Making image manipulations thru one class

src/gui/tabs/training_tab.py

@@ -10,7 +10,6 @@ from pathlib import Path
 from typing import Any, Dict, List, Optional, Tuple
 
 import yaml
-from PIL import Image as PILImage
 from PySide6.QtCore import Qt, QThread, Signal
 from PySide6.QtWidgets import (
     QWidget,
@@ -1293,8 +1292,8 @@ class TrainingTab(QWidget):
         if not sample_image:
             return False
         try:
-            with PILImage.open(sample_image) as img:
-                return img.mode.upper() != "RGB"
+            img = Image(sample_image)
+            return img.pil_image.mode.upper() != "RGB"
         except Exception as exc:
             logger.warning(f"Failed to inspect image {sample_image}: {exc}")
             return False
@@ -1354,11 +1353,12 @@ class TrainingTab(QWidget):
             dst = dst_dir / relative
             dst.parent.mkdir(parents=True, exist_ok=True)
             try:
-                with PILImage.open(src) as img:
-                    if len(img.getbands()) == 1:
-                        rgb_img = convert_grayscale_to_rgb_preserve_range(img)
+                img_obj = Image(src)
+                pil_img = img_obj.pil_image
+                if len(pil_img.getbands()) == 1:
+                    rgb_img = convert_grayscale_to_rgb_preserve_range(pil_img)
                 else:
-                        rgb_img = img.convert("RGB")
+                    rgb_img = pil_img.convert("RGB")
                 rgb_img.save(dst)
             except Exception as exc:
                 logger.warning(f"Failed to convert {src} to RGB: {exc}")

src/model/inference.py

@@ -5,12 +5,12 @@ Handles detection inference and result storage.
 
 from typing import List, Dict, Optional, Callable
 from pathlib import Path
-from PIL import Image
 import cv2
 import numpy as np
 
 from src.model.yolo_wrapper import YOLOWrapper
 from src.database.db_manager import DatabaseManager
+from src.utils.image import Image
 from src.utils.logger import get_logger
 from src.utils.file_utils import get_relative_path
 
@@ -64,9 +64,9 @@ class InferenceEngine:
                 stored_relative_path = str(Path(image_path).resolve())
 
             # Get image dimensions
-            img = Image.open(image_path)
-            width, height = img.size
-            img.close()
+            img = Image(image_path)
+            width = img.width
+            height = img.height
 
             # Perform detection
             detections = self.yolo.predict(image_path, conf=conf)

src/model/yolo_wrapper.py

@@ -7,10 +7,9 @@ from ultralytics import YOLO
 from pathlib import Path
 from typing import Optional, List, Dict, Callable, Any
 import torch
-from PIL import Image
 import tempfile
 import os
-from src.utils.image import convert_grayscale_to_rgb_preserve_range
+from src.utils.image import Image, convert_grayscale_to_rgb_preserve_range
 from src.utils.logger import get_logger
 
 
@@ -232,11 +231,12 @@ class YOLOWrapper:
             source_path = Path(source)
             if source_path.is_file():
                 try:
-                    with Image.open(source_path) as img:
-                        if len(img.getbands()) == 1:
-                            rgb_img = convert_grayscale_to_rgb_preserve_range(img)
+                    img_obj = Image(source_path)
+                    pil_img = img_obj.pil_image
+                    if len(pil_img.getbands()) == 1:
+                        rgb_img = convert_grayscale_to_rgb_preserve_range(pil_img)
                     else:
-                            rgb_img = img.convert("RGB")
+                        rgb_img = pil_img.convert("RGB")
 
                     suffix = source_path.suffix or ".png"
                     tmp = tempfile.NamedTemporaryFile(suffix=suffix, delete=False)