Android中Tess Two（Tesseract）问题：nep.traineddata致崩溃且相机输入无效

Hey there! I get that you're working on a university Android project with Tesseract (tess-two) and hitting two frustrating snags. Let's walk through each problem and fix them together.

Issue 1: App crashes when using Nepali training data (nep.traineddata) #

Here are the most common fixes for this crash:

• Match training data version to tess-two: Tesseract's trained data is version-locked with the library. If you're using an older tess-two dependency, a newer nep.traineddata might not be compatible. Double-check your build.gradle for the tess-two version (e.g., implementation 'com.rmtheis:tess-two:9.1.0' is a stable recent release) and make sure your Nepali training data is built for that exact Tesseract version.
• Verify file placement & integrity: Ensure nep.traineddata is placed in assets/tessdata/ in your project. Sometimes files get corrupted during copying—re-download the official Nepali data, re-add it to your assets, and confirm the file size matches the original download.
• Check language code spelling: When initializing Tesseract, make sure you're using setLanguage("nep") (not "ne" or any misspelling). A wrong language code can trigger crashes or initialization failures.
• Grab the crash LogCat: The LogCat snippet you shared is for English data—we need the crash log when using Nepali data. Look for lines starting with AndroidRuntime: FATAL EXCEPTION—this will tell us exactly why it's crashing (e.g., FileNotFoundException if the file is missing, or a format error if the data is incompatible).

Issue 2: Camera-captured images return empty recognition results #

Empty results usually come down to image preprocessing or access issues. Try these steps:

• Fix image rotation: Most phone cameras save images with a rotation flag (e.g., 90 degrees for vertical shots). Tesseract can't recognize text that's rotated, so you need to read the image's Exif data and rotate it to the correct orientation before passing it to Tesseract.
• Preprocess the image: Camera images are often high-res or have poor lighting. Resize the image to a manageable size (e.g., 1000x1000 pixels), convert it to grayscale, and maybe apply a threshold to improve contrast—this helps Tesseract pick up text better.
• Confirm file access permissions: If your camera saves images to external storage, make sure your app has the READ_EXTERNAL_STORAGE permission (and request it at runtime for Android 6+). Alternatively, use a FileProvider to get a secure Uri for the captured image, avoiding permission issues entirely.
• Run recognition on a background thread: Tesseract processing is slow—if you're running it on the UI thread, it might get interrupted before finishing, leading to empty results. Use an AsyncTask, Kotlin Coroutine, or ExecutorService to handle recognition in the background.

Quick Code Snippets to Help #

Initializing Tesseract with Nepali Data

private TessBaseAPI tessApi;

private void initTesseract() {
    tessApi = new TessBaseAPI();
    String tessDataPath = getFilesDir() + "/tessdata/";
    File tessDir = new File(tessDataPath);
    
    // Create directory if it doesn't exist
    if (!tessDir.exists()) {
        tessDir.mkdirs();
    }

    // Copy trained data from assets to app storage
    try (InputStream in = getAssets().open("tessdata/nep.traineddata");
         OutputStream out = new FileOutputStream(tessDataPath + "nep.traineddata")) {
        
        byte[] buffer = new byte[1024];
        int bytesRead;
        while ((bytesRead = in.read(buffer)) != -1) {
            out.write(buffer, 0, bytesRead);
        }
    } catch (IOException e) {
        Log.e("TesseractInit", "Failed to copy Nepali trained data", e);
        return;
    }

    // Initialize with Nepali language
    int initResult = tessApi.init(tessDataPath, "nep");
    if (initResult != TessBaseAPI.Ok) {
        Log.e("TesseractInit", "Initialization failed with code: " + initResult);
    }
}

Fixing Image Rotation

private Bitmap prepareCameraImage(String imagePath) {
    Bitmap rawBitmap = BitmapFactory.decodeFile(imagePath);
    int rotation = getImageRotation(imagePath);
    return rotateBitmap(rawBitmap, rotation);
}

private int getImageRotation(String imagePath) {
    try {
        ExifInterface exif = new ExifInterface(imagePath);
        int orientation = exif.getAttributeInt(
            ExifInterface.TAG_ORIENTATION,
            ExifInterface.ORIENTATION_NORMAL
        );
        switch (orientation) {
            case ExifInterface.ORIENTATION_ROTATE_90: return 90;
            case ExifInterface.ORIENTATION_ROTATE_180: return 180;
            case ExifInterface.ORIENTATION_ROTATE_270: return 270;
            default: return 0;
        }
    } catch (IOException e) {
        Log.e("ImageRotation", "Failed to read Exif data", e);
        return 0;
    }
}

private Bitmap rotateBitmap(Bitmap bitmap, int degrees) {
    if (degrees == 0) return bitmap;
    Matrix matrix = new Matrix();
    matrix.postRotate(degrees);
    return Bitmap.createBitmap(
        bitmap, 0, 0, bitmap.getWidth(), bitmap.getHeight(), matrix, true
    );
}

If you still run into issues, share the crash LogCat for the Nepali data and your camera image processing code—we can dig deeper from there!

内容的提问来源于stack exchange，提问作者Thanos