test_cases/remove_labels_on_edges.ipynb

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    "def remove_labels_on_edges(label_image):\n",
    "    \"\"\"\n",
    "    Takes a label_image and removes all objects which touch the image border.\n",
    "    \"\"\"\n",
    "    import skimage\n",
    "    return skimage.segmentation.clear_border(label_image)"
   ]
  },
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    "def check(candidate):\n",
    "    import numpy as np\n",
    "    \n",
    "    result = candidate(np.asarray([\n",
    "        [0,0,0,0,0],\n",
    "        [1,2,2,0,0],\n",
    "        [1,2,2,0,0],\n",
    "        [1,0,0,3,0],\n",
    "        [0,0,0,4,0],\n",
    "    ]))\n",
    "\n",
    "    # -1 becaue background counts\n",
    "    assert len(np.unique(result)) - 1 == 2\n",
    "    assert result.shape[0] == 5\n",
    "    assert result.shape[1] == 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e4789ed1-dc01-46a6-80b2-dd98d8d7b875",
   "metadata": {},
   "outputs": [],
   "source": [
    "check(remove_labels_on_edges)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b38939da-37b8-4572-8227-b35354f3d60d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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