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Updating image splitter

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This commit is contained in:
Martin Laasmaa
2026-01-12 13:28:00 +02:00
parent 510eabfa94
commit d998c65665
3 changed files with 83 additions and 42 deletions
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9
src/utils/image.py
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@@ -17,7 +17,7 @@ from tifffile import imread, imwrite
logger = get_logger(__name__)
def get_pseudo_rgb(arr: np.ndarray, gamma: float = 0.3) -> np.ndarray:
def get_pseudo_rgb(arr: np.ndarray, gamma: float = 0.5) -> np.ndarray:
"""
Convert a grayscale image to a pseudo-RGB image using a gamma correction.
@@ -33,10 +33,11 @@ def get_pseudo_rgb(arr: np.ndarray, gamma: float = 0.3) -> np.ndarray:
a1 = arr.copy().astype(np.float32)
a1 -= np.percentile(a1, 2)
a1[a1 < 0] = 0
# p999 = np.percentile(a1, 99.9)
# a1[a1 > p999] = p999
p999 = np.percentile(a1, 99.9)
a1[a1 > p999] = p999
a1 /= a1.max()
if 0:
a2 = a1.copy()
a2 = a2**gamma
a2 /= a2.max()
@@ -47,7 +48,7 @@ def get_pseudo_rgb(arr: np.ndarray, gamma: float = 0.3) -> np.ndarray:
a3 /= a3.max()
return np.stack([a1, np.zeros(a1.shape), np.zeros(a1.shape)], axis=0)
return np.stack([a2, np.zeros(a1.shape), np.zeros(a1.shape)], axis=0)
# return np.stack([a2, np.zeros(a1.shape), np.zeros(a1.shape)], axis=0)
# return np.stack([a1, a2, a3], axis=0)

29
src/utils/image_splitter.py
View File

@@ -4,10 +4,13 @@ from pathlib import Path
from tifffile import imread, imwrite
from shapely.geometry import LineString
from copy import deepcopy
from scipy.ndimage import zoom
# debug
from src.utils.image import Image
from show_yolo_seg import draw_annotations
import pylab as plt
import cv2
@@ -24,13 +27,15 @@ class Label:
class_id = int(class_id)
bbox = np.array(coords[:4], dtype=np.float32)
polygon = np.array(coords[4:], dtype=np.float32).reshape(-1, 2) if len(coords) > 4 else None
if not any(np.isclose(polygon[0], polygon[-1])):
polygon = np.vstack([polygon, polygon[0]])
return class_id, bbox, polygon
def offset_label(
self,
img_w,
img_h,
distance: float = 3.0,
distance: float = 1.0,
cap_style: int = 2,
join_style: int = 2,
):
@@ -64,7 +69,7 @@ class Label:
line = LineString(pts)
# Buffer distance in pixels
buffered = line.buffer(distance=distance, cap_style=cap_style, join_style=join_style)
self.polygon = np.array(buffered.exterior.coords, dtype=np.float32)
self.polygon = np.array(buffered.exterior.coords, dtype=np.float32) / (img_w, img_h)
xmn, ymn = self.polygon.min(axis=0)
xmx, ymx = self.polygon.max(axis=0)
xc = (xmn + xmx) / 2
@@ -158,6 +163,10 @@ class ImageSplitter:
self.image = imread(image_path)
self.image_path = image_path
self.label_path = label_path
if not label_path.exists():
print(f"Label file {label_path} not found")
self.labels = None
else:
self.labels = YoloLabelReader(label_path)
def split_into_tiles(self, patch_size: tuple = (2, 2)):
@@ -173,8 +182,11 @@ class ImageSplitter:
tile_reference = f"i{i}j{j}"
hrange = (i * hstep / h, (i + 1) * hstep / h)
wrange = (j * wstep / w, (j + 1) * wstep / w)
labels = deepcopy(self.labels.get_labels(hrange, wrange))
tile = self.image[i * hstep : (i + 1) * hstep, j * wstep : (j + 1) * wstep]
labels = None
if self.labels is not None:
labels = deepcopy(self.labels.get_labels(hrange, wrange))
print(id(labels))
if labels is not None:
@@ -234,13 +246,14 @@ class ImageSplitter:
# print("tile shape:", tile.shape)
yolo_annotation = f"{label.class_id} {x_offset/nx} {y_offset/ny} {h/ny} {w/nx} " + " ".join(
yolo_annotation = f"{label.class_id} {x_offset/nx} {y_offset/ny} {h_norm} {w_norm} "
print(yolo_annotation)
yolo_annotation += " ".join(
[
f"{(x*self.image.shape[1]-(xc - x_offset))/nx:.6f} {(y*self.image.shape[0]-(yc-y_offset))/ny:.6f}"
for x, y in label.polygon
]
)
# print(yolo_annotation)
new_label = Label(yolo_annotation=yolo_annotation)
yield tile_reference, tile, [new_label]
@@ -251,6 +264,7 @@ def main(args):
if args.output:
args.output.mkdir(exist_ok=True, parents=True)
(args.output / "images").mkdir(exist_ok=True)
(args.output / "images-zoomed").mkdir(exist_ok=True)
(args.output / "labels").mkdir(exist_ok=True)
for image_path in (args.input / "images").glob("*.tif"):
@@ -297,6 +311,11 @@ def main(args):
if args.output:
imwrite(args.output / "images" / f"{image_path.stem}_{tile_reference}.tif", tile)
scale = 5
tile_zoomed = zoom(tile, zoom=scale)
imwrite(args.output / "images-zoomed" / f"{image_path.stem}_{tile_reference}.tif", tile_zoomed)
if labels is not None:
with open(args.output / "labels" / f"{image_path.stem}_{tile_reference}.txt", "w") as f:
for label in labels:
label.offset_label(tile.shape[1], tile.shape[0])

25
tests/show_yolo_seg.py
View File

@@ -103,6 +103,7 @@ def draw_annotations(img, labels, alpha=0.4, draw_bbox_for_poly=True):
cv2.polylines(img, [pts], isClosed=True, color=color, thickness=1)
# put class text at first point
x, y = int(pts[0, 0]), int(pts[0, 1]) - 6
if 0:
cv2.putText(
img,
str(cls),
@@ -188,12 +189,32 @@ def main():
# continue and just show image
out = draw_annotations(img.copy(), labels, alpha=args.alpha, draw_bbox_for_poly=(not args.no_bbox))
lclass, coords = labels[0]
print(lclass, coords)
bbox = coords[:4]
print("bbox", bbox)
bbox = np.array(bbox) * np.array([img.shape[1], img.shape[0], img.shape[1], img.shape[0]])
yc, xc, h, w = bbox
print("bbox", bbox)
polyline = np.array(coords[4:]).reshape(-1, 2) * np.array([img.shape[1], img.shape[0]])
print("pl", coords[4:])
print("pl", polyline)
# Convert BGR -> RGB for matplotlib display
out_rgb = cv2.cvtColor(out, cv2.COLOR_BGR2RGB)
# out_rgb = cv2.cvtColor(out, cv2.COLOR_BGR2RGB)
out_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
# out_rgb = Image()
plt.figure(figsize=(10, 10 * out.shape[0] / out.shape[1]))
plt.imshow(out_rgb)
plt.axis("off")
plt.plot(polyline[:, 0], polyline[:, 1], "y", linewidth=2)
plt.plot(
[yc - h / 2, yc - h / 2, yc + h / 2, yc + h / 2, yc - h / 2],
[xc - w / 2, xc + w / 2, xc + w / 2, xc - w / 2, xc - w / 2],
"r",
linewidth=2,
)
# plt.axis("off")
plt.title(f"{img_path.name} ({lbl_path.name})")
plt.show()