add py/Rek_lambda.py.

py/Rek_lambda.py

@@ -0,0 +1,144 @@
+
+
+"""
+This is the starter code to detecting the faces/labels
+in our images of Kyle.
+
+It's mostly complete but we didn't know all the specifics
+to the API calls.
+
+If you look at the boto3 documentation you will be able to find
+all the answers!
+"""
+
+import boto3
+import json
+import os
+
+######
+# Getting our environment variables
+# Make sure to set these in your lambda function
+######
+# this is the name of the rekognition collection you've created
+rekognition_collection_id = os.environ['collection']
+# output on the dashboard
+sns_topic_arn = os.environ['sns_arn']
+# this is your "Team ID" you see at the top of the player 
+# dashboard like: 5a0e59338b894b57b48828b315a40afb
+# **IT IS NOT YOUR TEAM NAME**
+team_id = os.environ['team_id']
+
+
+# Rekognition allows you to specify a "tag" with your image.
+# so later when we detect a matching face, we read this tag
+# so we know the name or title of the person we've matched
+external_image_id = 'Kyle'
+
+# our boto3 rekognition client
+rekognition_client=boto3.client('rekognition')
+sns_client=boto3.client('sns')
+
+def facial_recognition(key, bucket):
+    response = rekognition_client.index_faces(
+        CollectionId=rekognition_collection_id,
+        Image={
+            'S3Object': {
+            'Bucket': bucket,
+            'Name': key
+        }
+        }
+    )
+    print "Index Faces response:\n %s" % response
+    # see if Rekognition detected any faces in this image
+    if not response['FaceRecords']:
+        # no faces detected, so we send back a false
+        return False
+
+    # we found faces, so let's see if they match our CEO
+    # iterating through the faces found in the submitted image
+    for face in response['FaceRecords']:
+        face_id = face['Face']['FaceId']
+        print "Face ID: %s" % face_id
+        # send the detected face to Rekognition to see if it matches
+        # anything in our collection
+        response = rekognition_client.search_faces(
+            CollectionId=rekognition_collection_id,
+            FaceId=face_id
+        )
+        print "Searching faces response:\n %s" % response
+        # checking if there were any matches
+        if not response['FaceMatches']:
+            # not our CEO
+            return False
+
+        # we recognized a face, let's see if it matches our CEO
+        for match in response['FaceMatches']:
+            if "ExternalImageId" in match['Face'] and match['Face']["ExternalImageId"] == external_image_id:
+                # we have a picture of our CEO
+                print "We've found our CEO!! Huzzah!"
+                return True
+
+        # At this point, we have other faces in our collection that 
+        # match this face, but it didn't match our CEO
+        print "not kyle :("
+        return False
+
+def get_labels(key, bucket):
+    response = rekognition_client.detect_labels(
+        Image={
+            'S3Object': {
+            'Bucket': bucket,
+            'Name': key
+        }
+        },
+        MinConfidence=50
+    )
+    raw_labels = response['Labels']
+    top_five=[]
+    for x in range(0,5):
+        top_five.append(raw_labels[x]['Name'])
+
+    return top_five
+
+def send_sns(message):
+    """
+    We'll use SNS to send our response back to the master account
+    with our labels
+    """
+    print message
+    response = sns_client.publish(
+        TopicArn=sns_topic_arn,
+        Message=json.dumps(message)
+    )
+
+    return
+
+def lambda_handler(event, context):
+    """
+    Main Lambda handler
+    """
+    print json.dumps(event)
+    # our incoming event is the S3 put event notification
+    s3_message = event
+    # get the object key and bucket name
+    key = s3_message['Records'][0]['s3']['object']['key']
+    bucket = s3_message['Records'][0]['s3']['bucket']['name']
+
+    # first we need to see if our CEO is in this picture
+    proceed = facial_recognition(key, bucket)
+
+    return_message={
+        "key":key,
+        "team_id":team_id
+    }
+
+    # now we move on to detecting what's in the image
+    if proceed:
+        labels = get_labels(key, bucket)
+        return_message['labels']=labels
+        return_message['kyle_present']=True
+    else:
+        # we need to signal back that our CEO wasn't in the picture
+        return_message['kyle_present']=False
+    
+    send_sns(return_message)