0705-16:02

debug_ocr/ocr_image_145435.png.txt

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+“
+
+giraudibrg-lsb.com/BRG-LAB/PAGE programmetssai/zE4AAHEVNGOAA
+
+ BAGLAB C9 Béton C9 Fouméseu labo © Masse
+
+FAT :1 Essai au bleu de méthylène (MB) - NF EN 933-9 (02-2022)
+
+£E Victor
+
+Echantilion _n°25-00075 réceptionné le 02/04/2028 par BOLLÉE Victor - prélevé le 02/04/2025 por BOLLEE Victor, n° prélbvement : 2500078
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+Matériau Sable 0/2 C - CARRIERE ADCEG
+
+V HISTORIQUE
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+
+[VU Essai [ve marée ][M For Uo |[v osservanons
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+
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+
+les statistiques
+
+lessai
+
+A
+
+impossible de trouver adresse IP du serveur de zk1.brg-lab.com.

utils/ocr_brut_test/ocr_preprocessor.py

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+# ocr_preprocessor.py
+
+import os
+from PIL import Image, ImageEnhance
+import cv2
+import numpy as np
+import time
+
+# === 🎛️ PROFILS DE TRAITEMENT D'IMAGE OCR ===
+PREPROCESSING_PROFILES = {
+    "default": {
+        "resize_min_dim": 1000,        # 📏 Si largeur/hauteur < 1000px, image agrandie proportionnellement
+        "enhance_contrast": True,      # 🔆 Active l'amélioration du contraste
+        "contrast_factor": 1.2,        # >1 = plus contrasté, typique : 1.2 à 1.8
+        "enhance_sharpness": False,    # 💥 Active la netteté
+        "sharpness_factor": 1.0,       # >1 = plus net, typique : 1.2 à 2.0
+        "apply_denoising": False,      # 🚿 Réduction de bruit
+        "denoise_strength": {
+            "h": 0,                    # 0 à 15 : intensité du lissage luminance
+            "hColor": 0,               # 0 à 15 : lissage chroma
+            "templateWindowSize": 7,   # Taille du patch à comparer (typiquement 7)
+            "searchWindowSize": 21     # Zone autour du patch pour recherche (typiquement 21)
+        },
+        "invert_colors": False,        # ↕️ Inversion si texte clair sur fond sombre
+        "apply_clahe": False,          # 📈 Égalisation du contraste local (utile en cas de zones très sombres/claires)
+        "save_debug_output": True,
+        "debug_output_dir": "debug_ocr_preprocessed"
+    },
+    "aggressive": {
+        "resize_min_dim": 1400,
+        "enhance_contrast": True,
+        "contrast_factor": 1.8,
+        "enhance_sharpness": True,
+        "sharpness_factor": 1.5,
+        "apply_denoising": True,
+        "denoise_strength": {
+            "h": 10,
+            "hColor": 10,
+            "templateWindowSize": 7,
+            "searchWindowSize": 21
+        },
+        "invert_colors": False,
+        "apply_clahe": False,
+        "save_debug_output": True,
+        "debug_output_dir": "debug_ocr_preprocessed"
+    },
+    "document": {
+        "resize_min_dim": 1100,
+        "enhance_contrast": True,
+        "contrast_factor": 1.2,
+        "enhance_sharpness": False,
+        "sharpness_factor": 1.0,
+        "apply_denoising": False,
+        "denoise_strength": {"h": 0, "hColor": 0, "templateWindowSize": 7, "searchWindowSize": 21},
+        "invert_colors": False,
+        "apply_clahe": False,
+        "save_debug_output": True,
+        "debug_output_dir": "debug_ocr_preprocessed"
+    },
+    "clahe_high": {
+        "resize_min_dim": 1200,
+        "enhance_contrast": True,
+        "contrast_factor": 1.4,
+        "enhance_sharpness": True,
+        "sharpness_factor": 1.3,
+        "apply_denoising": True,
+        "denoise_strength": {
+            "h": 7,
+            "hColor": 7,
+            "templateWindowSize": 7,     # Taille du patch local utilisé
+            "searchWindowSize": 21       # Zone de recherche du filtre
+        },
+        "invert_colors": False,
+        "apply_clahe": True,
+        "save_debug_output": True,
+        "debug_output_dir": "debug_ocr_preprocessed"
+    },
+    "invert_light": {
+        "resize_min_dim": 1200,
+        "enhance_contrast": True,
+        "contrast_factor": 1.3,
+        "enhance_sharpness": True,
+        "sharpness_factor": 1.4,
+        "apply_denoising": False,
+        "invert_colors": True,
+        "apply_clahe": False,
+        "save_debug_output": True,
+        "debug_output_dir": "debug_ocr_preprocessed"
+    }
+}
+
+def preprocess_image(image_path: str, **settings) -> Image.Image:
+    img = Image.open(image_path).convert("RGB")
+    base_name = os.path.basename(image_path)
+    
+    # Gestion des dossiers de debug
+    debug_dir = settings.get("debug_output_dir", "debug_ocr_preprocessed")
+    profile_name = settings.get("profile_name", "default")  # Ajout du nom du profil
+    debug_profile_dir = os.path.join(debug_dir, profile_name)
+    os.makedirs(debug_profile_dir, exist_ok=True)
+
+    # Redimensionnement
+    if settings.get("resize_min_dim", 0) > 0:
+        width, height = img.size
+        min_dim = min(width, height)
+        if min_dim < settings["resize_min_dim"]:
+            scale = settings["resize_min_dim"] / min_dim
+            new_size = (int(width * scale), int(height * scale))
+            img = img.resize(new_size, Image.Resampling.BICUBIC)
+
+    # Contraste
+    if settings.get("enhance_contrast", False):
+        enhancer = ImageEnhance.Contrast(img)
+        img = enhancer.enhance(settings.get("contrast_factor", 1.5))
+
+    # Netteté
+    if settings.get("enhance_sharpness", False):
+        enhancer = ImageEnhance.Sharpness(img)
+        img = enhancer.enhance(settings.get("sharpness_factor", 1.5))
+
+    # Convert to OpenCV image
+    img_cv = cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
+
+    # Débruitage
+    if settings.get("apply_denoising", False):
+        strength = settings.get("denoise_strength", {})
+        img_cv = cv2.fastNlMeansDenoisingColored(
+            img_cv,
+            None,
+            h=strength.get("h", 10),
+            hColor=strength.get("hColor", 10),
+            templateWindowSize=strength.get("templateWindowSize", 7),
+            searchWindowSize=strength.get("searchWindowSize", 21)
+        )
+
+    # CLAHE
+    if settings.get("apply_clahe", False):
+        lab = cv2.cvtColor(img_cv, cv2.COLOR_BGR2LAB)
+        l, a, b = cv2.split(lab)
+        clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
+        cl = clahe.apply(l)
+        img_cv = cv2.merge((cl, a, b))
+        img_cv = cv2.cvtColor(img_cv, cv2.COLOR_LAB2BGR)
+
+    # Inversion
+    if settings.get("invert_colors", False):
+        img_cv = cv2.bitwise_not(img_cv)
+
+    # Sauvegarde image prétraitée (debug)
+    if settings.get("save_debug_output", False):
+        debug_path = os.path.join(debug_profile_dir, f"optimized_{base_name}")
+        cv2.imwrite(debug_path, img_cv)
+
+    return Image.fromarray(cv2.cvtColor(img_cv, cv2.COLOR_BGR2RGB))
+
+def preprocess_image_with_profile(image_path: str, profile_name="default") -> Image.Image:
+    settings = PREPROCESSING_PROFILES[profile_name].copy()  # On fait une copie pour ne pas modifier l'original
+    settings["profile_name"] = profile_name  # On ajoute le nom du profil aux paramètres
+    return preprocess_image(image_path, **settings)