initial commit of new version

2026-10-04 18:24:18 -04:00
parent 994fac96e0
commit 57220375a3
43 changed files with 3429 additions and 1 deletions
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+"""
+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)