Annoter un lot de fichiers locaux (bêta)

Annote un lot de fichiers locaux en ligne.

Exemple de code

Java

Avant d'essayer cet exemple, suivez les instructions de configuration pour Java 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 Java.

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.

import com.google.api.core.ApiFuture;
import com.google.cloud.vision.v1p4beta1.AnnotateFileRequest;
import com.google.cloud.vision.v1p4beta1.AnnotateFileResponse;
import com.google.cloud.vision.v1p4beta1.BatchAnnotateFilesRequest;
import com.google.cloud.vision.v1p4beta1.BatchAnnotateFilesResponse;
import com.google.cloud.vision.v1p4beta1.Block;
import com.google.cloud.vision.v1p4beta1.Feature;
import com.google.cloud.vision.v1p4beta1.Feature.Type;
import com.google.cloud.vision.v1p4beta1.ImageAnnotatorClient;
import com.google.cloud.vision.v1p4beta1.InputConfig;
import com.google.cloud.vision.v1p4beta1.Page;
import com.google.cloud.vision.v1p4beta1.Paragraph;
import com.google.cloud.vision.v1p4beta1.Symbol;
import com.google.cloud.vision.v1p4beta1.TextAnnotation;
import com.google.cloud.vision.v1p4beta1.Word;
import com.google.protobuf.ByteString;
import java.io.FileInputStream;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

public class DetectBatchAnnotateFiles {

  // Performs document feature detection on a local PDF/TIFF/GIF file.
  public static void detectBatchAnnotateFiles(String filePath) {
    // String filePath = "path/to/your_file";

    try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
      // Annotate the first two pages and the last one (max 5 pages)
      // First page starts at 1, and not 0. Last page is -1.
      List<Integer> pages = Arrays.asList(1, 2, -1);
      ByteString pdfBytes = ByteString.readFrom(new FileInputStream(filePath));
      Feature feat = Feature.newBuilder().setType(Type.DOCUMENT_TEXT_DETECTION).build();
      // Other supported mime types : 'image/tiff' or 'image/gif'
      InputConfig inputConfig =
          InputConfig.newBuilder().setMimeType("application/pdf").setContent(pdfBytes).build();
      AnnotateFileRequest request =
          AnnotateFileRequest.newBuilder()
              .addFeatures(feat)
              .setInputConfig(inputConfig)
              .addAllPages(pages)
              .build();
      List<AnnotateFileRequest> requests = new ArrayList<>();
      requests.add(request);

      BatchAnnotateFilesRequest batchAnnotateFilesRequest =
          BatchAnnotateFilesRequest.newBuilder().addAllRequests(requests).build();
      ApiFuture<BatchAnnotateFilesResponse> future =
          client.batchAnnotateFilesCallable().futureCall(batchAnnotateFilesRequest);
      BatchAnnotateFilesResponse response = future.get();

      // Getting the first response
      AnnotateFileResponse annotateFileResponse = response.getResponses(0);

      // For full list of available annotations, see http://g.co/cloud/vision/docs
      TextAnnotation textAnnotation = annotateFileResponse.getResponses(0).getFullTextAnnotation();
      for (Page page : textAnnotation.getPagesList()) {
        String pageText = "";
        for (Block block : page.getBlocksList()) {
          String blockText = "";
          for (Paragraph para : block.getParagraphsList()) {
            String paraText = "";
            for (Word word : para.getWordsList()) {
              String wordText = "";
              for (Symbol symbol : word.getSymbolsList()) {
                wordText = wordText + symbol.getText();
                System.out.format(
                    "Symbol text: %s (Confidence: %f)\n", symbol.getText(), symbol.getConfidence());
              }
              System.out.format(
                  "Word text: %s (Confidence: %f)\n\n", wordText, word.getConfidence());
              paraText = String.format("%s %s", paraText, wordText);
            }
            // Output Example using Paragraph:
            System.out.println("\nParagraph: \n" + paraText);
            System.out.format("Paragraph Confidence: %f\n", para.getConfidence());
            blockText = blockText + paraText;
          }
          pageText = pageText + blockText;
        }
      }
      System.out.println("\nComplete annotation:");
      System.out.println(textAnnotation.getText());

    } catch (Exception e) {
      System.out.println("Error during detectPdfText: \n" + e.toString());
    }
  }
}

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_batch_annotate_files(path):
    """Detects document features in a PDF/TIFF/GIF file.

    While your PDF file may have several pages,
    this API can process up to 5 pages only.

    Args:
    path: The path to the local file.
    """
    from google.cloud import vision_v1p4beta1 as vision

    client = vision.ImageAnnotatorClient()

    with open(path, "rb") as pdf_file:
        content = pdf_file.read()

    # Other supported mime_types: image/tiff' or 'image/gif'
    mime_type = "application/pdf"
    input_config = vision.InputConfig(content=content, mime_type=mime_type)

    feature = vision.Feature(type_=vision.Feature.Type.DOCUMENT_TEXT_DETECTION)
    # Annotate the first two pages and the last one (max 5 pages)
    # First page starts at 1, and not 0. Last page is -1.
    pages = [1, 2, -1]

    request = vision.AnnotateFileRequest(
        input_config=input_config, features=[feature], pages=pages
    )

    response = client.batch_annotate_files(requests=[request])

    for image_response in response.responses[0].responses:
        for page in image_response.full_text_annotation.pages:
            for block in page.blocks:
                print(f"\nBlock confidence: {block.confidence}\n")
                for par in block.paragraphs:
                    print(f"\tParagraph confidence: {par.confidence}")
                    for word in par.words:
                        symbol_texts = [symbol.text for symbol in word.symbols]
                        word_text = "".join(symbol_texts)
                        print(
                            "\t\tWord text: {} (confidence: {})".format(
                                word_text, word.confidence
                            )
                        )
                        for symbol in word.symbols:
                            print(
                                "\t\t\tSymbol: {} (confidence: {})".format(
                                    symbol.text, symbol.confidence
                                )
                            )

Étapes suivantes

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