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ultralytics 8.0.155 allow imgsz and batch resume changes (#4366)

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Co-authored-by: Mostafa Nemati <58460889+monemati@users.noreply.github.com>
Co-authored-by: Eduard Voiculescu <eduardvoiculescu95@gmail.com>
This commit is contained in:
Glenn Jocher 2023-08-15 22:02:23 +02:00 • committed by GitHub
parent 60cad0c592
commit 9a0555eca4
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15 changed files with 84 additions and 105 deletions
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22
ultralytics/data/utils.py
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@ -142,16 +142,12 @@ def polygon2mask(imgsz, polygons, color=1, downsample_ratio=1):
downsample_ratio (int): downsample ratio
"""
mask = np.zeros(imgsz, dtype=np.uint8)
polygons = np.asarray(polygons)
polygons = polygons.astype(np.int32)
shape = polygons.shape
polygons = polygons.reshape(shape[0], -1, 2)
polygons = np.asarray(polygons, dtype=np.int32)
polygons = polygons.reshape((polygons.shape[0], -1, 2))
cv2.fillPoly(mask, polygons, color=color)
nh, nw = (imgsz[0] // downsample_ratio, imgsz[1] // downsample_ratio)
# NOTE: fillPoly firstly then resize is trying the keep the same way
# of loss calculation when mask-ratio=1.
mask = cv2.resize(mask, (nw, nh))
return mask
# NOTE: fillPoly first then resize is trying to keep the same way of loss calculation when mask-ratio=1.
return cv2.resize(mask, (nw, nh))
def polygons2masks(imgsz, polygons, color, downsample_ratio=1):
@ -162,11 +158,7 @@ def polygons2masks(imgsz, polygons, color, downsample_ratio=1):
color (int): color
downsample_ratio (int): downsample ratio
"""
masks = []
for si in range(len(polygons)):
mask = polygon2mask(imgsz, [polygons[si].reshape(-1)], color, downsample_ratio)
masks.append(mask)
return np.array(masks)
return np.array([polygon2mask(imgsz, [x.reshape(-1)], color, downsample_ratio) for x in polygons])
def polygons2masks_overlap(imgsz, segments, downsample_ratio=1):
@ -421,7 +413,7 @@ class HUBDatasetStats:
else:
raise ValueError('Undefined dataset task.')
zipped = zip(labels['cls'], coordinates)
return [[int(c), *(round(float(x), 4) for x in points)] for c, points in zipped]
return [[int(c[0]), *(round(float(x), 4) for x in points)] for c, points in zipped]
for split in 'train', 'val', 'test':
if self.data.get(split) is None:
@ -563,7 +555,7 @@ def zip_directory(dir, use_zipfile_library=True):
def autosplit(path=DATASETS_DIR / 'coco8/images', weights=(0.9, 0.1, 0.0), annotated_only=False):
"""
Autosplit a dataset into train/val/test splits and save the resulting splits into autosplit_*.txt files.
Automatically split a dataset into train/val/test splits and save the resulting splits into autosplit_*.txt files.
Args:
path (Path, optional): Path to images directory. Defaults to DATASETS_DIR / 'coco8/images'.