Modernize stackoverflow examples

Author: jni

lectures/stackoverflow_challenges.ipynb

@@ -22,8 +22,8 @@
    "source": [
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
-    "from skimage import (filter as filters, io, color,\n",
-    "                     exposure, segmentation, morphology, img_as_float)"
+    "from skimage import (filters, io, color, exposure, feature,\n",
+    "                     segmentation, morphology, img_as_float)"
    ]
   },
   {
@@ -50,31 +50,32 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "from scipy.signal import convolve2d\n",
+    "from scipy import ndimage as ndi\n",
     "\n",
-    "img = color.rgb2gray(io.imread('../images/snakes.png'))\n",
+    "image = color.rgb2gray(io.imread('../images/snakes.png'))\n",
     "\n",
     "# Reduce all lines to one pixel thickness\n",
-    "snakes = morphology.skeletonize(img < 1)\n",
+    "snakes = morphology.skeletonize(image < 1).astype(np.uint8)\n",
     "\n",
     "# Find pixels with only one neighbor\n",
-    "corners = convolve2d(snakes, [[1, 1, 1],\n",
-    "                              [1, 0, 1],\n",
-    "                              [1, 1, 1]], mode='same') == 1\n",
-    "corners = corners & snakes\n",
+    "neighbor_kernel = np.array([[1, 1, 1],\n",
+    "                            [1, 0, 1],\n",
+    "                            [1, 1, 1]])\n",
+    "num_neighbors = ndi.convolve(snakes, neighbor_kernel,\n",
+    "                             mode='constant')\n",
+    "corners = (num_neighbors == 1) & snakes\n",
     "\n",
     "# Those are the start and end positions of the segments\n",
-    "y, x = np.where(corners)\n",
+    "rr, cc = np.nonzero(corners)\n",
+    "\n",
+    "fig, ax = plt.subplots()\n",
+    "ax.imshow(img, cmap='gray')\n",
+    "ax.scatter(cc, rr)\n",
+    "ax.set_axis_off()\n",
     "\n",
-    "plt.figure(figsize=(10, 5))\n",
-    "plt.imshow(img, cmap=plt.cm.gray, interpolation='nearest')\n",
-    "plt.scatter(x, y)\n",
-    "plt.axis('off')\n",
     "plt.show()"
    ]
   },
@@ -108,7 +109,7 @@
    "source": [
     "image = io.imread(\"../images/round_pill.jpg\")\n",
     "image_equalized = exposure.equalize_adapthist(image)\n",
-    "edges = filters.canny(color.rgb2gray(image_equalized))\n",
+    "edges = feature.canny(color.rgb2gray(image_equalized))\n",
     "\n",
     "f, (ax0, ax1, ax2) = plt.subplots(1, 3, figsize=(15, 8))\n",
     "ax0.imshow(image)\n",
@@ -125,6 +126,7 @@
    "outputs": [],
    "source": [
     "from skimage import measure\n",
+    "from matplotlib.patches import Circle\n",
     "\n",
     "coords = np.column_stack(np.nonzero(edges))\n",
     "\n",
@@ -138,7 +140,7 @@
     "\n",
     "f, ax = plt.subplots()\n",
     "ax.imshow(image, cmap='gray');\n",
-    "circle = plt.Circle((col, row), radius=radius, edgecolor='green', linewidth=2, fill=False)\n",
+    "circle = Circle((col, row), radius=radius, edgecolor='C9', linewidth=2, fill=False)\n",
     "ax.add_artist(circle);"
    ]
   },
@@ -172,16 +174,16 @@
    },
    "outputs": [],
    "source": [
-    "from skimage import restoration, color, io, filter as filters, morphology\n",
+    "from skimage import restoration, color, io, feature, morphology\n",
     "\n",
     "image = color.rgb2gray(io.imread('../images/fingers.png'))\n",
     "denoised = restoration.denoise_tv_bregman(image, 1)\n",
-    "edges = filters.canny(denoised, low_threshold=0.01, high_threshold=0.21)\n",
+    "edges = feature.canny(denoised, low_threshold=0.01, high_threshold=0.21)\n",
     "\n",
-    "fig, axes = plt.subplots(1, 2, figsize=(15, 10))\n",
-    "axes[0].imshow(denoised, cmap='gray')\n",
-    "axes[1].imshow(edges, cmap='gray')\n",
-    "for ax in axes:\n",
+    "fig, (ax0, ax1) = plt.subplots(1, 2, figsize=(15, 10))\n",
+    "ax0.imshow(denoised, cmap='gray')\n",
+    "ax1.imshow(edges, cmap='gray')\n",
+    "for ax in (ax0, ax1):\n",
     "    ax.set_axis_off()"
    ]
   },
@@ -203,7 +205,7 @@
     "*Hint:*\n",
     "\n",
     "1. Equalize\n",
-    "2. Threshold (``filter.otsu`` or ``filters.otsu``, depending on version)\n",
+    "2. Threshold (``filters.threshold_otsu``)\n",
     "3. Remove objects touching boundary (``segmentation.clear_border``)\n",
     "4. Apply morphological closing (``morphology.closing``)\n",
     "5. Remove small objects (``measure.regionprops``)\n",
@@ -219,7 +221,8 @@
    "outputs": [],
    "source": [
     "from skimage import data\n",
-    "plt.imshow(data.coins(), cmap='gray');"
+    "fig, ax = plt.subplots()\n",
+    "ax.imshow(data.coins(), cmap='gray');"
    ]
   },
   {
@@ -230,14 +233,13 @@
    },
    "outputs": [],
    "source": [
-    "from scipy import ndimage\n",
     "from skimage import segmentation\n",
     "\n",
     "image = data.coins()\n",
     "equalized = exposure.equalize_adapthist(image)\n",
-    "edges = equalized > filters.threshold_otsu(equalized)\n",
-    "edges = segmentation.clear_border(edges)\n",
-    "edges = morphology.closing(edges, morphology.square(3))\n",
+    "binary0 = equalized > filters.threshold_otsu(equalized)\n",
+    "binary1 = segmentation.clear_border(binary0)\n",
+    "binary2 = morphology.closing(binary1, morphology.square(3))\n",
     "\n",
     "f, (ax0, ax1) = plt.subplots(1, 2)\n",
     "ax0.imshow(image, cmap='gray')\n",
@@ -247,21 +249,16 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "labels = measure.label(edges)\n",
-    "for region in measure.regionprops(labels):\n",
-    "    if region.area < 200:\n",
-    "        rows, cols = region.coords.T\n",
-    "        labels[rows, cols] = 0\n",
-    "\n",
-    "print(\"Number of coins:\", len(np.unique(labels)) - 1)\n",
-    "        \n",
-    "out = color.label2rgb(labels, image, bg_label=0)\n",
-    "plt.imshow(out);"
+    "labels = ndi.label(binary2)[0]\n",
+    "labels_big = morphology.remove_small_objects(labels)\n",
+    "print(\"Number of coins:\", len(np.unique(labels_big)[1:]))\n",
+    "\n",
+    "out = color.label2rgb(labels_big, image, bg_label=0)\n",
+    "fig, ax = plt.subplots()\n",
+    "ax.imshow(out);"
    ]
   },
   {
@@ -530,9 +527,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.6.3"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }