img)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# When 'prepare mask for download' is pressed once, the mask can be retrieved with the get_result() method\n",
-    "mask = interface.get_result()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Check the obtained mask"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "print (f\"Original image shape..: {img.shape}\")\n",
-    "print (f\"Mask image shape......: {mask.shape}\")\n",
-    "print (f\"\\nNumber of masks: {np.max(mask)}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Show the masked regions"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%matplotlib inline\n",
-    "\n",
-    "nmasks = np.max(mask)\n",
-    "fig, axs = plt.subplots(nrows=1, ncols=nmasks+2, figsize=(12,3))\n",
-    "\n",
-    "# Show original image\n",
-    "axs[0].imshow(img)\n",
-    "axs[0].set_title(\"Original\")\n",
-    "axs[0].axis('off')\n",
-    "\n",
-    "\n",
-    "# Show masks\n",
-    "cmap = mpl.colormaps[\"rainbow\"].copy()\n",
-    "cmap.set_under(color='black') # Sets the background to black\n",
-    "axs[1].imshow(mask, interpolation='none', cmap=cmap, vmin=1, vmax=nmasks+1)\n",
-    "axs[1].set_title(\"Masks\")\n",
-    "axs[1].axis('off')\n",
-    "\n",
-    "# Show masked regions\n",
-    "for idx in np.arange(2, nmasks+2):\n",
-    "    mask_id = idx-1\n",
-    "    submask = mask.copy()\n",
-    "    submask[submask != mask_id] = 0\n",
-    "    \n",
-    "    masked_img = img.copy()\n",
-    "    masked_img[submask==0] = 0\n",
-    "    axs[idx].imshow(masked_img)\n",
-    "    axs[idx].set_title(f\"Mask {mask_id}\")\n",
-    "\n",
-    "    axs[idx].axis('off')\n",
-    "\n",
-    "plt.show()"
+    "#interface.launch()\n",
+    "interface.launch(ndimage.zoom(img[0], 3, order=0))"
    ]
   }
  ],
@@ -141,9 +39,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.11"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }