Invoice recognition

.gitignore

@@ -2,6 +2,7 @@
 # Byte-compiled / optimized / DLL files
 __pycache__/
 cli.py
+*/*venv
 *$py.class
 
 # C extensions

README.md

@@ -1,2 +1,8 @@
-# aws
+# AWS image recognition with Textract
 
+
+### To deploy:
+ - clone lambda.py code into your lambda trigger
+ - Add S3 bucket to your Lambda Trigger
+ - Add invoice to your bucket
+ - Enjoy!

invoice/lambda.py

@@ -0,0 +1,45 @@
+import boto3
+from collections import defaultdict
+from urllib.parse import unquote_plus
+import json
+
+def print_labels_and_values(field, keys):
+    if "LabelDetection" in field and "ValueDetection" in field:
+        a, b = str(field.get('LabelDetection')['Text']), str(field.get('ValueDetection')['Text'])
+        for w in keys:
+            if w in a:
+                print(f"{a}:{b}")
+                return w, b
+    return None, None
+
+def process_expense_analysis(response):
+    wanted = {"NIP":"", "Sprzedawca":"", "brutto":""}
+    for expense_doc in response["ExpenseDocuments"]:
+        for summary_field in expense_doc["SummaryFields"]:
+            a,b = print_labels_and_values(summary_field, wanted.keys())
+            if a != None:
+                wanted[a] = b
+            print()
+    return wanted
+
+
+
+def lambda_handler(event, context):
+    file_obj = event["Records"][0]
+    bucket = unquote_plus(str(file_obj["s3"]["bucket"]["name"]))
+    file_name = unquote_plus(str(file_obj["s3"]["object"]["key"]))
+    print(f'Bucket: {bucket}, file: {file_name}')
+    
+    client = boto3.client('textract')
+    response = client.analyze_expense(Document={'S3Object': {'Bucket': bucket, "Name": file_name}})
+    
+    
+    invoice_data = process_expense_analysis(response)
+    invoice_data['name'] = file_name
+    print(json.dumps(invoice_data, indent=4))
+    
+    dynamodb = boto3.resource('dynamodb')
+    
+    table = dynamodb.Table('texttract-s478874')
+    
+    table.put_item(Item=invoice_data)

load-balancer/a.py

@@ -1,143 +0,0 @@
-from cli import aws_access_key_id, aws_secret_access_key, aws_session_token, DEFAULT_VPC
-import boto3, time
-
-
-index = '478874'
-key_name = index + '_key'
-group_name = index + '_group'
-target_name = index + '_target'
-lb_name = index + '_loadbalancer'
-
-
-user_data=r'''
-#!/bin/bash
-sudo yum update -y
-sudo yum install git -y
-git clone https://git.wmi.amu.edu.pl/bikol/DPZC-2022-23.git
-cd 04_Public_cloud/zadania
-sudo yum install docker -y
-sudo service docker start
-sudo usermod -a -G docker ec2-user
-docker build -t webservice .
-docker run -d -p 80:8080 -t webservice
-'''
-
-if __name__ == '__main__':
-    ec2 = boto3.resource(
-        'ec2',
-        region_name='us-east-1',
-        aws_access_key_id=aws_access_key_id,
-        aws_secret_access_key=aws_secret_access_key,
-        aws_session_token=aws_session_token,
-    )
-
-    key_pair = ec2.create_key_pair(
-        KeyName=key_name,
-        KeyType='ed25519',
-        KeyFormat='pem',
-    )
-
-    security_group = ec2.create_security_group(
-        Description=group_name,
-        GroupName=group_name,
-        VpcId=DEFAULT_VPC,
-    )
-
-    inbound_rules = security_group.authorize_ingress(
-        GroupId=security_group.group_id,
-        CidrIp='0.0.0.0/0',
-        IpProtocol='tcp',
-        FromPort=80,
-        ToPort=80,
-    )
-
-    #TODO instancja EC2
-    instance1, instance2 = ec2.create_instances(
-        ImageId='ami-0b5eea76982371e91',
-        MinCount=2,
-        MaxCount=2,
-        InstanceType='t2.micro',
-        KeyName=key_pair.name,
-        UserData=user_data,
-        SecurityGroups=[security_group.group_name],
-    )
-
-    while True:
-        time.sleep(1)
-        instance1 = ec2.Instance(instance1.id)
-        instance2 = ec2.Instance(instance2.id)
-        if instance1.state['Code'] == 16 and instance2.state['Code'] == 16:
-            break
-
-    #TODO target group
-    elbv2 = boto3.client(
-        'elbv2',
-        region_name='us-east-1',
-        aws_access_key_id=aws_access_key_id,
-        aws_secret_access_key=aws_secret_access_key,
-        aws_session_token=aws_session_token,
-    )
-
-    target_group = elbv2.create_target_group(
-        Name=target_name,
-        Protocol='TCP',
-        Port=80,
-        VpcId=DEFAULT_VPC,
-        TargetType='instance',
-        IpAddressType='ipv4',
-    )
-
-    registered_targets = elbv2.register_targets(
-        TargetGroupArn=target_group['TargetGroups'][0]['TargetGroupArn'],
-        Targets=[
-            {
-                'Id': instance1.id,
-                'Port': 80,
-            },
-            {
-                'Id': instance2.id,
-                'Port': 80,
-            },
-        ]
-    )
-
-    #TODO elastic IP
-    ec2_client = boto3.client(
-        'ec2',
-        region_name='us-east-1',
-        aws_access_key_id=aws_access_key_id,
-        aws_secret_access_key=aws_secret_access_key,
-        aws_session_token=aws_session_token,
-    )
-
-    allocation = ec2_client.allocate_address(
-        Domain='vpc'
-    )
-
-    #TODO load balancer
-    load_balancer = elbv2.create_load_balancer(
-        Name=lb_name,
-        SubnetMappings=[
-            {
-                'SubnetId': instance1.subnet_id,
-                'AllocationId': allocation['AllocationId'],
-            },
-        ],
-        Scheme='internet-facing',
-        Type='network',
-        IpAddressType='ipv4',
-    )
-
-    listener = elbv2.create_listener(
-        LoadBalancerArn=load_balancer['LoadBalancers'][0]['LoadBalancerArn'],
-        Protocol='TCP',
-        Port=80,
-        DefaultActions=[
-            {
-                'Type': 'forward',
-                'TargetGroupArn': target_group['TargetGroups'][0]['TargetGroupArn'],
-            },
-        ],
-    )
-
-    print(f'{allocation["PublicIp"]}:80')

load-balancer/deploy.sh

@@ -1,8 +0,0 @@
-#!/bin/bash
-echo "Creating virtual enviroment ..."
-python3 -m venv aws_lb_venv 
-echo "Installing dependencies ..."
-pip install -q boto3, time
-echo "Initiating gitea cloud deploy ..."
-chmod +x a.py
-python3 a.py