{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ab3fb8b5-37a4-4aae-8e1a-0ebc99ef1eac",
   "metadata": {
    "tags": []
   },
   "source": [
    "# 1. Rekognition Re-Index Solution"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26bea671-a45f-4d54-a685-85b94e91f3cc",
   "metadata": {},
   "source": [
    "This notebook contains scripts to help you deploy and use the solution.\n",
    "\n",
    "⚠️ **Please use notebook 0-Data-Preparation before running this notebook** ⚠️ \n",
    "\n",
    "**Notebook Steps:**\n",
    "1. Import libraries and clients\n",
    "2. Define variables\n",
    "3. Deploy and launch the solution\n",
    "4. Analyze the results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c374bb0a-b5bf-454b-881c-c36a6ddea3f4",
   "metadata": {
    "tags": []
   },
   "source": [
    "## 1. Import Libraries and Clients"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "705a2c73-b630-4d40-8969-04f0bcb63084",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import boto3, json, os, logging, sagemaker, time\n",
    "from botocore.exceptions import ClientError\n",
    "from zipfile import ZipFile\n",
    "rekClient = boto3.client('rekognition')\n",
    "dynamoClient = boto3.client('dynamodb')\n",
    "sfClient = boto3.client('stepfunctions')\n",
    "cfClient = boto3.client('cloudformation')\n",
    "sm_session = sagemaker.Session()\n",
    "boto3_session = boto3.session.Session()\n",
    "boto3_region = boto3_session.region_name"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6aac8527-b15e-41a0-a31b-0ad6c521d231",
   "metadata": {
    "tags": []
   },
   "source": [
    "## 2. Define Variables"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f44d8bb5-88a7-4ddb-bf00-f5a52f4e3cb8",
   "metadata": {},
   "source": [
    "If you have run the previous notebook you will find the details in the last cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b0a03f9a-78a3-4e77-a812-97c2baef1ee2",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "old_CollectionId =\"\"\n",
    "new_CollectionId =\"\"\n",
    "s3_bucket_name =\"\"\n",
    "records_folder =\"\"\n",
    "records_filename =\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "913b86ce-a1fa-42e6-9ca7-5f4e804a5405",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "stack_name = \"\" ## Specify a unique name for the stack\n",
    "RekognitionIndexFacesQualityFilter = \"AUTO\"\n",
    "RekognitionIndexFacesTPSLimit = \"50\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f4362ff-3271-46d5-9519-49e15031458b",
   "metadata": {
    "tags": []
   },
   "source": [
    "## 3. Deploy and launch the solution"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac0ac5d0-092d-4377-9106-4cba2a86d686",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### 3.1 Prepare and upload the necessary assets "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b7a74f6e-4478-4d76-9890-d93117fb1455",
   "metadata": {},
   "outputs": [],
   "source": [
    "lambda_folder = \"assets/lambda_functions\"\n",
    "for file in os.listdir(lambda_folder):\n",
    "    root,ext = os.path.splitext(file)\n",
    "    if ext == \".py\":\n",
    "        with ZipFile(\"{}/{}.zip\".format(lambda_folder,root),'w') as zip:\n",
    "            zip.write(\"{}/{}\".format(lambda_folder,file),file)\n",
    "            zip.close()\n",
    "        asset_s3_uri = sm_session.upload_data(\"{}/{}.zip\".format(lambda_folder,root), s3_bucket_name, lambda_folder)\n",
    "        print(\"Your function asset is located in {}\".format(asset_s3_uri))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9662efcf-02e1-41b8-938f-fca639bd03d3",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### 3.2 Deploy the Amazon CloudFormation template "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99c0c825-5f6a-4f18-8e64-3f56fa0cd665",
   "metadata": {
    "tags": []
   },
   "source": [
    "The cloudformation stack deployment should take around 3 minutes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "28264b26-db2a-4929-95d4-8eadf301a545",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "with open('{}/{}'.format(\"assets/cloudformation_template\",\"template.yaml\"), 'r') as file:\n",
    "    template_body = file.read()\n",
    "    file.close()\n",
    "    \n",
    "response_cft = cfClient.create_stack(\n",
    "    StackName= stack_name,\n",
    "    TemplateBody= template_body,\n",
    "    Parameters=[\n",
    "        {\n",
    "            'ParameterKey': 'AssetsBucket',\n",
    "            'ParameterValue': s3_bucket_name,\n",
    "        },\n",
    "        {\n",
    "            'ParameterKey': 'RekognitionIndexFacesQualityFilter',\n",
    "            'ParameterValue': RekognitionIndexFacesQualityFilter,\n",
    "        },\n",
    "        {\n",
    "            'ParameterKey': 'RekognitionIndexFacesTPSLimit',\n",
    "            'ParameterValue': RekognitionIndexFacesTPSLimit,\n",
    "        },\n",
    "    ],\n",
    "    Capabilities=['CAPABILITY_IAM','CAPABILITY_NAMED_IAM','CAPABILITY_AUTO_EXPAND'],\n",
    "    TimeoutInMinutes=20,\n",
    "    OnFailure='ROLLBACK'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f297add-9cb5-4943-aabc-d0a885eb4690",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def get_status(stackId):\n",
    "    cft_status = cfClient.describe_stacks(\n",
    "        StackName=stackId\n",
    "    )\n",
    "    return cft_status[\"Stacks\"][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a8725af5-7d2d-472f-aa9f-232c7e23d62b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "print(\"Creating Stack...\")\n",
    "while get_status(response_cft[\"StackId\"])[\"StackStatus\"] == \"CREATE_IN_PROGRESS\":\n",
    "    print(\".\", end =\"\")\n",
    "    time.sleep(10)\n",
    "print(\"Stack finished launching with state:\", get_status(response_cft[\"StackId\"])[\"StackStatus\"])\n",
    "sf_arn = get_status(response_cft[\"StackId\"])[\"Outputs\"][0][\"OutputValue\"]\n",
    "print(\"Step Function Workflow ARN:\", sf_arn)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a70fab62-9260-402e-a774-1b5efe322208",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### 3.3 Launch a new Step Functions Workflow to ReIndex the collection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee906b53-76e7-4118-92a8-e97c5df5bee2",
   "metadata": {},
   "outputs": [],
   "source": [
    "execution_response = sfClient.start_execution(\n",
    "    stateMachineArn=sf_arn,\n",
    "    input=json.dumps({\"bucket\": s3_bucket_name,\"key\": \"{}/{}\".format(records_folder,records_filename)})\n",
    ")\n",
    "execution_arn = execution_response[\"executionArn\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "52d9cdca-397f-4c8f-9288-0fbd75f0832c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def get_execution_status(execution_arn):\n",
    "    execution_status = sfClient.describe_execution(\n",
    "        executionArn=execution_arn\n",
    "    )\n",
    "    return execution_status[\"status\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8350d7e5-386d-4eaf-bc83-0d595102e9e9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "print(\"Reindexing face collection...\")\n",
    "while get_execution_status(execution_arn) not in [\"SUCCEEDED\",\"FAILED\"]:\n",
    "    print(\".\", end =\"\")\n",
    "    time.sleep(10)\n",
    "print(\"Execution finished launching with state:\", get_execution_status(execution_arn))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17819c76-765f-4cd2-ad33-514f5f190a8a",
   "metadata": {
    "tags": []
   },
   "source": [
    "## 4. Analyze the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "02eef5da-9818-446b-a9a4-f1d6386ebb63",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def list_collection_faces(collection_id):\n",
    "    response = rekClient.list_faces(\n",
    "        CollectionId=collection_id\n",
    "    )\n",
    "    print(\"Number Faces in {} is : {} \".format(collection_id, len(response[\"Faces\"])))  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aa4829f2-7883-46b0-9e72-c531cae987da",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "list_collection_faces(old_CollectionId)\n",
    "list_collection_faces(new_CollectionId)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c22c0ff-978c-4b3a-b945-fcea210d2169",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Analyze Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "491acb68-78b0-42a8-84da-8c49c7513ada",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "response_scan = dynamoClient.scan(\n",
    "        TableName=get_status(response_cft[\"StackId\"])[\"Outputs\"][1][\"OutputValue\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1db49639-5b3d-4539-9c6e-bc6674cb5093",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "new_faces_found = 0\n",
    "for face in response_scan[\"Items\"]:\n",
    "    if (face[\"IsNewFace\"][\"S\"]) == True:\n",
    "        new_faces_found = new_faces_found +1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c0aa263f-9532-4547-8b60-8b5da859bb3d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "print(\"Total faces reindexed:\",response_scan[\"Count\"])\n",
    "print(\"New faces found:\",new_faces_found)"
   ]
  }
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