forced images resize to 224x224

Author: Maxime Voisin

examples/integrations/huggingface/huggingface.ipynb

@@ -16,12 +16,12 @@
       "metadata": {},
       "source": [
         "<td>\n",
-        "<a href=\"https://colab.research.google.com/github/Labelbox/labelbox-python/blob/master/examples/integrations/huggingface/huggingface.ipynb\" target=\"_blank\"><img\n",
+        "<a href=\"https://colab.research.google.com/github/Labelbox/labelbox-python/blob/master/examples/basics/huggingface.ipynb\" target=\"_blank\"><img\n",
         "src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"></a>\n",
         "</td>\n",
         "\n",
         "<td>\n",
-        "<a href=\"https://github.com/Labelbox/labelbox-python/tree/master/examples/integrations/huggingface/huggingface.ipynb\" target=\"_blank\"><img\n",
+        "<a href=\"https://github.com/Labelbox/labelbox-python/tree/master/examples/basics/huggingface.ipynb\" target=\"_blank\"><img\n",
         "src=\"https://img.shields.io/badge/GitHub-100000?logo=github&logoColor=white\" alt=\"GitHub\"></a>\n",
         "</td>"
       ],
@@ -50,8 +50,8 @@
       "cell_type": "code",
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stdout",
+          "output_type": "stream",
           "text": [
             "\u001b[?25l     \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m0.0/190.5 KB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m190.5/190.5 KB\u001b[0m \u001b[31m7.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
@@ -269,7 +269,7 @@
         "      data_row_urls_chunk = data_row_urls[i:i+batch_size]\n",
         "      data_row_ids_chunk = data_row_ids[i:i+batch_size]\n",
         "      # download images\n",
-        "      imgs = [PIL.Image.open(requests.get(data_row_url, stream=True).raw).convert('RGB') for data_row_url in data_row_urls_chunk]\n",
+        "      imgs = [PIL.Image.open(requests.get(data_row_url, stream=True).raw).convert('RGB').resize((224, 224)) for data_row_url in data_row_urls_chunk]\n",
         "      # process images\n",
         "      img_hf = image_processor(imgs, return_tensors=\"pt\")\n",
         "      # generate resnet embeddings, thanks to inference\n",
@@ -711,4 +711,4 @@
       "execution_count": null
     }
   ]
-}
+}