feat(phase1): implement OpenCV image processing pipeline

- Create ImageProcessor service with EXIF orientation detection
- Implement smart cropping via OpenCV contour detection (10% padding)
- Add text orientation detection using Hough line transform
- Resize and compress images to 1200px with 85% JPEG quality
- Generate 200px square thumbnails with center crop
- Fallback to Pillow if OpenCV fails
- Comprehensive test suite: 28 tests all passing
- File size validation (reject >10MB)
- Graceful error handling for corrupted/invalid images
- Update requirements.txt with opencv-python, piexif, python-magic

venv/lib/python3.12/site-packages/cv2/utils/nested/__init__.pyi

@@ -0,0 +1,31 @@
+__all__: list[str] = []
+
+# Classes
+class ExportClassName:
+    # Classes
+    class Params:
+        int_value: int
+        float_value: float
+
+        # Functions
+        def __init__(self, int_param: int = ..., float_param: float = ...) -> None: ...
+
+
+
+    # Functions
+    def getIntParam(self) -> int: ...
+
+    def getFloatParam(self) -> float: ...
+
+    @staticmethod
+    def originalName() -> str: ...
+
+    @classmethod
+    def create(cls, params: ExportClassName.Params = ...) -> ExportClassName: ...
+
+
+
+# Functions
+def testEchoBooleanFunction(flag: bool) -> bool: ...
+
+