处理 Cloud Vision API 响应

在图片中检测到人脸时处理 Cloud Vision API 响应。

深入探索

如需查看包含此代码示例的详细文档，请参阅以下内容：

代码示例

Java

如需了解如何安装和使用 Vision API Product Search 客户端库，请参阅 Vision API Product Search 客户端库。 如需了解详情，请参阅 Vision API Product Search Java API 参考文档。

如需向 Vision API Product Search 进行身份验证，请设置应用默认凭证。如需了解详情，请参阅为本地开发环境设置身份验证。 

/** Reads image {@code inputPath} and writes {@code outputPath} with {@code faces} outlined. */
private static void writeWithFaces(Path inputPath, Path outputPath, List<FaceAnnotation> faces)
    throws IOException {
  BufferedImage img = ImageIO.read(inputPath.toFile());
  annotateWithFaces(img, faces);
  ImageIO.write(img, "jpg", outputPath.toFile());
}

/** Annotates an image {@code img} with a polygon around each face in {@code faces}. */
public static void annotateWithFaces(BufferedImage img, List<FaceAnnotation> faces) {
  for (FaceAnnotation face : faces) {
    annotateWithFace(img, face);
  }
}

/** Annotates an image {@code img} with a polygon defined by {@code face}. */
private static void annotateWithFace(BufferedImage img, FaceAnnotation face) {
  Graphics2D gfx = img.createGraphics();
  Polygon poly = new Polygon();
  for (Vertex vertex : face.getFdBoundingPoly().getVertices()) {
    poly.addPoint(vertex.getX(), vertex.getY());
  }
  gfx.setStroke(new BasicStroke(5));
  gfx.setColor(new Color(0x00ff00));
  gfx.draw(poly);
}

Node.js

如需了解如何安装和使用 Vision API Product Search 客户端库，请参阅 Vision API Product Search 客户端库。 如需了解详情，请参阅 Vision API Product Search Node.js API 参考文档。

如需向 Vision API Product Search 进行身份验证，请设置应用默认凭证。如需了解详情，请参阅为本地开发环境设置身份验证。 

async function highlightFaces(inputFile, faces, outputFile, PImage) {
  // Open the original image
  const stream = fs.createReadStream(inputFile);
  let promise;
  if (inputFile.match(/\.jpg$/)) {
    promise = PImage.decodeJPEGFromStream(stream);
  } else if (inputFile.match(/\.png$/)) {
    promise = PImage.decodePNGFromStream(stream);
  } else {
    throw new Error(`Unknown filename extension ${inputFile}`);
  }
  const img = await promise;
  const context = img.getContext('2d');
  context.drawImage(img, 0, 0, img.width, img.height, 0, 0);

  // Now draw boxes around all the faces
  context.strokeStyle = 'rgba(0,255,0,0.8)';
  context.lineWidth = '5';

  faces.forEach(face => {
    context.beginPath();
    let origX = 0;
    let origY = 0;
    face.boundingPoly.vertices.forEach((bounds, i) => {
      if (i === 0) {
        origX = bounds.x;
        origY = bounds.y;
        context.moveTo(bounds.x, bounds.y);
      } else {
        context.lineTo(bounds.x, bounds.y);
      }
    });
    context.lineTo(origX, origY);
    context.stroke();
  });

  // Write the result to a file
  console.log(`Writing to file ${outputFile}`);
  const writeStream = fs.createWriteStream(outputFile);
  await PImage.encodePNGToStream(img, writeStream);
}

PHP

如需了解如何安装和使用 Vision API Product Search 客户端库，请参阅 Vision API Product Search 客户端库。

如需向 Vision API Product Search 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为本地开发环境设置身份验证。 

# draw box around faces
if ($faces->count() && $outFile) {
    $imageCreateFunc = [
        'png' => 'imagecreatefrompng',
        'gd' => 'imagecreatefromgd',
        'gif' => 'imagecreatefromgif',
        'jpg' => 'imagecreatefromjpeg',
        'jpeg' => 'imagecreatefromjpeg',
    ];
    $imageWriteFunc = [
        'png' => 'imagepng',
        'gd' => 'imagegd',
        'gif' => 'imagegif',
        'jpg' => 'imagejpeg',
        'jpeg' => 'imagejpeg',
    ];

    copy($path, $outFile);
    $ext = strtolower(pathinfo($path, PATHINFO_EXTENSION));
    if (!array_key_exists($ext, $imageCreateFunc)) {
        throw new \Exception('Unsupported image extension');
    }
    $outputImage = call_user_func($imageCreateFunc[$ext], $outFile);

    foreach ($faces as $face) {
        $vertices = $face->getBoundingPoly()->getVertices();
        if ($vertices) {
            $x1 = $vertices[0]->getX();
            $y1 = $vertices[0]->getY();
            $x2 = $vertices[2]->getX();
            $y2 = $vertices[2]->getY();
            imagerectangle($outputImage, $x1, $y1, $x2, $y2, 0x00ff00);
        }
    }

Python

如需了解如何安装和使用 Vision API Product Search 客户端库，请参阅 Vision API Product Search 客户端库。 如需了解详情，请参阅 Vision API Product Search Python API 参考文档。

如需向 Vision API Product Search 进行身份验证，请设置应用默认凭证。如需了解详情，请参阅为本地开发环境设置身份验证。 

def highlight_faces(image, faces, output_filename):
    """Draws a polygon around the faces, then saves to output_filename.

    Args:
      image: a file containing the image with the faces.
      faces: a list of faces found in the file. This should be in the format
          returned by the Vision API.
      output_filename: the name of the image file to be created, where the
          faces have polygons drawn around them.
    """
    im = Image.open(image)
    draw = ImageDraw.Draw(im)
    # Sepecify the font-family and the font-size
    for face in faces:
        box = [(vertex.x, vertex.y) for vertex in face.bounding_poly.vertices]
        draw.line(box + [box[0]], width=5, fill="#00ff00")
        # Place the confidence value/score of the detected faces above the
        # detection box in the output image
        draw.text(
            (
                (face.bounding_poly.vertices)[0].x,
                (face.bounding_poly.vertices)[0].y - 30,
            ),
            str(format(face.detection_confidence, ".3f")) + "%",
            fill="#FF0000",
        )
    im.save(output_filename)

后续步骤

如需搜索和过滤其他 Google Cloud 产品的代码示例，请参阅Google Cloud 示例浏览器。