La fonctionnalité de détection des visages détecte les visages dans une image, ainsi que leurs caractéristiques principales, telles que l'état émotionnel ou les accessoires portés (wearing headwear
).
Elle ne permet pas la reconnaissance faciale des personnes.
Faites l'essai
Si vous débutez sur Google Cloud, créez un compte pour évaluer les performances de l'API Cloud Vision en conditions réelles. Les nouveaux clients bénéficient également de 300 $ de crédits offerts pour exécuter, tester et déployer des charges de travail.
Profiter d'un essai sans frais de l'API Cloud VisionDemandes de détection de visages
Configurer votre projet Google Cloud et votre authentification
Si vous n'avez pas encore créé de projet Google Cloud , faites-le maintenant. Développez cette section pour obtenir la marche à suivre.
- Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
-
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
-
Verify that billing is enabled for your Google Cloud project.
-
Enable the Vision API.
-
Install the Google Cloud CLI.
-
Si vous utilisez un fournisseur d'identité (IdP) externe, vous devez d'abord vous connecter à la gcloud CLI avec votre identité fédérée.
-
Pour initialiser la gcloud CLI, exécutez la commande suivante :
gcloud init
-
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
-
Verify that billing is enabled for your Google Cloud project.
-
Enable the Vision API.
-
Install the Google Cloud CLI.
-
Si vous utilisez un fournisseur d'identité (IdP) externe, vous devez d'abord vous connecter à la gcloud CLI avec votre identité fédérée.
-
Pour initialiser la gcloud CLI, exécutez la commande suivante :
gcloud init
- BASE64_ENCODED_IMAGE : représentation en base64 (chaîne ASCII) de vos données d'image binaires. Cette chaîne doit ressembler à la chaîne suivante :
/9j/4QAYRXhpZgAA...9tAVx/zDQDlGxn//2Q==
- RESULTS_INT : (facultatif) valeur entière des résultats à renvoyer. Si vous omettez le champ
"maxResults"
et sa valeur, l'API renvoie la valeur par défaut de 10 résultats. Ce champ ne s'applique pas aux types de fonctionnalités suivants :TEXT_DETECTION
,DOCUMENT_TEXT_DETECTION
ouCROP_HINTS
. - PROJECT_ID : ID de votre projet Google Cloud .
- CLOUD_STORAGE_IMAGE_URI : chemin d'accès à un fichier image valide dans un bucket Cloud Storage. Il vous faut au minimum disposer de droits de lecture sur le fichier.
Exemple :
gs://cloud-samples-data/vision/face/faces.jpeg
- RESULTS_INT : (facultatif) valeur entière des résultats à renvoyer. Si vous omettez le champ
"maxResults"
et sa valeur, l'API renvoie la valeur par défaut de 10 résultats. Ce champ ne s'applique pas aux types de fonctionnalités suivants :TEXT_DETECTION
,DOCUMENT_TEXT_DETECTION
ouCROP_HINTS
. - PROJECT_ID : ID de votre projet Google Cloud .
Détecter des visages dans une image locale
L'API Vision permet de détecter des caractéristiques dans un fichier image local.
Pour les requêtes REST, envoyez le contenu du fichier image en tant que chaîne encodée en base64 dans le corps de votre requête.
Pour les requêtes gcloud
et les bibliothèques clientes, spécifiez le chemin d'accès à une image locale dans votre requête.
REST
Avant d'utiliser les données de requête ci-dessous, effectuez les remplacements suivants :
Méthode HTTP et URL :
POST https://vision.googleapis.com/v1/images:annotate
Corps JSON de la requête :
{ "requests": [ { "image": { "content": "BASE64_ENCODED_IMAGE" }, "features": [ { "maxResults": RESULTS_INT, "type": "FACE_DETECTION" } ] } ] }
Pour envoyer votre requête, choisissez l'une des options suivantes :
curl
Enregistrez le corps de la requête dans un fichier nommé request.json
, puis exécutez la commande suivante :
curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "x-goog-user-project: PROJECT_ID" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://vision.googleapis.com/v1/images:annotate"
PowerShell
Enregistrez le corps de la requête dans un fichier nommé request.json
, puis exécutez la commande suivante :
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_ID" }
Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://vision.googleapis.com/v1/images:annotate" | Select-Object -Expand Content
Si la requête aboutit, le serveur affiche un code d'état HTTP 200 OK
et la réponse au format JSON.
Une réponse FACE_DETECTION
comprend des cadres de délimitation pour tous les visages détectés, des points de repère identifiés sur les visages (yeux, nez, bouche, etc.), ainsi que des indices de confiance associés aux propriétés d'image et de visage (joie, tristesse, colère, surprise, etc.).
Réponse
{ "responses": [ { "faceAnnotations": [ { "boundingPoly": { "vertices": [ { "x": 1077, "y": 157 }, { "x": 2146, "y": 157 }, { "x": 2146, "y": 1399 }, { "x": 1077, "y": 1399 } ] }, "fdBoundingPoly": { "vertices": [ { "x": 1112, "y": 407 }, { "x": 1946, "y": 407 }, { "x": 1946, "y": 1270 }, { "x": 1112, "y": 1270 } ] }, "landmarks": [ { "type": "LEFT_EYE", "position": { "x": 1368.748, "y": 739.0957, "z": 0.0024604797 } }, { "type": "RIGHT_EYE", "position": { "x": 1660.6105, "y": 751.5844, "z": -117.06496 } }, { "type": "LEFT_OF_LEFT_EYEBROW", "position": { "x": 1284.3208, "y": 666.61487, "z": 63.41506 } }, { "type": "RIGHT_OF_LEFT_EYEBROW", "position": { "x": 1418.9249, "y": 671.49414, "z": -83.82396 } }, { "type": "LEFT_OF_RIGHT_EYEBROW", "position": { "x": 1556.9579, "y": 672.2199, "z": -139.39935 } }, { "type": "RIGHT_OF_RIGHT_EYEBROW", "position": { "x": 1771.4799, "y": 682.65845, "z": -131.66716 } }, { "type": "MIDPOINT_BETWEEN_EYES", "position": { "x": 1479.6194, "y": 741.87305, "z": -114.84635 } }, { "type": "NOSE_TIP", "position": { "x": 1443.3151, "y": 917.5109, "z": -194.49301 } }, { "type": "UPPER_LIP", "position": { "x": 1466.7897, "y": 1025.3483, "z": -130.1202 } }, { "type": "LOWER_LIP", "position": { "x": 1467.2588, "y": 1147.0403, "z": -109.24505 } }, { "type": "MOUTH_LEFT", "position": { "x": 1376.8649, "y": 1066.0856, "z": -6.8136826 } }, { "type": "MOUTH_RIGHT", "position": { "x": 1652, "y": 1079.3108, "z": -106.93649 } }, { "type": "MOUTH_CENTER", "position": { "x": 1485.5554, "y": 1087.2388, "z": -110.68126 } }, { "type": "NOSE_BOTTOM_RIGHT", "position": { "x": 1571.9475, "y": 944.9213, "z": -124.11806 } }, { "type": "NOSE_BOTTOM_LEFT", "position": { "x": 1395.2339, "y": 938.12787, "z": -58.072197 } }, { "type": "NOSE_BOTTOM_CENTER", "position": { "x": 1468.4205, "y": 968.8732, "z": -132.09975 } }, { "type": "LEFT_EYE_TOP_BOUNDARY", "position": { "x": 1357.8658, "y": 711.2427, "z": -14.618992 } }, { "type": "LEFT_EYE_RIGHT_CORNER", "position": { "x": 1423.6936, "y": 750.4164, "z": -23.540215 } }, { "type": "LEFT_EYE_BOTTOM_BOUNDARY", "position": { "x": 1360.5627, "y": 762.87415, "z": -1.2607727 } }, { "type": "LEFT_EYE_LEFT_CORNER", "position": { "x": 1313.72, "y": 739.443, "z": 50.216393 } }, { "type": "RIGHT_EYE_TOP_BOUNDARY", "position": { "x": 1661.6622, "y": 718.6839, "z": -134.17404 } }, { "type": "RIGHT_EYE_RIGHT_CORNER", "position": { "x": 1730.0901, "y": 763.57104, "z": -116.365845 } }, { "type": "RIGHT_EYE_BOTTOM_BOUNDARY", "position": { "x": 1660.8823, "y": 777.3474, "z": -120.8635 } }, { "type": "RIGHT_EYE_LEFT_CORNER", "position": { "x": 1590.8903, "y": 753.5044, "z": -91.84842 } }, { "type": "LEFT_EYEBROW_UPPER_MIDPOINT", "position": { "x": 1345.7522, "y": 640.18243, "z": -27.887913 } }, { "type": "RIGHT_EYEBROW_UPPER_MIDPOINT", "position": { "x": 1660.5848, "y": 648.36145, "z": -153.73691 } }, { "type": "LEFT_EAR_TRAGION", "position": { "x": 1274.1006, "y": 826.2645, "z": 422.6642 } }, { "type": "RIGHT_EAR_TRAGION", "position": { "x": 2014.8041, "y": 908.56537, "z": 149.61232 } }, { "type": "FOREHEAD_GLABELLA", "position": { "x": 1476.2395, "y": 669.9625, "z": -120.59111 } }, { "type": "CHIN_GNATHION", "position": { "x": 1477.3256, "y": 1269.3269, "z": -67.748795 } }, { "type": "CHIN_LEFT_GONION", "position": { "x": 1336.8848, "y": 1096.2242, "z": 286.73004 } }, { "type": "CHIN_RIGHT_GONION", "position": { "x": 1863.2197, "y": 1128.6213, "z": 68.90431 } }, { "type": "LEFT_CHEEK_CENTER", "position": { "x": 1317.8549, "y": 940.8025, "z": 50.863163 } }, { "type": "RIGHT_CHEEK_CENTER", "position": { "x": 1733.4912, "y": 964.073, "z": -112.43947 } } ], "rollAngle": 1.5912293, "panAngle": -22.01964, "tiltAngle": -1.4997566, "detectionConfidence": 0.9310801, "landmarkingConfidence": 0.5775582, "joyLikelihood": "VERY_LIKELY", "sorrowLikelihood": "VERY_UNLIKELY", "angerLikelihood": "VERY_UNLIKELY", "surpriseLikelihood": "VERY_UNLIKELY", "underExposedLikelihood": "VERY_UNLIKELY", "blurredLikelihood": "VERY_UNLIKELY", "headwearLikelihood": "POSSIBLE" }, { "boundingPoly": { "vertices": [ { "x": 144, "y": 1273 }, { "x": 793, "y": 1273 }, { "x": 793, "y": 1844 }, { "x": 144, "y": 1844 } ] }, "fdBoundingPoly": { "vertices": [ { "x": 181, "y": 1373 }, { "x": 742, "y": 1373 }, { "x": 742, "y": 1844 }, { "x": 181, "y": 1844 } ] }, "landmarks": [ { "type": "LEFT_EYE", "position": { "x": 356.13745, "y": 1635.7034, "z": 0.0045757294 } }, { "type": "RIGHT_EYE", "position": { "x": 557.07324, "y": 1601.1769, "z": -10.258446 } }, { "type": "LEFT_OF_LEFT_EYEBROW", "position": { "x": 284.70563, "y": 1599.5238, "z": 28.755493 } }, { "type": "RIGHT_OF_LEFT_EYEBROW", "position": { "x": 397.47183, "y": 1574.1455, "z": -28.716581 } }, { "type": "LEFT_OF_RIGHT_EYEBROW", "position": { "x": 484.00983, "y": 1559.5669, "z": -33.509003 } }, { "type": "RIGHT_OF_RIGHT_EYEBROW", "position": { "x": 607.31726, "y": 1551.2396, "z": 11.0225525 } }, { "type": "MIDPOINT_BETWEEN_EYES", "position": { "x": 447.86597, "y": 1603.2458, "z": -40.69277 } }, { "type": "NOSE_TIP", "position": { "x": 463.15356, "y": 1705.7849, "z": -114.36831 } }, { "type": "UPPER_LIP", "position": { "x": 475.02646, "y": 1779.54, "z": -85.219086 } }, { "type": "LOWER_LIP", "position": { "x": 483.2983, "y": 1844.4594, "z": -83.812 } }, { "type": "MOUTH_LEFT", "position": { "x": 391.11206, "y": 1824.9432, "z": -34.578503 } }, { "type": "MOUTH_RIGHT", "position": { "x": 559.85266, "y": 1797.929, "z": -44.700863 } }, { "type": "MOUTH_CENTER", "position": { "x": 478.21106, "y": 1807.5089, "z": -76.46759 } }, { "type": "NOSE_BOTTOM_RIGHT", "position": { "x": 522.9539, "y": 1717.8636, "z": -51.489075 } }, { "type": "NOSE_BOTTOM_LEFT", "position": { "x": 414.95767, "y": 1739.2955, "z": -46.75015 } }, { "type": "NOSE_BOTTOM_CENTER", "position": { "x": 468.7361, "y": 1739.5958, "z": -78.64168 } }, { "type": "LEFT_EYE_TOP_BOUNDARY", "position": { "x": 352.39365, "y": 1618.0576, "z": -7.2005444 } }, { "type": "LEFT_EYE_RIGHT_CORNER", "position": { "x": 395.81454, "y": 1629.9379, "z": -2.4021797 } }, { "type": "LEFT_EYE_BOTTOM_BOUNDARY", "position": { "x": 357.511, "y": 1649.6553, "z": -4.4735374 } }, { "type": "LEFT_EYE_LEFT_CORNER", "position": { "x": 316.1426, "y": 1645.2771, "z": 18.701395 } }, { "type": "RIGHT_EYE_TOP_BOUNDARY", "position": { "x": 553.78973, "y": 1582.3448, "z": -17.07942 } }, { "type": "RIGHT_EYE_RIGHT_CORNER", "position": { "x": 596.6489, "y": 1599.1897, "z": 4.014868 } }, { "type": "RIGHT_EYE_BOTTOM_BOUNDARY", "position": { "x": 558.60706, "y": 1615.964, "z": -15.077105 } }, { "type": "RIGHT_EYE_LEFT_CORNER", "position": { "x": 514.8054, "y": 1605.6407, "z": -7.929638 } }, { "type": "LEFT_EYEBROW_UPPER_MIDPOINT", "position": { "x": 336.4973, "y": 1567.6466, "z": -7.853897 } }, { "type": "RIGHT_EYEBROW_UPPER_MIDPOINT", "position": { "x": 542.3708, "y": 1536.191, "z": -19.405855 } }, { "type": "LEFT_EAR_TRAGION", "position": { "x": 231.38948, "y": 1749.3823, "z": 221.4534 } }, { "type": "RIGHT_EAR_TRAGION", "position": { "x": 712.5644, "y": 1670.4897, "z": 199.4929 } }, { "type": "FOREHEAD_GLABELLA", "position": { "x": 439.35938, "y": 1561.1454, "z": -36.451645 } }, { "type": "CHIN_GNATHION", "position": { "x": 501.61096, "y": 1942.0133, "z": -75.04764 } }, { "type": "CHIN_LEFT_GONION", "position": { "x": 304.9834, "y": 1892.5361, "z": 114.12407 } }, { "type": "CHIN_RIGHT_GONION", "position": { "x": 684.92535, "y": 1824.337, "z": 96.13425 } }, { "type": "LEFT_CHEEK_CENTER", "position": { "x": 334.5645, "y": 1764.659, "z": -2.0755844 } }, { "type": "RIGHT_CHEEK_CENTER", "position": { "x": 609.5919, "y": 1719.6847, "z": -16.861538 } } ], "rollAngle": -8.514851, "panAngle": -3.096844, "tiltAngle": 9.26052, "detectionConfidence": 0.5463216, "landmarkingConfidence": 0.55711126, "joyLikelihood": "VERY_UNLIKELY", "sorrowLikelihood": "VERY_UNLIKELY", "angerLikelihood": "VERY_UNLIKELY", "surpriseLikelihood": "VERY_UNLIKELY", "underExposedLikelihood": "VERY_UNLIKELY", "blurredLikelihood": "UNLIKELY", "headwearLikelihood": "VERY_UNLIKELY" }, { "boundingPoly": { "vertices": [ { "x": 785, "y": 167 }, { "x": 1100, "y": 167 }, { "x": 1100, "y": 534 }, { "x": 785, "y": 534 } ] }, "fdBoundingPoly": { "vertices": [ { "x": 834, "y": 220 }, { "x": 1101, "y": 220 }, { "x": 1101, "y": 506 }, { "x": 834, "y": 506 } ] }, "landmarks": [ { "type": "LEFT_EYE", "position": { "x": 933.74615, "y": 351.82394, "z": -0.00068986416 } }, { "type": "RIGHT_EYE", "position": { "x": 1005.8836, "y": 329.02396, "z": 43.38338 } }, { "type": "LEFT_OF_LEFT_EYEBROW", "position": { "x": 901.93494, "y": 333.3503, "z": -9.714935 } }, { "type": "RIGHT_OF_LEFT_EYEBROW", "position": { "x": 957.4015, "y": 319.9436, "z": -6.8983736 } }, { "type": "LEFT_OF_RIGHT_EYEBROW", "position": { "x": 987.50134, "y": 308.46817, "z": 13.108145 } }, { "type": "RIGHT_OF_RIGHT_EYEBROW", "position": { "x": 1031.5519, "y": 298.8843, "z": 65.60683 } }, { "type": "MIDPOINT_BETWEEN_EYES", "position": { "x": 979.4568, "y": 336.0551, "z": 3.8077774 } }, { "type": "NOSE_TIP", "position": { "x": 1003.45795, "y": 398.80377, "z": -17.351936 } }, { "type": "UPPER_LIP", "position": { "x": 1000.16614, "y": 432.11664, "z": 5.2740355 } }, { "type": "LOWER_LIP", "position": { "x": 1004.0378, "y": 456.92422, "z": 13.545323 } }, { "type": "MOUTH_LEFT", "position": { "x": 961.922, "y": 448.64325, "z": 11.117096 } }, { "type": "MOUTH_RIGHT", "position": { "x": 1025.2979, "y": 432.70157, "z": 47.89795 } }, { "type": "MOUTH_CENTER", "position": { "x": 1002.51434, "y": 443.3482, "z": 13.021965 } }, { "type": "NOSE_BOTTOM_RIGHT", "position": { "x": 1015.5027, "y": 402.8421, "z": 28.03568 } }, { "type": "NOSE_BOTTOM_LEFT", "position": { "x": 969.764, "y": 413.05563, "z": 3.1156778 } }, { "type": "NOSE_BOTTOM_CENTER", "position": { "x": 997.8564, "y": 416.98083, "z": 3.3404813 } }, { "type": "LEFT_EYE_TOP_BOUNDARY", "position": { "x": 930.542, "y": 343.17078, "z": -6.9020395 } }, { "type": "LEFT_EYE_RIGHT_CORNER", "position": { "x": 950.7726, "y": 348.11346, "z": 9.216144 } }, { "type": "LEFT_EYE_BOTTOM_BOUNDARY", "position": { "x": 933.6862, "y": 359.50848, "z": -1.3347243 } }, { "type": "LEFT_EYE_LEFT_CORNER", "position": { "x": 914.83966, "y": 356.1447, "z": -1.4299142 } }, { "type": "RIGHT_EYE_TOP_BOUNDARY", "position": { "x": 1006.59766, "y": 319.50406, "z": 38.31219 } }, { "type": "RIGHT_EYE_RIGHT_CORNER", "position": { "x": 1021.45886, "y": 327.68784, "z": 61.100002 } }, { "type": "RIGHT_EYE_BOTTOM_BOUNDARY", "position": { "x": 1009.46686, "y": 336.0832, "z": 43.87975 } }, { "type": "RIGHT_EYE_LEFT_CORNER", "position": { "x": 991.17535, "y": 331.97632, "z": 34.4881 } }, { "type": "LEFT_EYEBROW_UPPER_MIDPOINT", "position": { "x": 928.40436, "y": 317.13898, "z": -14.411907 } }, { "type": "RIGHT_EYEBROW_UPPER_MIDPOINT", "position": { "x": 1008.5887, "y": 294.364, "z": 32.917953 } }, { "type": "LEFT_EAR_TRAGION", "position": { "x": 835.18915, "y": 395.7093, "z": 81.31065 } }, { "type": "RIGHT_EAR_TRAGION", "position": { "x": 1024.4136, "y": 360.64178, "z": 182.02446 } }, { "type": "FOREHEAD_GLABELLA", "position": { "x": 975.5221, "y": 315.06647, "z": 0.31154716 } }, { "type": "CHIN_GNATHION", "position": { "x": 1010.74097, "y": 503.23572, "z": 29.966637 } }, { "type": "CHIN_LEFT_GONION", "position": { "x": 891.86237, "y": 466.7829, "z": 58.84553 } }, { "type": "CHIN_RIGHT_GONION", "position": { "x": 1031.9008, "y": 428.13455, "z": 145.42484 } }, { "type": "LEFT_CHEEK_CENTER", "position": { "x": 929.4197, "y": 418.09122, "z": 4.574672 } }, { "type": "RIGHT_CHEEK_CENTER", "position": { "x": 1033.7278, "y": 390.5432, "z": 65.6329 } } ], "rollAngle": -12.077273, "panAngle": 27.194477, "tiltAngle": -5.252778, "detectionConfidence": 0.38126788, "landmarkingConfidence": 0.040030442, "joyLikelihood": "VERY_UNLIKELY", "sorrowLikelihood": "VERY_UNLIKELY", "angerLikelihood": "VERY_UNLIKELY", "surpriseLikelihood": "VERY_UNLIKELY", "underExposedLikelihood": "LIKELY", "blurredLikelihood": "VERY_LIKELY", "headwearLikelihood": "VERY_UNLIKELY" } ] } ] }
Go
Avant d'essayer cet exemple, suivez les instructions de configuration pour Go décrites dans le guide de démarrage rapide de Vision à l'aide des bibliothèques clientes. Pour en savoir plus, consultez la documentation de référence de l'API Cloud Vision en langage Go.
Pour vous authentifier auprès de Vision, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez Configurer l'authentification pour un environnement de développement local.
// detectFaces gets faces from the Vision API for an image at the given file path.
func detectFaces(w io.Writer, file string) error {
ctx := context.Background()
client, err := vision.NewImageAnnotatorClient(ctx)
if err != nil {
return err
}
defer client.Close()
f, err := os.Open(file)
if err != nil {
return err
}
defer f.Close()
image, err := vision.NewImageFromReader(f)
if err != nil {
return err
}
annotations, err := client.DetectFaces(ctx, image, nil, 10)
if err != nil {
return err
}
if len(annotations) == 0 {
fmt.Fprintln(w, "No faces found.")
} else {
fmt.Fprintln(w, "Faces:")
for i, annotation := range annotations {
fmt.Fprintln(w, " Face", i)
fmt.Fprintln(w, " Anger:", annotation.AngerLikelihood)
fmt.Fprintln(w, " Joy:", annotation.JoyLikelihood)
fmt.Fprintln(w, " Surprise:", annotation.SurpriseLikelihood)
}
}
return nil
}
Java
Avant d'essayer cet exemple, suivez les instructions de configuration pour Java du guide de démarrage rapide de Vision à l'aide des bibliothèques clientes. Pour en savoir plus, consultez la documentation de référence de l'API Vision pour Java.
import com.google.cloud.vision.v1.AnnotateImageRequest;
import com.google.cloud.vision.v1.AnnotateImageResponse;
import com.google.cloud.vision.v1.BatchAnnotateImagesResponse;
import com.google.cloud.vision.v1.FaceAnnotation;
import com.google.cloud.vision.v1.Feature;
import com.google.cloud.vision.v1.Image;
import com.google.cloud.vision.v1.ImageAnnotatorClient;
import com.google.protobuf.ByteString;
import java.io.FileInputStream;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
public class DetectFaces {
public static void detectFaces() throws IOException {
// TODO(developer): Replace these variables before running the sample.
String filePath = "path/to/your/image/file.jpg";
detectFaces(filePath);
}
// Detects faces in the specified local image.
public static void detectFaces(String filePath) throws IOException {
List<AnnotateImageRequest> requests = new ArrayList<>();
ByteString imgBytes = ByteString.readFrom(new FileInputStream(filePath));
Image img = Image.newBuilder().setContent(imgBytes).build();
Feature feat = Feature.newBuilder().setType(Feature.Type.FACE_DETECTION).build();
AnnotateImageRequest request =
AnnotateImageRequest.newBuilder().addFeatures(feat).setImage(img).build();
requests.add(request);
// Initialize client that will be used to send requests. This client only needs to be created
// once, and can be reused for multiple requests. After completing all of your requests, call
// the "close" method on the client to safely clean up any remaining background resources.
try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
List<AnnotateImageResponse> responses = response.getResponsesList();
for (AnnotateImageResponse res : responses) {
if (res.hasError()) {
System.out.format("Error: %s%n", res.getError().getMessage());
return;
}
// For full list of available annotations, see http://g.co/cloud/vision/docs
for (FaceAnnotation annotation : res.getFaceAnnotationsList()) {
System.out.format(
"anger: %s%njoy: %s%nsurprise: %s%nposition: %s",
annotation.getAngerLikelihood(),
annotation.getJoyLikelihood(),
annotation.getSurpriseLikelihood(),
annotation.getBoundingPoly());
}
}
}
}
}
Node.js
Avant d'essayer cet exemple, suivez les instructions de configuration pour Node.js décrites dans le guide de démarrage rapide de Vision à l'aide des bibliothèques clientes. Pour en savoir plus, consultez la documentation de référence de l'API Cloud Vision en langage Node.js.
Pour vous authentifier auprès de Vision, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez Configurer l'authentification pour un environnement de développement local.
// Imports the Google Cloud client library
const vision = require('@google-cloud/vision');
// Creates a client
const client = new vision.ImageAnnotatorClient();
async function detectFaces() {
/**
* TODO(developer): Uncomment the following line before running the sample.
*/
// const fileName = 'Local image file, e.g. /path/to/image.png';
const [result] = await client.faceDetection(fileName);
const faces = result.faceAnnotations;
console.log('Faces:');
faces.forEach((face, i) => {
console.log(` Face #${i + 1}:`);
console.log(` Joy: ${face.joyLikelihood}`);
console.log(` Anger: ${face.angerLikelihood}`);
console.log(` Sorrow: ${face.sorrowLikelihood}`);
console.log(` Surprise: ${face.surpriseLikelihood}`);
});
}
detectFaces();
Python
Avant d'essayer cet exemple, suivez les instructions de configuration pour Python décrites dans le guide de démarrage rapide de Vision à l'aide des bibliothèques clientes. Pour en savoir plus, consultez la documentation de référence de l'API Cloud Vision en langage Python.
Pour vous authentifier auprès de Vision, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez Configurer l'authentification pour un environnement de développement local.
def detect_faces(path):
"""Detects faces in an image."""
from google.cloud import vision
client = vision.ImageAnnotatorClient()
with open(path, "rb") as image_file:
content = image_file.read()
image = vision.Image(content=content)
response = client.face_detection(image=image)
faces = response.face_annotations
# Names of likelihood from google.cloud.vision.enums
likelihood_name = (
"UNKNOWN",
"VERY_UNLIKELY",
"UNLIKELY",
"POSSIBLE",
"LIKELY",
"VERY_LIKELY",
)
print("Faces:")
for face in faces:
print(f"anger: {likelihood_name[face.anger_likelihood]}")
print(f"joy: {likelihood_name[face.joy_likelihood]}")
print(f"surprise: {likelihood_name[face.surprise_likelihood]}")
vertices = [
f"({vertex.x},{vertex.y})" for vertex in face.bounding_poly.vertices
]
print("face bounds: {}".format(",".join(vertices)))
if response.error.message:
raise Exception(
"{}\nFor more info on error messages, check: "
"https://cloud.google.com/apis/design/errors".format(response.error.message)
)
Langages supplémentaires
C# : Veuillez suivre les Instructions de configuration pour C# sur la page des bibliothèques clientes, puis consultez la Documentation de référence sur Vision pour .NET.
PHP : Veuillez suivre les Instructions de configuration pour PHP sur la page des bibliothèques clientes, puis consultez la Documentation de référence sur Vision pour PHP.
Ruby : Veuillez suivre les Instructions de configuration de Ruby sur la page des bibliothèques clientes, puis consultez la Documentation de référence sur Vision pour Ruby.
Détecter les visages dans une image distante
L'API Vision permet de détecter des caractéristiques dans un fichier image distant situé dans Cloud Storage ou sur le Web. Pour envoyer une requête de fichier distant, spécifiez l'URL Web ou l'URI Cloud Storage du fichier dans le corps de la requête.
REST
Avant d'utiliser les données de requête ci-dessous, effectuez les remplacements suivants :
Méthode HTTP et URL :
POST https://vision.googleapis.com/v1/images:annotate
Corps JSON de la requête :
{ "requests": [ { "image": { "source": { "imageUri": "CLOUD_STORAGE_IMAGE_URI" } }, "features": [ { "maxResults": RESULTS_INT, "type": "FACE_DETECTION" } ] } ] }
Pour envoyer votre requête, choisissez l'une des options suivantes :
curl
Enregistrez le corps de la requête dans un fichier nommé request.json
, puis exécutez la commande suivante :
curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "x-goog-user-project: PROJECT_ID" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://vision.googleapis.com/v1/images:annotate"
PowerShell
Enregistrez le corps de la requête dans un fichier nommé request.json
, puis exécutez la commande suivante :
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_ID" }
Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://vision.googleapis.com/v1/images:annotate" | Select-Object -Expand Content
Si la requête aboutit, le serveur affiche un code d'état HTTP 200 OK
et la réponse au format JSON.
Une réponse FACE_DETECTION
comprend des cadres de délimitation pour tous les visages détectés, des points de repère identifiés sur les visages (yeux, nez, bouche, etc.), ainsi que des indices de confiance associés aux propriétés d'image et de visage (joie, tristesse, colère, surprise, etc.).
Réponse
{ "responses": [ { "faceAnnotations": [ { "boundingPoly": { "vertices": [ { "x": 1077, "y": 157 }, { "x": 2146, "y": 157 }, { "x": 2146, "y": 1399 }, { "x": 1077, "y": 1399 } ] }, "fdBoundingPoly": { "vertices": [ { "x": 1112, "y": 407 }, { "x": 1946, "y": 407 }, { "x": 1946, "y": 1270 }, { "x": 1112, "y": 1270 } ] }, "landmarks": [ { "type": "LEFT_EYE", "position": { "x": 1368.748, "y": 739.0957, "z": 0.0024604797 } }, { "type": "RIGHT_EYE", "position": { "x": 1660.6105, "y": 751.5844, "z": -117.06496 } }, { "type": "LEFT_OF_LEFT_EYEBROW", "position": { "x": 1284.3208, "y": 666.61487, "z": 63.41506 } }, { "type": "RIGHT_OF_LEFT_EYEBROW", "position": { "x": 1418.9249, "y": 671.49414, "z": -83.82396 } }, { "type": "LEFT_OF_RIGHT_EYEBROW", "position": { "x": 1556.9579, "y": 672.2199, "z": -139.39935 } }, { "type": "RIGHT_OF_RIGHT_EYEBROW", "position": { "x": 1771.4799, "y": 682.65845, "z": -131.66716 } }, { "type": "MIDPOINT_BETWEEN_EYES", "position": { "x": 1479.6194, "y": 741.87305, "z": -114.84635 } }, { "type": "NOSE_TIP", "position": { "x": 1443.3151, "y": 917.5109, "z": -194.49301 } }, { "type": "UPPER_LIP", "position": { "x": 1466.7897, "y": 1025.3483, "z": -130.1202 } }, { "type": "LOWER_LIP", "position": { "x": 1467.2588, "y": 1147.0403, "z": -109.24505 } }, { "type": "MOUTH_LEFT", "position": { "x": 1376.8649, "y": 1066.0856, "z": -6.8136826 } }, { "type": "MOUTH_RIGHT", "position": { "x": 1652, "y": 1079.3108, "z": -106.93649 } }, { "type": "MOUTH_CENTER", "position": { "x": 1485.5554, "y": 1087.2388, "z": -110.68126 } }, { "type": "NOSE_BOTTOM_RIGHT", "position": { "x": 1571.9475, "y": 944.9213, "z": -124.11806 } }, { "type": "NOSE_BOTTOM_LEFT", "position": { "x": 1395.2339, "y": 938.12787, "z": -58.072197 } }, { "type": "NOSE_BOTTOM_CENTER", "position": { "x": 1468.4205, "y": 968.8732, "z": -132.09975 } }, { "type": "LEFT_EYE_TOP_BOUNDARY", "position": { "x": 1357.8658, "y": 711.2427, "z": -14.618992 } }, { "type": "LEFT_EYE_RIGHT_CORNER", "position": { "x": 1423.6936, "y": 750.4164, "z": -23.540215 } }, { "type": "LEFT_EYE_BOTTOM_BOUNDARY", "position": { "x": 1360.5627, "y": 762.87415, "z": -1.2607727 } }, { "type": "LEFT_EYE_LEFT_CORNER", "position": { "x": 1313.72, "y": 739.443, "z": 50.216393 } }, { "type": "RIGHT_EYE_TOP_BOUNDARY", "position": { "x": 1661.6622, "y": 718.6839, "z": -134.17404 } }, { "type": "RIGHT_EYE_RIGHT_CORNER", "position": { "x": 1730.0901, "y": 763.57104, "z": -116.365845 } }, { "type": "RIGHT_EYE_BOTTOM_BOUNDARY", "position": { "x": 1660.8823, "y": 777.3474, "z": -120.8635 } }, { "type": "RIGHT_EYE_LEFT_CORNER", "position": { "x": 1590.8903, "y": 753.5044, "z": -91.84842 } }, { "type": "LEFT_EYEBROW_UPPER_MIDPOINT", "position": { "x": 1345.7522, "y": 640.18243, "z": -27.887913 } }, { "type": "RIGHT_EYEBROW_UPPER_MIDPOINT", "position": { "x": 1660.5848, "y": 648.36145, "z": -153.73691 } }, { "type": "LEFT_EAR_TRAGION", "position": { "x": 1274.1006, "y": 826.2645, "z": 422.6642 } }, { "type": "RIGHT_EAR_TRAGION", "position": { "x": 2014.8041, "y": 908.56537, "z": 149.61232 } }, { "type": "FOREHEAD_GLABELLA", "position": { "x": 1476.2395, "y": 669.9625, "z": -120.59111 } }, { "type": "CHIN_GNATHION", "position": { "x": 1477.3256, "y": 1269.3269, "z": -67.748795 } }, { "type": "CHIN_LEFT_GONION", "position": { "x": 1336.8848, "y": 1096.2242, "z": 286.73004 } }, { "type": "CHIN_RIGHT_GONION", "position": { "x": 1863.2197, "y": 1128.6213, "z": 68.90431 } }, { "type": "LEFT_CHEEK_CENTER", "position": { "x": 1317.8549, "y": 940.8025, "z": 50.863163 } }, { "type": "RIGHT_CHEEK_CENTER", "position": { "x": 1733.4912, "y": 964.073, "z": -112.43947 } } ], "rollAngle": 1.5912293, "panAngle": -22.01964, "tiltAngle": -1.4997566, "detectionConfidence": 0.9310801, "landmarkingConfidence": 0.5775582, "joyLikelihood": "VERY_LIKELY", "sorrowLikelihood": "VERY_UNLIKELY", "angerLikelihood": "VERY_UNLIKELY", "surpriseLikelihood": "VERY_UNLIKELY", "underExposedLikelihood": "VERY_UNLIKELY", "blurredLikelihood": "VERY_UNLIKELY", "headwearLikelihood": "POSSIBLE" }, { "boundingPoly": { "vertices": [ { "x": 144, "y": 1273 }, { "x": 793, "y": 1273 }, { "x": 793, "y": 1844 }, { "x": 144, "y": 1844 } ] }, "fdBoundingPoly": { "vertices": [ { "x": 181, "y": 1373 }, { "x": 742, "y": 1373 }, { "x": 742, "y": 1844 }, { "x": 181, "y": 1844 } ] }, "landmarks": [ { "type": "LEFT_EYE", "position": { "x": 356.13745, "y": 1635.7034, "z": 0.0045757294 } }, { "type": "RIGHT_EYE", "position": { "x": 557.07324, "y": 1601.1769, "z": -10.258446 } }, { "type": "LEFT_OF_LEFT_EYEBROW", "position": { "x": 284.70563, "y": 1599.5238, "z": 28.755493 } }, { "type": "RIGHT_OF_LEFT_EYEBROW", "position": { "x": 397.47183, "y": 1574.1455, "z": -28.716581 } }, { "type": "LEFT_OF_RIGHT_EYEBROW", "position": { "x": 484.00983, "y": 1559.5669, "z": -33.509003 } }, { "type": "RIGHT_OF_RIGHT_EYEBROW", "position": { "x": 607.31726, "y": 1551.2396, "z": 11.0225525 } }, { "type": "MIDPOINT_BETWEEN_EYES", "position": { "x": 447.86597, "y": 1603.2458, "z": -40.69277 } }, { "type": "NOSE_TIP", "position": { "x": 463.15356, "y": 1705.7849, "z": -114.36831 } }, { "type": "UPPER_LIP", "position": { "x": 475.02646, "y": 1779.54, "z": -85.219086 } }, { "type": "LOWER_LIP", "position": { "x": 483.2983, "y": 1844.4594, "z": -83.812 } }, { "type": "MOUTH_LEFT", "position": { "x": 391.11206, "y": 1824.9432, "z": -34.578503 } }, { "type": "MOUTH_RIGHT", "position": { "x": 559.85266, "y": 1797.929, "z": -44.700863 } }, { "type": "MOUTH_CENTER", "position": { "x": 478.21106, "y": 1807.5089, "z": -76.46759 } }, { "type": "NOSE_BOTTOM_RIGHT", "position": { "x": 522.9539, "y": 1717.8636, "z": -51.489075 } }, { "type": "NOSE_BOTTOM_LEFT", "position": { "x": 414.95767, "y": 1739.2955, "z": -46.75015 } }, { "type": "NOSE_BOTTOM_CENTER", "position": { "x": 468.7361, "y": 1739.5958, "z": -78.64168 } }, { "type": "LEFT_EYE_TOP_BOUNDARY", "position": { "x": 352.39365, "y": 1618.0576, "z": -7.2005444 } }, { "type": "LEFT_EYE_RIGHT_CORNER", "position": { "x": 395.81454, "y": 1629.9379, "z": -2.4021797 } }, { "type": "LEFT_EYE_BOTTOM_BOUNDARY", "position": { "x": 357.511, "y": 1649.6553, "z": -4.4735374 } }, { "type": "LEFT_EYE_LEFT_CORNER", "position": { "x": 316.1426, "y": 1645.2771, "z": 18.701395 } }, { "type": "RIGHT_EYE_TOP_BOUNDARY", "position": { "x": 553.78973, "y": 1582.3448, "z": -17.07942 } }, { "type": "RIGHT_EYE_RIGHT_CORNER", "position": { "x": 596.6489, "y": 1599.1897, "z": 4.014868 } }, { "type": "RIGHT_EYE_BOTTOM_BOUNDARY", "position": { "x": 558.60706, "y": 1615.964, "z": -15.077105 } }, { "type": "RIGHT_EYE_LEFT_CORNER", "position": { "x": 514.8054, "y": 1605.6407, "z": -7.929638 } }, { "type": "LEFT_EYEBROW_UPPER_MIDPOINT", "position": { "x": 336.4973, "y": 1567.6466, "z": -7.853897 } }, { "type": "RIGHT_EYEBROW_UPPER_MIDPOINT", "position": { "x": 542.3708, "y": 1536.191, "z": -19.405855 } }, { "type": "LEFT_EAR_TRAGION", "position": { "x": 231.38948, "y": 1749.3823, "z": 221.4534 } }, { "type": "RIGHT_EAR_TRAGION", "position": { "x": 712.5644, "y": 1670.4897, "z": 199.4929 } }, { "type": "FOREHEAD_GLABELLA", "position": { "x": 439.35938, "y": 1561.1454, "z": -36.451645 } }, { "type": "CHIN_GNATHION", "position": { "x": 501.61096, "y": 1942.0133, "z": -75.04764 } }, { "type": "CHIN_LEFT_GONION", "position": { "x": 304.9834, "y": 1892.5361, "z": 114.12407 } }, { "type": "CHIN_RIGHT_GONION", "position": { "x": 684.92535, "y": 1824.337, "z": 96.13425 } }, { "type": "LEFT_CHEEK_CENTER", "position": { "x": 334.5645, "y": 1764.659, "z": -2.0755844 } }, { "type": "RIGHT_CHEEK_CENTER", "position": { "x": 609.5919, "y": 1719.6847, "z": -16.861538 } } ], "rollAngle": -8.514851, "panAngle": -3.096844, "tiltAngle": 9.26052, "detectionConfidence": 0.5463216, "landmarkingConfidence": 0.55711126, "joyLikelihood": "VERY_UNLIKELY", "sorrowLikelihood": "VERY_UNLIKELY", "angerLikelihood": "VERY_UNLIKELY", "surpriseLikelihood": "VERY_UNLIKELY", "underExposedLikelihood": "VERY_UNLIKELY", "blurredLikelihood": "UNLIKELY", "headwearLikelihood": "VERY_UNLIKELY" }, { "boundingPoly": { "vertices": [ { "x": 785, "y": 167 }, { "x": 1100, "y": 167 }, { "x": 1100, "y": 534 }, { "x": 785, "y": 534 } ] }, "fdBoundingPoly": { "vertices": [ { "x": 834, "y": 220 }, { "x": 1101, "y": 220 }, { "x": 1101, "y": 506 }, { "x": 834, "y": 506 } ] }, "landmarks": [ { "type": "LEFT_EYE", "position": { "x": 933.74615, "y": 351.82394, "z": -0.00068986416 } }, { "type": "RIGHT_EYE", "position": { "x": 1005.8836, "y": 329.02396, "z": 43.38338 } }, { "type": "LEFT_OF_LEFT_EYEBROW", "position": { "x": 901.93494, "y": 333.3503, "z": -9.714935 } }, { "type": "RIGHT_OF_LEFT_EYEBROW", "position": { "x": 957.4015, "y": 319.9436, "z": -6.8983736 } }, { "type": "LEFT_OF_RIGHT_EYEBROW", "position": { "x": 987.50134, "y": 308.46817, "z": 13.108145 } }, { "type": "RIGHT_OF_RIGHT_EYEBROW", "position": { "x": 1031.5519, "y": 298.8843, "z": 65.60683 } }, { "type": "MIDPOINT_BETWEEN_EYES", "position": { "x": 979.4568, "y": 336.0551, "z": 3.8077774 } }, { "type": "NOSE_TIP", "position": { "x": 1003.45795, "y": 398.80377, "z": -17.351936 } }, { "type": "UPPER_LIP", "position": { "x": 1000.16614, "y": 432.11664, "z": 5.2740355 } }, { "type": "LOWER_LIP", "position": { "x": 1004.0378, "y": 456.92422, "z": 13.545323 } }, { "type": "MOUTH_LEFT", "position": { "x": 961.922, "y": 448.64325, "z": 11.117096 } }, { "type": "MOUTH_RIGHT", "position": { "x": 1025.2979, "y": 432.70157, "z": 47.89795 } }, { "type": "MOUTH_CENTER", "position": { "x": 1002.51434, "y": 443.3482, "z": 13.021965 } }, { "type": "NOSE_BOTTOM_RIGHT", "position": { "x": 1015.5027, "y": 402.8421, "z": 28.03568 } }, { "type": "NOSE_BOTTOM_LEFT", "position": { "x": 969.764, "y": 413.05563, "z": 3.1156778 } }, { "type": "NOSE_BOTTOM_CENTER", "position": { "x": 997.8564, "y": 416.98083, "z": 3.3404813 } }, { "type": "LEFT_EYE_TOP_BOUNDARY", "position": { "x": 930.542, "y": 343.17078, "z": -6.9020395 } }, { "type": "LEFT_EYE_RIGHT_CORNER", "position": { "x": 950.7726, "y": 348.11346, "z": 9.216144 } }, { "type": "LEFT_EYE_BOTTOM_BOUNDARY", "position": { "x": 933.6862, "y": 359.50848, "z": -1.3347243 } }, { "type": "LEFT_EYE_LEFT_CORNER", "position": { "x": 914.83966, "y": 356.1447, "z": -1.4299142 } }, { "type": "RIGHT_EYE_TOP_BOUNDARY", "position": { "x": 1006.59766, "y": 319.50406, "z": 38.31219 } }, { "type": "RIGHT_EYE_RIGHT_CORNER", "position": { "x": 1021.45886, "y": 327.68784, "z": 61.100002 } }, { "type": "RIGHT_EYE_BOTTOM_BOUNDARY", "position": { "x": 1009.46686, "y": 336.0832, "z": 43.87975 } }, { "type": "RIGHT_EYE_LEFT_CORNER", "position": { "x": 991.17535, "y": 331.97632, "z": 34.4881 } }, { "type": "LEFT_EYEBROW_UPPER_MIDPOINT", "position": { "x": 928.40436, "y": 317.13898, "z": -14.411907 } }, { "type": "RIGHT_EYEBROW_UPPER_MIDPOINT", "position": { "x": 1008.5887, "y": 294.364, "z": 32.917953 } }, { "type": "LEFT_EAR_TRAGION", "position": { "x": 835.18915, "y": 395.7093, "z": 81.31065 } }, { "type": "RIGHT_EAR_TRAGION", "position": { "x": 1024.4136, "y": 360.64178, "z": 182.02446 } }, { "type": "FOREHEAD_GLABELLA", "position": { "x": 975.5221, "y": 315.06647, "z": 0.31154716 } }, { "type": "CHIN_GNATHION", "position": { "x": 1010.74097, "y": 503.23572, "z": 29.966637 } }, { "type": "CHIN_LEFT_GONION", "position": { "x": 891.86237, "y": 466.7829, "z": 58.84553 } }, { "type": "CHIN_RIGHT_GONION", "position": { "x": 1031.9008, "y": 428.13455, "z": 145.42484 } }, { "type": "LEFT_CHEEK_CENTER", "position": { "x": 929.4197, "y": 418.09122, "z": 4.574672 } }, { "type": "RIGHT_CHEEK_CENTER", "position": { "x": 1033.7278, "y": 390.5432, "z": 65.6329 } } ], "rollAngle": -12.077273, "panAngle": 27.194477, "tiltAngle": -5.252778, "detectionConfidence": 0.38126788, "landmarkingConfidence": 0.040030442, "joyLikelihood": "VERY_UNLIKELY", "sorrowLikelihood": "VERY_UNLIKELY", "angerLikelihood": "VERY_UNLIKELY", "surpriseLikelihood": "VERY_UNLIKELY", "underExposedLikelihood": "LIKELY", "blurredLikelihood": "VERY_LIKELY", "headwearLikelihood": "VERY_UNLIKELY" } ] } ] }
Go
Avant d'essayer cet exemple, suivez les instructions de configuration pour Go décrites dans le guide de démarrage rapide de Vision à l'aide des bibliothèques clientes. Pour en savoir plus, consultez la documentation de référence de l'API Cloud Vision en langage Go.
Pour vous authentifier auprès de Vision, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez Configurer l'authentification pour un environnement de développement local.
// detectFaces gets faces from the Vision API for an image at the given file path.
func detectFacesURI(w io.Writer, file string) error {
ctx := context.Background()
client, err := vision.NewImageAnnotatorClient(ctx)
if err != nil {
return err
}
image := vision.NewImageFromURI(file)
annotations, err := client.DetectFaces(ctx, image, nil, 10)
if err != nil {
return err
}
if len(annotations) == 0 {
fmt.Fprintln(w, "No faces found.")
} else {
fmt.Fprintln(w, "Faces:")
for i, annotation := range annotations {
fmt.Fprintln(w, " Face", i)
fmt.Fprintln(w, " Anger:", annotation.AngerLikelihood)
fmt.Fprintln(w, " Joy:", annotation.JoyLikelihood)
fmt.Fprintln(w, " Surprise:", annotation.SurpriseLikelihood)
}
}
return nil
}
Java
Avant d'essayer cet exemple, suivez les instructions de configuration pour Java du guide de démarrage rapide de Vision à l'aide des bibliothèques clientes. Pour en savoir plus, consultez la documentation de référence de l'API Vision pour Java.
import com.google.cloud.vision.v1.AnnotateImageRequest;
import com.google.cloud.vision.v1.AnnotateImageResponse;
import com.google.cloud.vision.v1.BatchAnnotateImagesResponse;
import com.google.cloud.vision.v1.FaceAnnotation;
import com.google.cloud.vision.v1.Feature;
import com.google.cloud.vision.v1.Image;
import com.google.cloud.vision.v1.ImageAnnotatorClient;
import com.google.cloud.vision.v1.ImageSource;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
public class DetectFacesGcs {
public static void detectFacesGcs() throws IOException {
// TODO(developer): Replace these variables before running the sample.
String filePath = "gs://your-gcs-bucket/path/to/image/file.jpg";
detectFacesGcs(filePath);
}
// Detects faces in the specified remote image on Google Cloud Storage.
public static void detectFacesGcs(String gcsPath) throws IOException {
List<AnnotateImageRequest> requests = new ArrayList<>();
ImageSource imgSource = ImageSource.newBuilder().setGcsImageUri(gcsPath).build();
Image img = Image.newBuilder().setSource(imgSource).build();
Feature feat = Feature.newBuilder().setType(Feature.Type.FACE_DETECTION).build();
AnnotateImageRequest request =
AnnotateImageRequest.newBuilder().addFeatures(feat).setImage(img).build();
requests.add(request);
// Initialize client that will be used to send requests. This client only needs to be created
// once, and can be reused for multiple requests. After completing all of your requests, call
// the "close" method on the client to safely clean up any remaining background resources.
try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
List<AnnotateImageResponse> responses = response.getResponsesList();
for (AnnotateImageResponse res : responses) {
if (res.hasError()) {
System.out.format("Error: %s%n", res.getError().getMessage());
return;
}
// For full list of available annotations, see http://g.co/cloud/vision/docs
for (FaceAnnotation annotation : res.getFaceAnnotationsList()) {
System.out.format(
"anger: %s%njoy: %s%nsurprise: %s%nposition: %s",
annotation.getAngerLikelihood(),
annotation.getJoyLikelihood(),
annotation.getSurpriseLikelihood(),
annotation.getBoundingPoly());
}
}
}
}
}
Node.js
Avant d'essayer cet exemple, suivez les instructions de configuration pour Node.js décrites dans le guide de démarrage rapide de Vision à l'aide des bibliothèques clientes. Pour en savoir plus, consultez la documentation de référence de l'API Cloud Vision en langage Node.js.
Pour vous authentifier auprès de Vision, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez Configurer l'authentification pour un environnement de développement local.
// Imports the Google Cloud client libraries
const vision = require('@google-cloud/vision');
// Creates a client
const client = new vision.ImageAnnotatorClient();
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const bucketName = 'Bucket where the file resides, e.g. my-bucket';
// const fileName = 'Path to file within bucket, e.g. path/to/image.png';
// Performs face detection on the gcs file
const [result] = await client.faceDetection(`gs://${bucketName}/${fileName}`);
const faces = result.faceAnnotations;
console.log('Faces:');
faces.forEach((face, i) => {
console.log(` Face #${i + 1}:`);
console.log(` Joy: ${face.joyLikelihood}`);
console.log(` Anger: ${face.angerLikelihood}`);
console.log(` Sorrow: ${face.sorrowLikelihood}`);
console.log(` Surprise: ${face.surpriseLikelihood}`);
});
Python
Avant d'essayer cet exemple, suivez les instructions de configuration pour Python décrites dans le guide de démarrage rapide de Vision à l'aide des bibliothèques clientes. Pour en savoir plus, consultez la documentation de référence de l'API Cloud Vision en langage Python.
Pour vous authentifier auprès de Vision, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez Configurer l'authentification pour un environnement de développement local.
def detect_faces_uri(uri):
"""Detects faces in the file located in Google Cloud Storage or the web."""
from google.cloud import vision
client = vision.ImageAnnotatorClient()
image = vision.Image()
image.source.image_uri = uri
response = client.face_detection(image=image)
faces = response.face_annotations
# Names of likelihood from google.cloud.vision.enums
likelihood_name = (
"UNKNOWN",
"VERY_UNLIKELY",
"UNLIKELY",
"POSSIBLE",
"LIKELY",
"VERY_LIKELY",
)
print("Faces:")
for face in faces:
print(f"anger: {likelihood_name[face.anger_likelihood]}")
print(f"joy: {likelihood_name[face.joy_likelihood]}")
print(f"surprise: {likelihood_name[face.surprise_likelihood]}")
vertices = [
f"({vertex.x},{vertex.y})" for vertex in face.bounding_poly.vertices
]
print("face bounds: {}".format(",".join(vertices)))
if response.error.message:
raise Exception(
"{}\nFor more info on error messages, check: "
"https://cloud.google.com/apis/design/errors".format(response.error.message)
)
gcloud
Pour exécuter la détection de visages, utilisez la commande gcloud ml vision detect-faces
comme indiqué dans l'exemple suivant :
gcloud ml vision detect-faces gs://cloud-samples-data/vision/face/faces.jpeg
Langages supplémentaires
C# : Veuillez suivre les Instructions de configuration pour C# sur la page des bibliothèques clientes, puis consultez la Documentation de référence sur Vision pour .NET.
PHP : Veuillez suivre les Instructions de configuration pour PHP sur la page des bibliothèques clientes, puis consultez la Documentation de référence sur Vision pour PHP.
Ruby : Veuillez suivre les Instructions de configuration pour Ruby sur la page des bibliothèques clientes, puis consultez la Documentation de référence sur Vision pour Ruby.
Essayer
Essayez la détection des visages ci-dessous. Vous pouvez utiliser l'image déjà spécifiée gs://cloud-samples-data/vision/face/faces.jpeg
ou spécifier votre propre image à la place. Pour envoyer la requête, cliquez sur Exécuter.
Corps de la requête :
{ "requests": [ { "features": [ { "maxResults": 10, "type": "FACE_DETECTION" } ], "image": { "source": { "imageUri": "gs://cloud-samples-data/vision/face/faces.jpeg" } } } ] }