fixing some bugs

PNG_preparation.ipynb

@@ -192,13 +192,6 @@
     "- Note that here, the default colour map of the 1-tensor images is actually the viridis _cmap_ (yellow to dark purple), which is unexpected. This is a great example of why you should always check the dimensions of the image array, and never trust your naked eye alone!"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Let's first try to fix the issue of having different tensor dimensions by converting every image numpy array to a 1-tensor (i.e. convert the rbg pixel value encoding to a grayscale pixel value encoding):"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -209,19 +202,11 @@
     "\n",
     "images_adjusted = []\n",
     "for i in range(20):\n",
-    "    img=images[i]\n",
-    "    grayscale=rgb2gray(img)\n",
-    "    images_adjusted.append(grayscale)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [],
-   "source": [
+    "    img = images[i]\n",
+    "    if len(img.shape) != 2:\n",
+    "        grayscale=rgb2gray(img)\n",
+    "        images_adjusted.append(grayscale)\n",
+    "\n",
     "fig = plt.figure(figsize=(20, 15))\n",
     "rows = 5\n",
     "columns = 4\n",
@@ -315,16 +300,16 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "resized_images=[]\n",
-    "fig = plt.figure(figsize=(20, 15))\n",
-    "rows = 5\n",
-    "columns = 4\n",
-    "for i in range(20):\n",
-    "    fig.add_subplot(rows, columns, i+1)\n",
-    "    img=resized_images_array[i]\n",
-    "    plt.imshow(img)\n",
-    "    plt.axis('off')\n",
-    "    plt.title(img.shape)"
+    "# resized_images=[]\n",
+    "# fig = plt.figure(figsize=(20, 15))\n",
+    "# rows = 5\n",
+    "# columns = 4\n",
+    "# for i in range(20):\n",
+    "#     fig.add_subplot(rows, columns, i+1)\n",
+    "#     img=resized_images_array[i]\n",
+    "#     plt.imshow(img)\n",
+    "#     plt.axis('off')\n",
+    "#     plt.title(img.shape)"
    ]
   },
   {
@@ -341,14 +326,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "height=[]\n",
-    "width=[]\n",
-    "for i in range(20):\n",
-    "    img=images_adjusted[i]\n",
-    "    height.append(img.shape[0])\n",
-    "    width.append(img.shape[1])\n",
-    "print(f'Smallest image height: {min(height)}')\n",
-    "print(f'Smallest image width: {min(width)}')"
+    "# height=[]\n",
+    "# width=[]\n",
+    "# for i in range(20):\n",
+    "#     img=images_adjusted[i]\n",
+    "#     height.append(img.shape[0])\n",
+    "#     width.append(img.shape[1])\n",
+    "# print(f'Smallest image height: {min(height)}')\n",
+    "# print(f'Smallest image width: {min(width)}')"
    ]
   },
   {
@@ -357,13 +342,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "trimmed_images=[]\n",
-    "for i in range(20):\n",
-    "    img=images_adjusted[i]\n",
-    "    img_trim=img[0:min(height),0:min(width)]\n",
-    "    trimmed_images.append(img_trim)\n",
-    "trimmed_images_array = np.array(trimmed_images)\n",
-    "trimmed_images_array.shape"
+    "# trimmed_images=[]\n",
+    "# for i in range(20):\n",
+    "#     img=images_adjusted[i]\n",
+    "#     img_trim=img[0:min(height),0:min(width)]\n",
+    "#     trimmed_images.append(img_trim)\n",
+    "# trimmed_images_array = np.array(trimmed_images)\n",
+    "# trimmed_images_array.shape"
    ]
   },
   {
@@ -372,15 +357,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = plt.figure(figsize=(20, 15))\n",
-    "rows = 5\n",
-    "columns = 4\n",
-    "for i in range(20):\n",
-    "    fig.add_subplot(rows, columns, i+1)\n",
-    "    img=trimmed_images_array[i]\n",
-    "    plt.imshow(img)\n",
-    "    plt.axis('off')\n",
-    "    plt.title(img.shape)"
+    "# fig = plt.figure(figsize=(20, 15))\n",
+    "# rows = 5\n",
+    "# columns = 4\n",
+    "# for i in range(20):\n",
+    "#     fig.add_subplot(rows, columns, i+1)\n",
+    "#     img=trimmed_images_array[i]\n",
+    "#     plt.imshow(img)\n",
+    "#     plt.axis('off')\n",
+    "#     plt.title(img.shape)"
    ]
   },
   {
@@ -434,7 +419,7 @@
     "import matplotlib\n",
     "\n",
     "for i in range(20):\n",
-    "    img=images_adjusted[i]\n",
+    "    img = images_adjusted[i]\n",
     "    matplotlib.image.imsave(f'adjusted_images/img_{i}.png', img) "
    ]
   },
@@ -648,7 +633,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -662,7 +647,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.8"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,