Example usage for com.amazonaws.services.rekognition.model DetectFacesResult getFaceDetails

Introduction

In this page you can find the example usage for com.amazonaws.services.rekognition.model DetectFacesResult getFaceDetails.

Prototype

public java.util.List<FaceDetail> getFaceDetails() 

Source Link

Document

Details of each face found in the image.

Usage

From source file:com.razorfish.fluent.contentintelligence.core.servlets.SmartCropServlet.java

License:Apache License

@Override
protected final void doGet(final SlingHttpServletRequest request, final SlingHttpServletResponse response)
        throws ServletException, IOException {

    String[] selectors = request.getRequestPathInfo().getSelectors();

    int sizeX = Integer.parseInt(selectors[0]);
    int sizeY = Integer.parseInt(selectors[1]);
    String extension = request.getRequestPathInfo().getExtension();
    String imagePath = request.getRequestPathInfo().getResourcePath().substring(0,
            request.getRequestPathInfo().getResourcePath().indexOf("."));

    log.info("received" + Arrays.toString(selectors) + " : " + extension + " : " + imagePath);

    String type = getImageType(extension);
    if (type == null) {
        response.sendError(404, "Image type not supported");
        return;//from   w ww . java 2  s  . c om
    }
    response.setContentType(type);

    ImageContext context = new ImageContext(request, type);

    Resource resource = context.request.getResourceResolver().getResource(imagePath + "." + extension);
    Asset asset = resource.adaptTo(Asset.class);

    log.info("asset : " + asset.getPath());

    log.info("resource : " + resource.getPath() + "type " + resource.getResourceType());
    Image image = new Image(resource);

    float x1 = 0, y1 = 0, x2 = 1, y2 = 1;

    if (isAsset(resource) || isRendition(resource)) {
        image.setFileReference(image.getPath());
        Rendition r = null;
        if (isAsset(resource)) {
            r = DamUtil.resolveToAsset(resource).getOriginal();
        } else {
            r = resource.adaptTo(Rendition.class);
        }
        byte[] data = new byte[(int) r.getSize()];

        int numbytesread = r.getStream().read(data);
        log.debug("Read : {} of {}", numbytesread, r.getSize());
        DetectFacesRequest dfrequest = new DetectFacesRequest()
                .withImage(
                        new com.amazonaws.services.rekognition.model.Image().withBytes(ByteBuffer.wrap(data)))
                .withAttributes(Attribute.ALL);

        AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(
                new ProfileCredentialsProvider().getCredentials());
        rekognitionClient.setSignerRegionOverride("us-east-1");

        DetectFacesResult result = rekognitionClient.detectFaces(dfrequest);

        List<FaceDetail> faceDetails = result.getFaceDetails();
        if (!faceDetails.isEmpty()) {
            log.info("result " + Arrays.toString(faceDetails.toArray()));
            x1 = faceDetails.get(0).getBoundingBox().getLeft();
            y1 = faceDetails.get(0).getBoundingBox().getTop();
            x2 = x1 + faceDetails.get(0).getBoundingBox().getWidth();
            y2 = y1 + faceDetails.get(0).getBoundingBox().getHeight();

        }
    }

    if (!image.hasContent()) {
        response.sendError(404);
        return;
    }

    Layer layer;
    try {
        log.info("image : " + image.getMimeType());
        layer = image.getLayer(true, false, true);
        int ratioY = layer.getHeight();
        int ratioX = layer.getWidth();

        if (sizeX > ratioX) {
            sizeX = ratioX;
        }

        if (sizeY > ratioY) {
            sizeY = ratioY;
        }

        log.info("baseline : " + sizeX + "," + sizeY);
        x1 = (int) Math.ceil(x1 * ratioX);
        y1 = (int) Math.ceil(y1 * ratioY);
        x2 = (int) Math.ceil(x2 * ratioX);
        y2 = (int) Math.ceil(y2 * ratioY);

        log.info("detected : " + (int) x1 + "," + (int) y1 + "," + (int) x2 + "," + (int) y2);
        log.info("calculated : " + (int) (x2 - x1) + "," + (int) (y2 - y1));

        // check if the crop target is bigger than bounding box, if so crop at a larger size
        if ((x2 - x1) < sizeX) {
            x1 = x1 - ((sizeX - (x2 - x1)) / 2);
            x2 = x2 + ((sizeX - (x2 - x1)) / 2);
            log.info("x adj : " + (int) x1 + "," + (int) y1 + "," + (int) x2 + "," + (int) y2);
            log.info("x adj : " + (int) (x2 - x1) + "," + (int) (y2 - y1));
        }

        if ((y2 - y1) < sizeY) {
            y1 = y1 - ((sizeY - (y2 - y1)) / 2);
            y2 = y2 + ((sizeY - (y2 - y1)) / 2);

            log.info("y adj : " + (int) x1 + "," + (int) y1 + "," + (int) x2 + "," + (int) y2);
            log.info("y adj : " + (int) (x2 - x1) + "," + (int) (y2 - y1));
        }

        //ensure we are still within the image boundaries   
        if (x1 < 0) {
            x2 = x2 - x1;
            x1 = 0;
        }
        if (y1 < 0) {
            y2 = y2 - y1;
            y1 = 0;
        }
        if (x2 > ratioX) {
            x1 = x1 - (x2 - ratioX);
            x2 = ratioX;
        }
        if (y2 > ratioY) {
            y1 = y1 - (y2 - ratioY);
            y2 = ratioY;
        }

        //TODO - handle negative values for bounding box - http://docs.aws.amazon.com/rekognition/latest/dg/API_BoundingBox.html
        log.info("resolved : " + (int) x1 + "," + (int) y1 + "," + (int) x2 + "," + (int) y2);
        layer.crop(ImageHelper.getCropRect((int) x1 + "," + (int) y1 + "," + (int) x2 + "," + (int) y2,
                image.getPath()));

        //after cropping the face, resize to the target size if needed
        layer.resize(sizeX, sizeY);
        //layer.crop(ImageHelper.getCropRect("225,121,525,421", image.getPath()));

        double quality = image.getMimeType().equals("image/gif") ? 255 : 1.0;
        layer.write(image.getMimeType(), quality, response.getOutputStream());
    } catch (RepositoryException e) {
        log.error("Could not create layer" + e);
        e.printStackTrace();
    }

    response.flushBuffer();
}

---