Created using Colaboratory

Author: Nada-Nasser

image_classification_api.ipynb

@@ -5,7 +5,7 @@
     "colab": {
       "name": "image_classification_api.ipynb",
       "provenance": [],
-      "authorship_tag": "ABX9TyPfIvL8gBIX/AmhLYjFsMxz",
+      "authorship_tag": "ABX9TyMhXgOvQyLiMY4uFPYQMak+",
       "include_colab_link": true
     },
     "kernelspec": {
@@ -182,18 +182,24 @@
       "source": [
         "## Receive Post request to classify the image included in its body\n",
         "\n",
-        "Using **fastapi** lib, we create a path to be used in a post request url to call the function named ***classifyimage***, in the post request body, there should be a json object that has an image in 64-base format.\n",
-        "request body ex.:\n",
+        "Using **`fastapi`** lib, we create a path to be used in a post request url to call the function named **`classifyimage`**, in the post request body, there should be a json object that has an image in 64-base format.\n",
+        "* request body ex.:\n",
         "```\n",
         "{\n",
         "  file:\"64-base encoded image\"\n",
         "}\n",
         "```\n",
         "\n",
-        "in ***classifyimage*** function:\n",
+        "in **`classifyimage`** function:\n",
+        "\n",
+        "1.   Convert the 64-base encoded image to **`png`** file and save the generated image in \"**`imageToSave.png`**\" file.\n",
+        "2.   call **`get_animal_name`** to get the animal name from the image using image recognition model.\n",
+        "3. replace all white spaces in the animal name with underscore ( **`_`** ).\n",
+        "4. convert all letters in the animal name to lowercase.\n",
+        "5. use **`Classify`** class to classify the animal using its name and return **`True`** if it not a wild animal and return **`False`** otherwise\n",
+        "\n",
+        "\n",
         "\n",
-        "*   Convert the 64-base encoded image to **png** file and save the generated image in \"imageToSave.png\" file\n",
-        "*   call *get_animal_name* to get the animal name from the image using image recognition model\n",
         "\n"
       ]
     },
@@ -233,6 +239,17 @@
       "execution_count": null,
       "outputs": []
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "g0f-oq5kQeRV"
+      },
+      "source": [
+        "## **Calssify class**\n",
+        "Using wordnet synsets and hypernyms, this class used to know if the animal_name is belong to **`domestic_animal`**, **`birds`** or **`entity`** using **dfs** algorithm.\n",
+        "Then if the animal_name belongs to  **`domestic_animal`**, **`birds`** then the function returns **`True`**, otherwise returns **`False`**"
+      ]
+    },
     {
       "cell_type": "code",
       "metadata": {