#13 use webp instead of jpeg/png

This commit is contained in:
2025-01-30 20:37:52 +01:00
parent e80ff12242
commit 297e2b9489
6 changed files with 561 additions and 129 deletions

View File

@@ -26,116 +26,84 @@ def get_dir_name():
def create_debug_directory(dir_name):
"""Erstellt ein eindeutiges Verzeichnis für Debug-Bilder"""
base_dir = 'debug_images'
timestamp = datetime.datetime.now().strftime('%Y%m%d_%H%M%S')
unique_id = str(uuid.uuid4())[:8]
base_dir = 'images'
full_path = os.path.join(base_dir, dir_name)
# Erstelle Hauptverzeichnis falls nicht vorhanden
if not os.path.exists(base_dir):
os.makedirs(base_dir)
# Erstelle spezifisches Verzeichnis für diesen Durchlauf
os.makedirs(full_path)
return full_path
def preprocess_image(image, debug_dir):
"""
Verarbeitet das Bild und speichert Zwischenergebnisse im angegebenen Verzeichnis,
einschließlich einer komprimierten JPG-Version und eines Thumbnails.
"""
"""Bildverarbeitung mit optionalen Optimierungen"""
try:
# Umwandlung in Graustufen
# Graustufenkonvertierung
gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
# Anwendung von CLAHE zur Kontrastverbesserung
clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
# Kontrastverbesserung mit CLAHE
clahe = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8,8)) # Erhöhter Clip-Limit
enhanced = clahe.apply(gray)
# Rauschunterdrückung
denoised = cv2.fastNlMeansDenoising(enhanced)
# Optional: Binärschwellenwert (auskommentiert)
# _, binary = cv2.threshold(denoised, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
# Rauschunterdrückung mit optimierten Parametern
denoised = cv2.fastNlMeansDenoising(
enhanced,
h=15, # Stärkere Rauschreduzierung
templateWindowSize=7,
searchWindowSize=21
)
# Speichern der Zwischenergebnisse im spezifischen Verzeichnis
cv2.imwrite(os.path.join(debug_dir, 'gray.png'), gray)
cv2.imwrite(os.path.join(debug_dir, 'enhanced.png'), enhanced)
cv2.imwrite(os.path.join(debug_dir, 'denoised.png'), denoised)
# cv2.imwrite(os.path.join(debug_dir, 'binary.png'), binary)
# Debug-Bilder speichern
# cv2.imwrite(os.path.join(debug_dir, 'gray.png'), gray)
# cv2.imwrite(os.path.join(debug_dir, 'enhanced.png'), enhanced)
# cv2.imwrite(os.path.join(debug_dir, 'denoised.png'), denoised)
# Speichern der komprimierten JPG-Version des Originalbildes
compressed_jpg_path = os.path.join(debug_dir, 'original_compressed.jpg')
original_bgr = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
cv2.imwrite(compressed_jpg_path, original_bgr, [int(cv2.IMWRITE_JPEG_QUALITY), 80]) # Qualität auf 80 setzen
logger.info(f"Komprimiertes Original JPG gespeichert: {compressed_jpg_path}")
# Thumbnail als WebP
denoised_rgb = cv2.cvtColor(denoised, cv2.COLOR_GRAY2RGB)
thumbnail = Image.fromarray(denoised_rgb)
thumbnail.thumbnail((256, 256))
thumbnail_path = os.path.join(debug_dir, 'thumbnail.webp')
thumbnail.save(thumbnail_path, 'WEBP', quality=85)
# Erstellen und Speichern des Thumbnails
thumbnail_path = os.path.join(debug_dir, 'thumbnail.jpg')
image_pil = Image.fromarray(denoised)
image_pil.thumbnail((128, 128)) # Thumbnail-Größe auf 128x128 Pixel setzen
image_pil.save(thumbnail_path, 'JPEG')
logger.info(f"Thumbnail gespeichert: {thumbnail_path}")
logger.info(f"Debug images saved in: {debug_dir}")
return denoised
except Exception as e:
logger.error(f"Preprocessing error: {str(e)}")
raise
@app.route('/api/ocr', methods=['POST'])
def ocr_endpoint():
debug_dir = None
try:
# Erstelle eindeutiges Debug-Verzeichnis für diesen Request
# Verzeichnis erstellen
dir_name = get_dir_name()
debug_dir = create_debug_directory(dir_name)
logger.info(f"Created debug directory: {debug_dir}")
if not request.is_json:
return jsonify({'error': 'Content-Type must be application/json'}), 400
data = request.get_json()
if not data or 'image' not in data:
return jsonify({'error': 'No image provided'}), 400
image_b64 = data['image']
# Base64 Dekodierung
try:
image_data = base64.b64decode(image_b64)
except Exception as decode_err:
logger.error(f"Base64 decode error: {str(decode_err)}")
return jsonify({'error': 'Base64 decode error'}), 400
# Bildverarbeitung
try:
image = Image.open(BytesIO(image_data)).convert('RGB')
image = np.array(image)
logger.info(f"Image loaded successfully. Shape: {image.shape}")
# Originalbild speichern
cv2.imwrite(os.path.join(debug_dir, 'original.png'),
cv2.cvtColor(image, cv2.COLOR_RGB2BGR))
except Exception as img_err:
logger.error(f"Image processing error: {str(img_err)}")
return jsonify({'error': 'Invalid image data'}), 400
data = request.get_json()
image_data = base64.b64decode(data['image'])
# Originalbild als WebP speichern
original_image = Image.open(BytesIO(image_data)).convert('RGB')
webp_path = os.path.join(debug_dir, 'original.webp')
original_image.save(webp_path, 'WEBP', quality=50)
# Bildvorverarbeitung
processed_image = preprocess_image(image, debug_dir)
logger.info("Preprocessing completed")
# WebP-Bild für Verarbeitung laden
with open(webp_path, 'rb') as f:
webp_image = Image.open(BytesIO(f.read())).convert('RGB')
# Vorverarbeitung
processed_image = preprocess_image(np.array(webp_image), debug_dir)
# PaddleOCR Konfiguration
# OCR mit optimierter Konfiguration
ocr = PaddleOCR(
use_angle_cls=True,
lang='en',
det_db_thresh=0.3,
det_db_box_thresh=0.3,
det_db_unclip_ratio=2.0,
rec_char_type='en',
det_limit_side_len=960,
det_limit_type='max',
det_model_dir='en_PP-OCRv3_det',
rec_model_dir='en_PP-OCRv3_rec',
det_limit_side_len=processed_image.shape[0] * 2,
use_dilation=True,
det_db_score_mode='fast',
show_log=True
det_db_score_mode='fast'
)
# OCR durchführen
@@ -206,59 +174,12 @@ def ocr_endpoint():
}), 500
except Exception as e:
logger.error(f"Unexpected error: {str(e)}")
logger.error(traceback.format_exc())
logger.error(f"Fehler: {str(e)}")
return jsonify({
'error': 'Internal server error',
'debug_dir': debug_dir if 'debug_dir' in locals() else None
'error': 'Verarbeitungsfehler',
'details': str(e),
'debug_dir': dir_name if debug_dir else None
}), 500
@app.route('/api/debug_image/<name>/<filename>', methods=['GET'])
def get_debug_image(name, filename):
"""
Gibt das angeforderte Bild unter 'debug_images/[name]/[filename]' direkt zurück.
"""
try:
# Sicherheitsmaßnahme: Nur erlaubte Zeichen im Verzeichnisnamen
if not all(c.isalnum() or c in ('_', '-') for c in name):
logger.warning(f"Ungültiger Verzeichnisname angefordert: {name}")
return jsonify({'error': 'Invalid directory name'}), 400
# Sicherheitsmaßnahme: Nur erlaubte Zeichen im Dateinamen
if not all(c.isalnum() or c in ('_', '-', '.',) for c in filename):
logger.warning(f"Ungültiger Dateiname angefordert: {filename}")
return jsonify({'error': 'Invalid file name'}), 400
# Vollständigen Pfad zum Bild erstellen
image_path = os.path.join('debug_images', name, filename)
# Überprüfen, ob die Datei existiert
if not os.path.isfile(image_path):
logger.warning(f"Bild nicht gefunden: {image_path}")
return jsonify({'error': 'Image not found'}), 404
# Bestimmen des MIME-Typs basierend auf der Dateiendung
mime_type = 'image/png' # Standard-MIME-Typ
if filename.lower().endswith('.jpg') or filename.lower().endswith('.jpeg'):
mime_type = 'image/jpeg'
elif filename.lower().endswith('.gif'):
mime_type = 'image/gif'
elif filename.lower().endswith('.bmp'):
mime_type = 'image/bmp'
elif filename.lower().endswith('.tiff') or filename.lower().endswith('.tif'):
mime_type = 'image/tiff'
return send_file(
image_path,
mimetype=mime_type,
as_attachment=False
)
except Exception as e:
logger.error(f"Fehler beim Abrufen des Bildes '{name}/{filename}': {str(e)}")
logger.error(traceback.format_exc())
return jsonify({'error': 'Failed to retrieve image'}), 500
if __name__ == '__main__':
app.run(host='0.0.0.0', port=5000, debug=False)