123 lines
4.5 KiB
Python
123 lines
4.5 KiB
Python
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"""
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Test module for the ColorFeaturesPyramid class.
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This module contains unit tests to verify the functionality of the ColorFeaturesPyramid class,
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including initialization, down-sampling, and tile analysis.
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"""
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import os
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import sys
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import numpy as np
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from avdb.db import DBOps, DBConnection
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from avdb.color_features_pyramid import ColorFeaturesPyramid
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def demo():
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"""
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Main function to demonstrate the usage of the ColorFeaturesPyramid class.
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This function shows how to use the `_down_sample_and_analyze` method to perform
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down-sampling and tile analysis on an image.
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"""
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# Example image path and UUID
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img_path = "img/TESTIMG.jpeg"
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uuid = "TESTIMG"
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# Initialize the ColorFeaturesPyramid with custom parameters
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pyramid = ColorFeaturesPyramid(
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uuid=uuid,
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root_path=".",
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down_sampling=9,
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colorspace='lab'
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)
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print("Starting down-sampling and analysis...")
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# Run the down-sampling and analysis process
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results = list(pyramid._down_sample_and_analyze())
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# Print the results for each level
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for level, (histograms, metadata) in results:
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imgw, imgh, tilesw, tilesh = metadata
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print(f"Level {level}:")
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print(f" Image dimensions: {imgw} x {imgh}")
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print(f" Tiles: {tilesw} x {tilesh}")
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print(f" Histograms shape: {histograms.shape}")
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print()
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print("Down-sampling and analysis completed successfully.")
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def analyze_all_images(limit=10, dryrun=True):
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"""
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Iterate over all images in the 'img/' folder and analyze them using the ColorFeaturesPyramid class.
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This function processes each image in the 'img/' folder, initializes the ColorFeaturesPyramid,
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and performs down-sampling and tile analysis for each image.
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"""
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with DBConnection('testdb').get_connection() as db_conn:
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db_ops = DBOps(db_conn)
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img_folder = "img"
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if not os.path.exists(img_folder):
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print(f"Error: The folder '{img_folder}' does not exist.")
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return
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# Get all image files in the folder
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image_extensions = ('.jpg', '.jpeg')
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image_files = [
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f"{f}/{f}.jpeg" for f in os.listdir(img_folder)
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]
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if not image_files:
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print(f"No images found in the folder '{img_folder}'.")
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return
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print(f"Found {len(image_files)} images in the folder '{img_folder}'.")
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for img_file in image_files[:limit]:
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img_path = os.path.join(img_folder, img_file)
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uuid = os.path.splitext(img_file.split('/')[1])[0] # Use the filename (without extension) as UUID
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data_file_exists = os.path.exists(img_path.replace(".jpeg", ".lab.pyr_3.jpeg.tiles.mmap"))
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print(img_path.replace(".jpeg", ".lab.pyr_3.jpeg.tiles.mmap"))
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print(data_file_exists)
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# Check if the analysis files exist using level 7 as proxy
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if not data_file_exists:
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# img = cv.imread(img_path)
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# print(f"\nAnalyzing image: {img_path} - {os.path.basename(img_path)} - {len(image_files)} - {img.shape}")
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# if not dryrun:
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# img_name = os.path.basename(img_path)
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# img_id_out = db_ops.insert_image(
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# img_path,
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# img_name,
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# img.shape[0],
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# img.shape[1]
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# )
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# print(f"Inserted image {i+1} {img_id_out}")
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# Initialize the ColorFeaturesPyramid with custom parameters
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pyramid = ColorFeaturesPyramid(
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uuid=uuid,
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root_path=".",
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down_sampling=9,
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colorspace='lab'
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)
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# Run the down-sampling and analysis process
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results = list(pyramid._down_sample_and_analyze())
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# Print the results for each level
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for level, (histograms, metadata) in results:
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imgw, imgh, tilesw, tilesh = metadata
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print(f" Level {level}:")
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print(f" Image dimensions: {imgw} x {imgh}")
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print(f" Tiles: {tilesw} x {tilesh}")
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print(f" Histograms shape: {histograms.shape}\n\n")
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else:
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print(f"\nSkipping analysis file already exists:\n\t{img_file}\n")
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print("\nAnalysis of all images completed successfully.")
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if __name__ == "__main__":
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# demo()
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analyze_all_images(limit=999, dryrun=False)
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