look at size statistics

build_dataset.ipynb

@@ -9,7 +9,10 @@
    "source": [
     "from glob import glob\n",
     "from datasets import Dataset, Features, Image, Value\n",
-    "from PIL import Image as PILImage"
+    "from PIL import Image as PILImage\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import torch"
    ]
   },
   {
@@ -24,7 +27,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 19,
    "id": "e4ffa17d-3a4e-4c84-bf1b-905001deff29",
    "metadata": {},
    "outputs": [],
@@ -32,24 +35,24 @@
     "def load_image(sample):\n",
     "    image_path = sample['path']\n",
     "    image = PILImage.open(image_path)\n",
-    "    return {\"image\": image}"
+    "    return {\"image\": image, \"w\":image.width, \"h\":image.height, \"mode\":image.mode, \"aspect\":image.width/image.height}"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 20,
    "id": "115873bf-a6ba-4a9d-a4c1-c2507b558e39",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f74bebabb9e142dea3c5e4896707a0cd",
+       "model_id": "3f1a61826305422a8bbf3577dff36e09",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Map:   0%|          | 0/25000 [00:00<?, ? examples/s]"
+       "Map:   0%|          | 0/40000 [00:00<?, ? examples/s]"
       ]
      },
      "metadata": {},
@@ -59,6 +62,90 @@
    "source": [
     "LSDIR = LSDIR_paths.map(load_image)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "0a37bca8-fca2-4faf-9a1d-dec46bf8f548",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "all(mode == 'RGB' for mode in LSDIR['mode'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "cede2255-099d-416b-b359-4eddb3a641c6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(LSDIR['aspect'],bins=15,alpha=0.7);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "0ee68902-8cbf-404f-9141-85230b8ef0e6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "540\n",
+      "540\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print(min(LSDIR['h']))\n",
+    "print(min(LSDIR['w']))\n",
+    "plt.hist(LSDIR['h'],bins=15,alpha=0.7);\n",
+    "plt.hist(LSDIR['w'],bins=15,alpha=0.7);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "8dabc199-e8af-4bc8-9a70-34ed2fe5199a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "LSDIR_sort = LSDIR.sort(\"aspect\")"
+   ]
   }
  ],
  "metadata": {