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ultralytics 8.0.30 Docker, rect, data=*.zip updates (#832)

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Glenn Jocher 2023-02-06 21:57:10 +04:00 • committed by GitHub
parent 09265b17d7
commit 64f247d692
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17 changed files with 67 additions and 43 deletions
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8
ultralytics/yolo/data/dataset.py
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@ -113,13 +113,15 @@ class YOLODataset(BaseDataset):
tqdm(None, desc=self.prefix + d, total=n, initial=n, bar_format=TQDM_BAR_FORMAT) # display cache results
if cache["msgs"]:
LOGGER.info("\n".join(cache["msgs"])) # display warnings
assert nf > 0, f"{self.prefix}No labels found in {cache_path}, can not start training. {HELP_URL}"
if nf == 0: # number of labels found
raise FileNotFoundError(f"{self.prefix}No labels found in {cache_path}, can not start training. {HELP_URL}")
# Read cache
[cache.pop(k) for k in ("hash", "version", "msgs")] # remove items
labels = cache["labels"]
# Check if the dataset is all boxes or all segments
len_cls = sum(len(lb["cls"]) for lb in labels)
len_boxes = sum(len(lb["bboxes"]) for lb in labels)
len_segments = sum(len(lb["segments"]) for lb in labels)
if len_segments and len_boxes != len_segments:
@ -129,8 +131,8 @@ class YOLODataset(BaseDataset):
"To avoid this please supply either a detect or segment dataset, not a detect-segment mixed dataset.")
for lb in labels:
lb["segments"] = []
nl = len(np.concatenate([label["cls"] for label in labels], 0)) # number of labels
assert nl > 0, f"{self.prefix}All labels empty in {cache_path}, can not start training. {HELP_URL}"
if len_cls == 0:
raise ValueError(f"{self.prefix}All labels empty in {cache_path}, can not start training. {HELP_URL}")
return labels
# TODO: use hyp config to set all these augmentations