v1.2

Migration from Version 1.1 to 1.2

Version: 1.2

Summary of Changes:

1. Added Precision Configuration:

• Introduced the coord_precision parameter in the __init__ method, allowing configuration of the number of decimal places for geographic coordinates. The default is 9 decimal places.

2. Error Handling:

• Added error handling for opening the TIFF file with a try-except block to raise a ValueError if the file cannot be opened.
• Added error handling for model inference with a try-except block to raise a RuntimeError if the model prediction fails or any other exception occurs during processing.

3. Enhanced Geographic Coordinates Formatting:

• Geographic coordinates are now formatted according to the coord_precision parameter, providing more control over output precision.

4. Improved Output Information:

• Updated the CSV column name from "Probability" to "Confidence Score".
• Updated print statements to use a consistent format for confidence scores and bounding box centers, including improved formatting for bounding box center coordinates.

5. Code Cleanup and Documentation:

• Improved code comments and docstrings for clarity and consistency.
• Added example usage for the new coord_precision parameter in documentation.

Detailed Changes:

• Constructor (__init__ method):

  • Added coord_precision parameter:

    def __init__(self, tif_path, model_path, coord_precision=9):

  • Added error handling for TIFF file opening:

    try:
        with rasterio.open(self.tif_path) as dataset:
            self.image_width = dataset.width
            self.image_height = dataset.height
    except rasterio.errors.RasterioIOError as e:
        raise ValueError(f"Error opening TIFF file {self.tif_path}: {e}")

• Process Image Method:

  • Added error handling for model loading and inference:

    try:
        model = YOLO(self.model_path)
        results = model.predict(self.tif_path)
    except Exception as e:
        raise RuntimeError(f"Error during model inference: {e}")

  • Updated geographic coordinates formatting to use coord_precision:

    formatted_geographic_coords = np.array([
        [f'{lat:.{self.coord_precision}f}', f'{lon:.{self.coord_precision}f}']
        for lat, lon in geographic_coords
    ])

  • Updated CSV column name and print statements:

    "Confidence Score": box.conf[0].item()

  • Added error handling for image processing:

    except Exception as e:
        raise RuntimeError(f"Error processing the image: {e}")