"""
Test module for the ColorFeaturesPyramid class.

This module contains unit tests to verify the functionality of the ColorFeaturesPyramid class,
including initialization, down-sampling, and tile analysis.
"""

import os
import sys
import numpy as np
from avdb.db import DBOps, DBConnection
from avdb.color_features_pyramid import ColorFeaturesPyramid

def demo():
    """
    Main function to demonstrate the usage of the ColorFeaturesPyramid class.

    This function shows how to use the `_down_sample_and_analyze` method to perform
    down-sampling and tile analysis on an image.
    """
    # Example image path and UUID
    img_path = "img/TESTIMG.jpeg"
    uuid = "TESTIMG"

    # Initialize the ColorFeaturesPyramid with custom parameters
    pyramid = ColorFeaturesPyramid(
        uuid=uuid,
        root_path=".",
        down_sampling=9,
        colorspace='lab'
    )

    print("Starting down-sampling and analysis...")

    # Run the down-sampling and analysis process
    results = list(pyramid._down_sample_and_analyze())

    # Print the results for each level
    for level, (histograms, metadata) in results:
        imgw, imgh, tilesw, tilesh = metadata
        print(f"Level {level}:")
        print(f"  Image dimensions: {imgw} x {imgh}")
        print(f"  Tiles: {tilesw} x {tilesh}")
        print(f"  Histograms shape: {histograms.shape}")
        print()

    print("Down-sampling and analysis completed successfully.")

def analyze_all_images(limit=10, dryrun=True):
    """
    Iterate over all images in the 'img/' folder and analyze them using the ColorFeaturesPyramid class.

    This function processes each image in the 'img/' folder, initializes the ColorFeaturesPyramid,
    and performs down-sampling and tile analysis for each image.
    """
    with DBConnection('testdb').get_connection() as db_conn:
        db_ops = DBOps(db_conn)
    
        img_folder = "img"
        if not os.path.exists(img_folder):
            print(f"Error: The folder '{img_folder}' does not exist.")
            return

        # Get all image files in the folder
        image_extensions = ('.jpg', '.jpeg')
        image_files = [
            f"{f}/{f}.jpeg" for f in os.listdir(img_folder)
        ]

        if not image_files:
            print(f"No images found in the folder '{img_folder}'.")
            return

        print(f"Found {len(image_files)} images in the folder '{img_folder}'.")

        for img_file in image_files[:limit]:
            img_path = os.path.join(img_folder, img_file)
            uuid = os.path.splitext(img_file.split('/')[1])[0]  # Use the filename (without extension) as UUID

            data_file_exists = os.path.exists(img_path.replace(".jpeg", ".lab.pyr_3.jpeg.tiles.mmap"))
            print(img_path.replace(".jpeg", ".lab.pyr_3.jpeg.tiles.mmap"))
            print(data_file_exists)
            # Check if the analysis files exist using level 7 as proxy
            if not data_file_exists:
                # img = cv.imread(img_path)
                # print(f"\nAnalyzing image: {img_path} - {os.path.basename(img_path)} - {len(image_files)} - {img.shape}")

                # if not dryrun:
                #     img_name = os.path.basename(img_path)
                #     img_id_out = db_ops.insert_image(
                #         img_path,
                #         img_name,
                #         img.shape[0],
                #         img.shape[1]
                #     )
                #     print(f"Inserted image {i+1} {img_id_out}")

                    # Initialize the ColorFeaturesPyramid with custom parameters
                pyramid = ColorFeaturesPyramid(
                    uuid=uuid,
                    root_path=".",
                    down_sampling=9,
                    colorspace='lab'
                )

                # Run the down-sampling and analysis process
                results = list(pyramid._down_sample_and_analyze())

                # Print the results for each level
                for level, (histograms, metadata) in results:
                    imgw, imgh, tilesw, tilesh = metadata
                    print(f"  Level {level}:")
                    print(f"    Image dimensions: {imgw} x {imgh}")
                    print(f"    Tiles: {tilesw} x {tilesh}")
                    print(f"    Histograms shape: {histograms.shape}\n\n")
            else:
                print(f"\nSkipping analysis file already exists:\n\t{img_file}\n")

        print("\nAnalysis of all images completed successfully.")

if __name__ == "__main__":
    # demo()
    analyze_all_images(limit=999, dryrun=False)