simplify more

Author: dnth

examples/analyzing-kaggle-datasets.ipynb

@@ -18,13 +18,7 @@
     "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/visual-layer/fastdup/blob/main/examples/analyzing-kaggle-datasets.ipynb)\n",
     "[![Open in Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://github.com/visual-layer/fastdup/blob/main/examples/analyzing-kaggle-datasets.ipynb)\n",
     "\n",
-    "This notebook shows how you can use fastdup to analyze any datasets from [Kaggle](https://kaggle.com).\n",
-    "\n",
-    "We will analyze an image classification dataset for:\n",
-    "\n",
-    "+ Duplicates / near-duplicates.\n",
-    "+ Outliers.\n",
-    "+ Wrong labels."
+    "This notebook shows how you can use [fastdup](https://github.com/visual-layer/fastdup) to analyze any computer vision datasets from [Kaggle](https://kaggle.com)."
    ]
   },
   {
@@ -181,6 +175,14 @@
     "!unzip -q the-rvlcdip-dataset-test.zip"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "1f8d6b66-3f53-4afb-b040-c5d91a628608",
+   "metadata": {},
+   "source": [
+    "Once completed, we should have a folder with the name `test/` which contains all the images from the dataset."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "41f2abee-1251-4500-8ebf-90c593b6157a",
@@ -246,6 +248,14 @@
     "## Run fastdup"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "a10910f4-b772-400b-96b6-f44b62b97fe0",
+   "metadata": {},
+   "source": [
+    "To run fastdup, we only need to point `input_dir` to the folder containing images from the dataset."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 6,