# Image Rotation Utils Helper

## Interface Definition

**Interface Name**: `IImageRotationUtils`

### Interface Methods

```python
class IImageRotationUtils(ABC):
    @abstractmethod
    def rotate_image(self, image: np.ndarray, angle: float, center: Optional[Tuple[int, int]] = None) -> np.ndarray:
        pass
    
    @abstractmethod
    def calculate_rotation_from_points(self, src_points: np.ndarray, dst_points: np.ndarray) -> float:
        pass
    
    @abstractmethod
    def normalize_angle(self, angle: float) -> float:
        pass
    
    @abstractmethod
    def compute_rotation_matrix(self, angle: float, center: Tuple[int, int]) -> np.ndarray:
        pass
```

## Component Description

Image rotation operations, angle calculations from point shifts.

## API Methods

### `rotate_image(image: np.ndarray, angle: float, center: Optional[Tuple[int, int]] = None) -> np.ndarray`

**Description**: Rotates image around center.

**Implementation**: Uses cv2.getRotationMatrix2D + cv2.warpAffine

**Parameters**:
- **angle**: Degrees (0-360)
- **center**: Rotation center (default: image center)

**Returns**: Rotated image (same dimensions)

---

### `calculate_rotation_from_points(src_points: np.ndarray, dst_points: np.ndarray) -> float`

**Description**: Calculates rotation angle from point correspondences.

**Input**: (N, 2) arrays of matching points

**Algorithm**:
1. Compute centroids
2. Calculate angle from centroid shifts
3. Return angle in degrees

**Use Case**: Extract precise angle from LiteSAM homography

---

### `normalize_angle(angle: float) -> float`

**Description**: Normalizes angle to 0-360 range.

**Formula**:
```
angle = angle % 360
if angle < 0:
    angle += 360
```

---

### `compute_rotation_matrix(angle: float, center: Tuple[int, int]) -> np.ndarray`

**Description**: Computes 2D rotation matrix.

**Returns**: 2×3 affine transformation matrix

## Dependencies

**External**: opencv-python, numpy

## Test Cases

1. Rotate 90° → image rotated correctly
2. Calculate angle from points → accurate angle
3. Normalize 370° → 10°
4. Rotation matrix → correct transformation