Perl
Perl
Amazon Rekognition - Detect Faces in an Image
See more Amazon Rekognition Examples
Detects faces within an image that is provided as input. This example passes theimage as base64-encoded image bytes.Chilkat Perl Downloads
use chilkat();
$success = 0;
$rest = chilkat::CkRest->new();
$authAws = chilkat::CkAuthAws->new();
$authAws->put_AccessKey("AWS_ACCESS_KEY");
$authAws->put_SecretKey("AWS_SECRET_KEY");
# Don't forget to change the region to your particular region. (Also make the same change in the call to Connect below.)
$authAws->put_Region("us-west-2");
$authAws->put_ServiceName("rekognition");
# SetAuthAws causes Chilkat to automatically add the following headers: Authorization, X-Amz-Date
$rest->SetAuthAws($authAws);
# URL: https://rekognition.us-west-2.amazonaws.com/
$bTls = 1;
$port = 443;
$bAutoReconnect = 1;
# Don't forget to change the region domain (us-west-2.amazonaws.com) to your particular region.
$success = $rest->Connect("rekognition.us-west-2.amazonaws.com",$port,$bTls,$bAutoReconnect);
if ($success != 1) {
print "ConnectFailReason: " . $rest->get_ConnectFailReason() . "\r\n";
print $rest->lastErrorText() . "\r\n";
exit;
}
# Note: The above code does not need to be repeatedly called for each REST request.
# The rest object can be setup once, and then many requests can be sent. Chilkat will automatically
# reconnect within a FullRequest* method as needed. It is only the very first connection that is explicitly
# made via the Connect method.
# Load the JPG to be passed as base64 in the JSON.
$bdJpg = chilkat::CkBinData->new();
$success = $bdJpg->LoadFile("qa_data/jpg/kid_blue_coat.jpg");
if ($success != 1) {
print "Failed to load the input JPG file." . "\r\n";
exit;
}
# We wish to send the following JSON in the body of our HTTP request:
# {
# "Image": {
# "Bytes": "base64_image_bytes"
# }
# "Attributes": [
# "ALL"
# ]
# }
# Here is the image we used for testing:
# 
# Convert binary image bytes to base64.
# Note: We are explicitly keeping the data inside Chilkat to avoid having to pass large strings
# as arguments to function calls. This is important for some programming languages.
$sbJpg = chilkat::CkStringBuilder->new();
$bdJpg->GetEncodedSb("base64",$sbJpg);
$json = chilkat::CkJsonObject->new();
$json->UpdateSb("Image.Bytes",$sbJpg);
$json->UpdateString("Attributes[0]","ALL");
$rest->AddHeader("Content-Type","application/x-amz-json-1.1");
$rest->AddHeader("X-Amz-Target","RekognitionService.DetectFaces");
$sbRequestBody = chilkat::CkStringBuilder->new();
$json->EmitSb($sbRequestBody);
$sbResponseBody = chilkat::CkStringBuilder->new();
$success = $rest->FullRequestSb("POST","/",$sbRequestBody,$sbResponseBody);
if ($success != 1) {
print $rest->lastErrorText() . "\r\n";
exit;
}
$respStatusCode = $rest->get_ResponseStatusCode();
print "response status code = " . $respStatusCode . "\r\n";
if ($respStatusCode >= 400) {
print "Response Status Code = " . $respStatusCode . "\r\n";
print "Response Header:" . "\r\n";
print $rest->responseHeader() . "\r\n";
print "Response Body:" . "\r\n";
print $sbResponseBody->getAsString() . "\r\n";
exit;
}
$jResp = chilkat::CkJsonObject->new();
$jResp->LoadSb($sbResponseBody);
$jResp->put_EmitCompact(0);
print $jResp->emit() . "\r\n";
# Sample JSON response:
# (Sample code for parsing the JSON response is shown below)
# {
# "FaceDetails": [
# {
# "AgeRange": {
# "High": 18,
# "Low": 8
# },
# "Beard": {
# "Confidence": 98.06282806396484,
# "Value": false
# },
# "BoundingBox": {
# "Height": 0.327279269695282,
# "Left": 0.5339247584342957,
# "Top": 0.23660442233085632,
# "Width": 0.35611653327941895
# },
# "Confidence": 99.99732971191406,
# "Emotions": [
# {
# "Confidence": 99.5849380493164,
# "Type": "HAPPY"
# },
# {
# "Confidence": 0.15533843636512756,
# "Type": "CALM"
# },
# {
# "Confidence": 0.08864031732082367,
# "Type": "SURPRISED"
# },
# {
# "Confidence": 0.05476664379239082,
# "Type": "SAD"
# },
# {
# "Confidence": 0.042048510164022446,
# "Type": "CONFUSED"
# },
# {
# "Confidence": 0.038942769169807434,
# "Type": "DISGUSTED"
# },
# {
# "Confidence": 0.021463459357619286,
# "Type": "FEAR"
# },
# {
# "Confidence": 0.013858155347406864,
# "Type": "ANGRY"
# }
# ],
# "Eyeglasses": {
# "Confidence": 98.5116195678711,
# "Value": false
# },
# "EyesOpen": {
# "Confidence": 99.65477752685547,
# "Value": true
# },
# "Gender": {
# "Confidence": 97.1164321899414,
# "Value": "Female"
# },
# "Landmarks": [
# {
# "Type": "eyeLeft",
# "X": 0.6554790735244751,
# "Y": 0.35153862833976746
# },
# {
# "Type": "eyeRight",
# "X": 0.7940073609352112,
# "Y": 0.38292214274406433
# },
# {
# "Type": "mouthLeft",
# "X": 0.6188991069793701,
# "Y": 0.46431097388267517
# },
# {
# "Type": "mouthRight",
# "X": 0.7352844476699829,
# "Y": 0.490242063999176
# },
# {
# "Type": "nose",
# "X": 0.7125006914138794,
# "Y": 0.44607019424438477
# },
# {
# "Type": "leftEyeBrowLeft",
# "X": 0.6096581220626831,
# "Y": 0.3071737587451935
# },
# {
# "Type": "leftEyeBrowRight",
# "X": 0.6628581285476685,
# "Y": 0.3133310079574585
# },
# {
# "Type": "leftEyeBrowUp",
# "X": 0.7027584314346313,
# "Y": 0.33200803399086
# },
# {
# "Type": "rightEyeBrowLeft",
# "X": 0.7813941240310669,
# "Y": 0.35023579001426697
# },
# {
# "Type": "rightEyeBrowRight",
# "X": 0.8213478922843933,
# "Y": 0.34993964433670044
# },
# {
# "Type": "rightEyeBrowUp",
# "X": 0.8495538234710693,
# "Y": 0.36189284920692444
# },
# {
# "Type": "leftEyeLeft",
# "X": 0.629088282585144,
# "Y": 0.34286588430404663
# },
# {
# "Type": "leftEyeRight",
# "X": 0.6820939183235168,
# "Y": 0.3586524724960327
# },
# {
# "Type": "leftEyeUp",
# "X": 0.6580297946929932,
# "Y": 0.3468707501888275
# },
# {
# "Type": "leftEyeDown",
# "X": 0.6537532210350037,
# "Y": 0.35663917660713196
# },
# {
# "Type": "rightEyeLeft",
# "X": 0.7655976414680481,
# "Y": 0.3776427209377289
# },
# {
# "Type": "rightEyeRight",
# "X": 0.8166338801383972,
# "Y": 0.38544225692749023
# },
# {
# "Type": "rightEyeUp",
# "X": 0.7969376444816589,
# "Y": 0.37844377756118774
# },
# {
# "Type": "rightEyeDown",
# "X": 0.7909533977508545,
# "Y": 0.3877102732658386
# },
# {
# "Type": "noseLeft",
# "X": 0.6727234721183777,
# "Y": 0.44030481576919556
# },
# {
# "Type": "noseRight",
# "X": 0.7237889170646667,
# "Y": 0.45200300216674805
# },
# {
# "Type": "mouthUp",
# "X": 0.6882695555686951,
# "Y": 0.4740942418575287
# },
# {
# "Type": "mouthDown",
# "X": 0.6720560789108276,
# "Y": 0.5046101808547974
# },
# {
# "Type": "leftPupil",
# "X": 0.6554790735244751,
# "Y": 0.35153862833976746
# },
# {
# "Type": "rightPupil",
# "X": 0.7940073609352112,
# "Y": 0.38292214274406433
# },
# {
# "Type": "upperJawlineLeft",
# "X": 0.5517005324363708,
# "Y": 0.30355724692344666
# },
# {
# "Type": "midJawlineLeft",
# "X": 0.5320234894752502,
# "Y": 0.43352627754211426
# },
# {
# "Type": "chinBottom",
# "X": 0.6419994831085205,
# "Y": 0.5531964302062988
# },
# {
# "Type": "midJawlineRight",
# "X": 0.7752369046211243,
# "Y": 0.48957017064094543
# },
# {
# "Type": "upperJawlineRight",
# "X": 0.8515444397926331,
# "Y": 0.37258899211883545
# }
# ],
# "MouthOpen": {
# "Confidence": 68.26280212402344,
# "Value": false
# },
# "Mustache": {
# "Confidence": 99.73213195800781,
# "Value": false
# },
# "Pose": {
# "Pitch": -11.299633026123047,
# "Roll": 17.6924991607666,
# "Yaw": 13.582314491271973
# },
# "Quality": {
# "Brightness": 83.72581481933594,
# "Sharpness": 67.22731018066406
# },
# "Smile": {
# "Confidence": 98.4793930053711,
# "Value": true
# },
# "Sunglasses": {
# "Confidence": 99.3582992553711,
# "Value": false
# }
# }
# ]
# }
# Sample code for parsing the JSON response...
# Use the following online tool to generate parsing code from sample JSON:
# Generate Parsing Code from JSON
$i = 0;
$count_i = $jResp->SizeOfArray("FaceDetails");
while ($i < $count_i) {
$jResp->put_I($i);
$AgeRangeHigh = $jResp->IntOf("FaceDetails[i].AgeRange.High");
$AgeRangeLow = $jResp->IntOf("FaceDetails[i].AgeRange.Low");
$BeardConfidence = $jResp->stringOf("FaceDetails[i].Beard.Confidence");
$BeardValue = $jResp->BoolOf("FaceDetails[i].Beard.Value");
$BoundingBoxHeight = $jResp->stringOf("FaceDetails[i].BoundingBox.Height");
$BoundingBoxLeft = $jResp->stringOf("FaceDetails[i].BoundingBox.Left");
$BoundingBoxTop = $jResp->stringOf("FaceDetails[i].BoundingBox.Top");
$BoundingBoxWidth = $jResp->stringOf("FaceDetails[i].BoundingBox.Width");
$Confidence = $jResp->stringOf("FaceDetails[i].Confidence");
$EyeglassesConfidence = $jResp->stringOf("FaceDetails[i].Eyeglasses.Confidence");
$EyeglassesValue = $jResp->BoolOf("FaceDetails[i].Eyeglasses.Value");
$EyesOpenConfidence = $jResp->stringOf("FaceDetails[i].EyesOpen.Confidence");
$EyesOpenValue = $jResp->BoolOf("FaceDetails[i].EyesOpen.Value");
$GenderConfidence = $jResp->stringOf("FaceDetails[i].Gender.Confidence");
$GenderValue = $jResp->stringOf("FaceDetails[i].Gender.Value");
$MouthOpenConfidence = $jResp->stringOf("FaceDetails[i].MouthOpen.Confidence");
$MouthOpenValue = $jResp->BoolOf("FaceDetails[i].MouthOpen.Value");
$MustacheConfidence = $jResp->stringOf("FaceDetails[i].Mustache.Confidence");
$MustacheValue = $jResp->BoolOf("FaceDetails[i].Mustache.Value");
$PosePitch = $jResp->stringOf("FaceDetails[i].Pose.Pitch");
$PoseRoll = $jResp->stringOf("FaceDetails[i].Pose.Roll");
$PoseYaw = $jResp->stringOf("FaceDetails[i].Pose.Yaw");
$QualityBrightness = $jResp->stringOf("FaceDetails[i].Quality.Brightness");
$QualitySharpness = $jResp->stringOf("FaceDetails[i].Quality.Sharpness");
$SmileConfidence = $jResp->stringOf("FaceDetails[i].Smile.Confidence");
$SmileValue = $jResp->BoolOf("FaceDetails[i].Smile.Value");
$SunglassesConfidence = $jResp->stringOf("FaceDetails[i].Sunglasses.Confidence");
$SunglassesValue = $jResp->BoolOf("FaceDetails[i].Sunglasses.Value");
$j = 0;
$count_j = $jResp->SizeOfArray("FaceDetails[i].Emotions");
while ($j < $count_j) {
$jResp->put_J($j);
$Confidence = $jResp->stringOf("FaceDetails[i].Emotions[j].Confidence");
$v_Type = $jResp->stringOf("FaceDetails[i].Emotions[j].Type");
$j = $j + 1;
}
$j = 0;
$count_j = $jResp->SizeOfArray("FaceDetails[i].Landmarks");
while ($j < $count_j) {
$jResp->put_J($j);
$v_Type = $jResp->stringOf("FaceDetails[i].Landmarks[j].Type");
$X = $jResp->stringOf("FaceDetails[i].Landmarks[j].X");
$Y = $jResp->stringOf("FaceDetails[i].Landmarks[j].Y");
$j = $j + 1;
}
$i = $i + 1;
}