If you only want to perform a batch request you can just use batchAnnotateImages
using ImageAnnotatorClient
. Below you can find a sample using it as well as a way to create a request
variable. Also, I include below a asyncBatchAnnotateImages
sample but I recommend the one I mentioned earlier.
Using ImageAnnotatorClient with batchAnnotateImages
<?php
require '../vendor/autoload.php';
use Google\Cloud\Storage\StorageClient;
use Google\Cloud\Vision\V1\Feature;
use Google\Cloud\Vision\V1\Feature_Type;
use Google\Cloud\Vision\V1\ImageAnnotatorClient;
use Google\Cloud\Vision\V1\Image;
use Google\Cloud\Vision\V1\ImageSource;
use Google\Cloud\Vision\V1\AnnotateImageRequest;
use Google\Cloud\Vision\V1\Likelihood;
$client = new ImageAnnotatorClient();
try {
$feature = (new Feature())
->setType(Feature_Type::FACE_DETECTION);
$image = (new Image())
->setContent(file_get_contents("../images/family.jpg","r"));
$request = (new AnnotateImageRequest())
->setImage($image)
->setFeatures([$feature]);
$requests = [$request];
# note: you can add as many requests you want to perform. ie: [$request,$request2,..,..]
$results = $client->batchAnnotateImages($requests);
foreach($results->getResponses() as $result){
foreach ($result->getFaceAnnotations() as $faceAnnotation) {
$likelihood = Likelihood::name($faceAnnotation->getJoyLikelihood());
echo "Likelihood of headwear: $likelihood" . PHP_EOL;
}
}
} finally {
$client->close();
}
Using ImageAnnotatorClient with asyncBatchAnnotateImages
<?php
require '../vendor/autoload.php';
use Google\Cloud\Storage\StorageClient;
use Google\Cloud\Vision\V1\Feature;
use Google\Cloud\Vision\V1\Feature_Type;
use Google\Cloud\Vision\V1\ImageAnnotatorClient;
use Google\Cloud\Vision\V1\Image;
use Google\Cloud\Vision\V1\ImageSource;
use Google\Cloud\Vision\V1\AnnotateImageRequest;
use Google\Cloud\Vision\V1\asyncBatchAnnotateImages;
use Google\Cloud\Vision\V1\OutputConfig;
use Google\Cloud\Vision\V1\GcsDestination;
$client = new ImageAnnotatorClient();
try {
$feature = (new Feature())
->setType(Feature_Type::FACE_DETECTION);
$gcsImageUri = 'gs://<YOUR BUCKET ID>/<YOUR IMAGE FILE>';
$source = new ImageSource();
$source->setImageUri($gcsImageUri);
$image = (new Image())
->setSource($source);
$request = (new AnnotateImageRequest())
->setImage($image)
->setFeatures([$feature]);
$requests = [$request];
$gcsDestination = (new GcsDestination())
->setUri("gs://<YOUR BUCKET>/<OUTPUT FOLDER>/");
$outputConfig = (new OutputConfig())
->setGcsDestination($gcsDestination);
$operationResponse = $client->asyncBatchAnnotateImages($requests, $outputConfig);
$operationResponse->pollUntilComplete();
if ($operationResponse->operationSucceeded()) {
$result = $operationResponse->getResult();
var_dump($result);
#Your Folder output will have your file processing results.
}
} finally {
$client->close();
}
Note: To add on this, you can also check an official implementation of a similar case using vision client on this link but its a sample to detect text on a pdf file.
You can also find additional information on these links: