Fixing pseudo rgb

src/utils/ultralytics_16bit_patch.py

@@ -32,8 +32,10 @@ def apply_ultralytics_16bit_tiff_patches(*, force: bool = False) -> None:
 
     import cv2
     import numpy as np
-    import tifffile
+
+    # import tifffile
     import torch
+    from src.utils.image import Image
 
     from ultralytics.utils import patches as ul_patches
 
@@ -55,7 +57,7 @@ def apply_ultralytics_16bit_tiff_patches(*, force: bool = False) -> None:
 
         ext = os.path.splitext(filename)[1].lower()
         if ext in (".tif", ".tiff"):
-            arr = tifffile.imread(filename)
+            arr = Image(filename).get_qt_rgb()[:, :, :3]
 
             # Normalize common shapes:
             # - (H, W) -> (H, W, 1)
@@ -71,35 +73,6 @@ def apply_ultralytics_16bit_tiff_patches(*, force: bool = False) -> None:
             if arr.ndim == 2:
                 arr = arr[..., None]
 
-            # Ultralytics expects BGR ordering when `channels=3`.
-            # For grayscale data we replicate channels (no scaling, no quantization).
-            if flags != cv2.IMREAD_GRAYSCALE:
-                if arr.shape[2] == 1:
-                    if pseudo_rgb:
-                        gamma = 0.3
-                        a1 = arr.copy().astype(np.float32)
-                        a1 -= np.percentile(a1, 2)
-                        a1[a1 < 0] = 0
-                        p98 = np.percentile(a1, 98)
-                        a1[a1 > p98] = p98
-                        a1 /= a1.max()
-
-                        a2 = a1.copy()
-                        a2 = a2**gamma
-                        a2 /= a2.max()
-
-                        a3 = a1.copy()
-                        p90 = np.percentile(a3, 90)
-                        a3[a3 > p90] = p90
-                        a3 /= a3.max()
-
-                        arr = np.concatenate([a1, a2, a3], axis=2)
-
-                    else:
-                        arr = np.repeat(arr, 3, axis=2)
-                elif arr.shape[2] >= 3:
-                    arr = arr[:, :, :3]
-
             # Ensure contiguous array for downstream OpenCV ops.
             logger.info(f"Loading with monkey-patched imread: {filename}")
             return np.ascontiguousarray(arr)