Updating tiff image patch

pyproject.toml

@@ -82,12 +82,12 @@ include-package-data = true
 "src.database" = ["*.sql"]
 
 [tool.black]
-line-length = 88
+line-length = 120
 target-version = ['py38', 'py39', 'py310', 'py311']
 include = '\.pyi?$'
 
 [tool.pylint.messages_control]
-max-line-length = 88
+max-line-length = 120
 
 [tool.mypy]
 python_version = "3.8"

src/utils/ultralytics_16bit_patch.py

@@ -45,9 +45,7 @@ def apply_ultralytics_16bit_tiff_patches(*, force: bool = False) -> None:
 
     _original_imread = ul_patches.imread
 
-    def tifffile_imread(
+    def tifffile_imread(filename: str, flags: int = cv2.IMREAD_COLOR, pseudo_rgb: bool = True) -> Optional[np.ndarray]:
-        filename: str, flags: int = cv2.IMREAD_COLOR, pseudo_rgb: bool = True
-    ) -> Optional[np.ndarray]:
         """Replacement for [`ultralytics.utils.patches.imread()`](venv/lib/python3.12/site-packages/ultralytics/utils/patches.py:20).
 
         - For `.tif/.tiff`, uses `tifffile.imread()` and preserves dtype (e.g. uint16).
@@ -65,19 +63,17 @@ def apply_ultralytics_16bit_tiff_patches(*, force: bool = False) -> None:
             # - (C, H, W) -> (H, W, C) (heuristic)
             if arr is None:
                 return None
-            if (
+            if arr.ndim == 3 and arr.shape[0] in (1, 3, 4) and arr.shape[0] < arr.shape[1]:
-                arr.ndim == 3
-                and arr.shape[0] in (1, 3, 4)
-                and arr.shape[0] < arr.shape[1]
-            ):
                 arr = np.transpose(arr, (1, 2, 0))
             if arr.ndim == 2:
                 arr = arr[..., None]
 
             # Ensure contiguous array for downstream OpenCV ops.
             # logger.info(f"Loading with monkey-patched imread: {filename}")
-            arr *= 2**8 - 1
+            arr = arr.astype(np.float32)
-            arr = arr.astype(np.uint8)
+            arr /= arr.max()
+            arr *= 2**16 - 1
+            arr = arr.astype(np.uint16)
             return np.ascontiguousarray(arr)
 
         # logger.info(f"Loading with original imread: {filename}")
@@ -142,21 +138,14 @@ def apply_ultralytics_16bit_tiff_patches(*, force: bool = False) -> None:
 
             imgs = batch["img"]
             sz = (
-                random.randrange(
+                random.randrange(int(self.args.imgsz * 0.5), int(self.args.imgsz * 1.5 + self.stride))
-                    int(self.args.imgsz * 0.5), int(self.args.imgsz * 1.5 + self.stride)
-                )
                 // self.stride
                 * self.stride
             )
             sf = sz / max(imgs.shape[2:])
             if sf != 1:
-                ns = [
+                ns = [math.ceil(x * sf / self.stride) * self.stride for x in imgs.shape[2:]]
-                    math.ceil(x * sf / self.stride) * self.stride
+                imgs = nn.functional.interpolate(imgs, size=ns, mode="bilinear", align_corners=False)
-                    for x in imgs.shape[2:]
-                ]
-                imgs = nn.functional.interpolate(
-                    imgs, size=ns, mode="bilinear", align_corners=False
-                )
             batch["img"] = imgs
 
         return batch
@@ -164,6 +153,4 @@ def apply_ultralytics_16bit_tiff_patches(*, force: bool = False) -> None:
     detect_train.DetectionTrainer.preprocess_batch = preprocess_batch_16bit
 
     # Tag function to make it easier to detect patch state.
-    setattr(
+    setattr(detect_train.DetectionTrainer.preprocess_batch, "_ultralytics_16bit_patch", True)
-        detect_train.DetectionTrainer.preprocess_batch, "_ultralytics_16bit_patch", True
-    )

tests/show_yolo_seg.py

@@ -17,6 +17,7 @@ import matplotlib.pyplot as plt
 import argparse
 from pathlib import Path
 import random
+from shapely.geometry import LineString
 
 from src.utils.image import Image
 
@@ -75,7 +76,12 @@ def draw_annotations(img, labels, alpha=0.4, draw_bbox_for_poly=True):
     # img: BGR numpy array
     overlay = img.copy()
     h, w = img.shape[:2]
-    for cls, coords in labels:
+    for line in labels:
+        if isinstance(line, str):
+            cls, coords = parse_label_line(line)
+        if isinstance(line, tuple):
+            cls, coords = line
+
         if not coords:
             continue
         # polygon case (>=6 coordinates)
@@ -83,9 +89,16 @@ def draw_annotations(img, labels, alpha=0.4, draw_bbox_for_poly=True):
             color = random_color_for_class(cls)
 
             x1, y1, x2, y2 = yolo_bbox_to_xyxy(coords[:4], w, h)
+            print(x1, y1, x2, y2)
             cv2.rectangle(img, (x1, y1), (x2, y2), color, 1)
 
             pts = poly_to_pts(coords[4:], w, h)
+            line = LineString(pts)
+            # Buffer distance in pixels
+            buffered = line.buffer(3, cap_style=2, join_style=2)
+            coords = np.array(buffered.exterior.coords, dtype=np.int32)
+            cv2.fillPoly(overlay, [coords], color=(255, 255, 255))
+
             # fill on overlay
             cv2.fillPoly(overlay, [pts], color)
             # outline on base image