Delete my_model/scratch/extract_objects.py

my_model/scratch/extract_objects.py

@@ -1,45 +0,0 @@
-from object_detection import ObjectDetector
-import os
-
-def detect_objects_for_image(image_name, detector):
-
-    if os.path.exists(image_path):
-        image = detector.process_image(image_path)
-        detected_objects_str, _ = detector.detect_objects(image)
-        return detected_objects_str
-    else:
-        return "Image not found"
-
-def add_detected_objects_to_dataframe(df, image_directory, detector):
-    """
-    Adds a column to the DataFrame with detected objects for each image specified in the 'image_name' column.
-
-    Parameters:
-    df (pd.DataFrame): DataFrame containing a column 'image_name' with image filenames.
-    image_directory (str): Path to the directory containing images.
-    detector (ObjectDetector): An instance of the ObjectDetector class.
-
-    Returns:
-    pd.DataFrame: The original DataFrame with an additional column 'detected_objects'.
-    """
-
-    # Ensure 'image_name' column exists in the DataFrame
-    if 'image_name' not in df.columns:
-        raise ValueError("DataFrame must contain an 'image_name' column.")
-
-    image_path = os.path.join(image_directory, image_name)
-
-    # Function to detect objects for a given image filename
-
-
-    # Apply the function to each row in the DataFrame
-    df['detected_objects'] = df['image_name'].apply(detect_objects_for_image)
-
-    return df
-
-# Example usage (assuming the function will be used in a context where 'detector' is defined and configured):
-# df_images = pd.DataFrame({"image_name": ["image1.jpg", "image2.jpg", ...]})
-# image_directory = "path/to/image_directory"
-# updated_df = add_detected_objects_to_dataframe(df_images, image_directory, detector)
-# updated_df.head()
-