Add comprehensive test suite for image processing and related services

- Implement tests for database generator to ensure proper session handling.
- Create tests for EXIF extraction and conversion functions.
- Add tests for image-related endpoints, ensuring proper data retrieval and isolation between clients.
- Develop tests for OCR functionality, including language detection and text extraction.
- Introduce tests for the image processing pipeline, covering success and failure scenarios.
- Validate rate limiting functionality and ensure independent counters for different clients.
- Implement scraper tests to verify HTML content fetching and error handling.
- Add unit tests for various services, including storage and filename generation.
- Establish worker entry point for ARQ to handle background image processing tasks.

app/services/ocr_service.py

@@ -0,0 +1,107 @@
+"""
+Service OCR — extraction de texte via Tesseract
+"""
+import logging
+from pathlib import Path
+from PIL import Image as PILImage
+from app.config import settings
+
+logger = logging.getLogger(__name__)
+
+try:
+    import pytesseract
+    _ocr_import_error: Exception | None = None
+except Exception as e:
+    pytesseract = None
+    _ocr_import_error = e
+
+
+def _detect_language(text: str) -> str:
+    """Détection grossière de la langue à partir du texte extrait."""
+    if not text:
+        return "unknown"
+
+    # Mots communs français
+    fr_words = {"le", "la", "les", "de", "du", "des", "un", "une", "et", "en", "est", "que"}
+    # Mots communs anglais
+    en_words = {"the", "is", "are", "and", "or", "of", "to", "in", "a", "an", "for", "with"}
+
+    words = set(text.lower().split())
+    fr_score = len(words & fr_words)
+    en_score = len(words & en_words)
+
+    if fr_score == 0 and en_score == 0:
+        return "unknown"
+    return "fr" if fr_score >= en_score else "en"
+
+
+def extract_text(file_path: str) -> dict:
+    """
+    Extrait le texte d'une image via Tesseract OCR.
+    Retourne un dict avec le texte, la langue et le score de confiance.
+    """
+    result = {
+        "text": None,
+        "language": None,
+        "confidence": None,
+        "has_text": False,
+    }
+
+    if not settings.OCR_ENABLED:
+        return result
+
+    if pytesseract is None:
+        logger.warning("ocr.unavailable", extra={"error": str(_ocr_import_error)})
+        return result
+
+    path = Path(file_path)
+    if not path.exists():
+        return result
+
+    try:
+        # Configuration Tesseract
+        if settings.TESSERACT_CMD:
+            pytesseract.pytesseract.tesseract_cmd = settings.TESSERACT_CMD
+
+        with PILImage.open(path) as img:
+            # Convertit en RGB si nécessaire
+            if img.mode not in ("RGB", "L"):
+                img = img.convert("RGB")
+
+            # Extraction avec données de confiance
+            data = pytesseract.image_to_data(
+                img,
+                lang=settings.OCR_LANGUAGES,
+                output_type=pytesseract.Output.DICT,
+            )
+
+            # Calcul de la confiance moyenne (on ignore les -1)
+            confidences = [
+                int(c) for c in data["conf"]
+                if str(c).strip() not in ("-1", "")
+            ]
+            avg_confidence = (
+                round(sum(confidences) / len(confidences) / 100, 3)
+                if confidences else 0.0
+            )
+
+            # Texte nettoyé
+            raw_text = pytesseract.image_to_string(
+                img,
+                lang=settings.OCR_LANGUAGES,
+            ).strip()
+
+            if raw_text and len(raw_text) > 3:
+                result["text"] = raw_text
+                result["has_text"] = True
+                result["confidence"] = avg_confidence
+                result["language"] = _detect_language(raw_text)
+            else:
+                result["has_text"] = False
+
+    except pytesseract.TesseractNotFoundError:
+        logger.warning("ocr.tesseract_not_found")
+    except Exception as e:
+        logger.error("ocr.extraction_error", extra={"file": file_path, "error": str(e)})
+
+    return result