I have been very excited by the Cloud Vision API recently put into Beta by Google Cloud Platform. I haven’t had a chance to play with it much, and I wanted to fool around with it from PHP on App Engine (or vanilla PHP for that matter), but there is no documentation for PHP yet.
So here is a little primer on how to do this from PHP on App Engine.
First you have to complete a few prerequisites:
Once you do this you’re ready to start developing. Because I am running PHP on App Engine I want the App Engine SDK for PHP.
I’m going to use the GUI to run this app, but you can use the command line just as easily.
The first thing I need to do is write a php.ini that properly allows use of cURL and has a good limit on uploaded files.
google_app_engine.enable_curl_lite = 1
upload_max_filesize = 5M
Then I set up a page named creds.php to hold my API key for Cloud Storage and my Cloud Storage Bucket name.
<?php
//Create Bucket here
// https://cloud.google.com/storage/docs/getting-started-console#create_a_bucket
$bucket = "YOUR BUCKET HERE";
// Get Service account API hereL
// https://cloud.google.com/vision/docs/getting-started#setting_up_a_service_account
$api_key = "YOUR API KEY HERE ";
?>
Then I create a form page named index.php that creates an App Engine Upload URL for me. (If I wanted to not use App Engine, I could just skip the call to Cloud Storage Tools and post directly to the next file in the example: process.php.)
<?php
include_once("creds.php"); // Get $bucket
use googleappengineapicloud_storageCloudStorageTools;
$options = [ 'gs_bucket_name' => $bucket ];
$upload_url = CloudStorageTools::createUploadUrl('/process.php', $options);
?>
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Cloud Vision API PHP Example</title>
</head>
<body>
<form action="<?php echo $upload_url ?>" method="post" enctype="multipart/form-data">
Your Photo: <input type="file" name="photo" size="25" />
<input type="submit" name="submit" value="Submit" />
</form>
</body>
</html>
Then process.php does the hard work of taking the uploaded file, converting it to base64 and uploading to the Cloud Vision API.
<?php
include_once("creds.php"); // Get $api_key
$cvurl = "https://vision.googleapis.com/v1/images:annotate?key=" . $api_key;
$type = "LANDMARK_DETECTION";
//Did they upload a file...
if($_FILES['photo']['name'])
{
//if no errors...
if(!$_FILES['photo']['error'])
{
$valid_file = true;
//can't be larger than ~4 MB
if($_FILES['photo']['size'] > (4024000))
{
$valid_file = false;
die('Your file's size is too large.');
}
//if the file has passed the test
if($valid_file)
{
//convert it to base64
$fname = $_FILES['photo']['tmp_name'];
$data = file_get_contents($fname);
$base64 = base64_encode($data);
//Create this JSON
$r_json ='{
"requests": [
{
"image": {
"content":"' . $base64. '"
},
"features": [
{
"type": "' .$type. '",
"maxResults": 200
}
]
}
]
}';
$curl = curl_init();
curl_setopt($curl, CURLOPT_URL, $cvurl);
curl_setopt($curl, CURLOPT_RETURNTRANSFER, true);
curl_setopt($curl, CURLOPT_HTTPHEADER,
array("Content-type: application/json"));
curl_setopt($curl, CURLOPT_POST, true);
curl_setopt($curl, CURLOPT_POSTFIELDS, $r_json);
$json_response = curl_exec($curl);
$status = curl_getinfo($curl, CURLINFO_HTTP_CODE);
curl_close($curl);
if ( $status != 200 ) {
die("Error: $cvurl failed status $status" );
}
echo "<pre>";
echo $json_response;
echo "</pre>";
}
}
//if there is an error...
else
{
//set that to be the returned message
echo "Error";
die('Drror: '.$_FILES['photo']['error']);
}
}
?>
Finally I have to create an app.yaml to serve up the two pages.
module: default
version: 1
api_version: 1
runtime: php55
threadsafe: yes
handlers:
# Needed for static image files
- url: /
script: index.php
- url: /process.php
script: process.php
Use GoogleAppEngineLauncher to start your app.
You should get this.
Assuming you upload a picture from the top of the Eiffel Tower looking at the Champs de Mars, you’ll get something like this:
{
"responses": [
{
"landmarkAnnotations": [
{
"mid": "/m/02j81",
"description": "Champ de Mars",
"score": 0.81389683,
"boundingPoly": {
"vertices": [
{
"x": 202,
"y": 410
},
{
"x": 1967,
"y": 410
},
{
"x": 1967,
"y": 1318
},
{
"x": 202,
"y": 1318
}
]
},
"locations": [
{
"latLng": {
"latitude": 48.858249,
"longitude": 2.294694185256958
}
}
]
},
{
"mid": "/m/02j81",
"description": "Paris",
"score": 0.5426321,
"boundingPoly": {
"vertices": [
{
"x": 305,
"y": 412
},
{
"x": 1737,
"y": 412
},
{
"x": 1737,
"y": 895
},
{
"x": 305,
"y": 895
}
]
},
"locations": [
{
"latLng": {
"latitude": 48.858546,
"longitude": 2.3222419999999997
}
}
]
},
{
"mid": "/g/1tc__sx0",
"description": "France Eiffel Hotel",
"score": 0.36458692,
"boundingPoly": {
"vertices": [
{
"x": 732,
"y": 394
},
{
"x": 1260,
"y": 394
},
{
"x": 1260,
"y": 691
},
{
"x": 732,
"y": 691
}
]
},
"locations": [
{
"latLng": {
"latitude": 48.858362,
"longitude": 2.294125
}
}
]
}
]
}
]
}
There you go, bare bones but simple Cloud Vision example in PHP.
If you want to dig deeper into the Cloud Vision API you can
The code for all of this is available on GitHub.
Earlier this week, Google Cloud Platform announced 
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