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Add best.pt val and COCO pycocotools val (#98)

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Co-authored-by: ayush chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Glenn Jocher
2022-12-27 04:56:24 +01:00
committed by GitHub
parent a1808eeda4
commit 6f0ba81427
12 changed files with 159 additions and 115 deletions
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15
ultralytics/yolo/data/utils.py
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@ -132,8 +132,9 @@ def polygon2mask(imgsz, polygons, color=1, downsample_ratio=1):
"""
Args:
imgsz (tuple): The image size.
polygons (np.ndarray): [N, M], N is the number of polygons,
M is the number of points(Be divided by 2).
polygons (np.ndarray): [N, M], N is the number of polygons, M is the number of points(Be divided by 2).
color (int): color
downsample_ratio (int): downsample ratio
"""
mask = np.zeros(imgsz, dtype=np.uint8)
polygons = np.asarray(polygons)
@ -152,9 +153,9 @@ def polygons2masks(imgsz, polygons, color, downsample_ratio=1):
"""
Args:
imgsz (tuple): The image size.
polygons (list[np.ndarray]): each polygon is [N, M],
N is the number of polygons,
M is the number of points(Be divided by 2).
polygons (list[np.ndarray]): each polygon is [N, M], N is number of polygons, M is number of points (M % 2 = 0)
color (int): color
downsample_ratio (int): downsample ratio
"""
masks = []
for si in range(len(polygons)):
@ -191,7 +192,7 @@ def polygons2masks_overlap(imgsz, segments, downsample_ratio=1):
def check_dataset_yaml(data, autodownload=True):
# Download, check and/or unzip dataset if not found locally
data = check_file(data)
DATASETS_DIR = Path.cwd() / "../datasets"
DATASETS_DIR = Path.cwd() / "../datasets" # TODO: handle global dataset dir
# Download (optional)
extract_dir = ''
if isinstance(data, (str, Path)) and (is_zipfile(data) or is_tarfile(data)):
@ -231,7 +232,7 @@ def check_dataset_yaml(data, autodownload=True):
if not all(x.exists() for x in val):
LOGGER.info('\nDataset not found ⚠️, missing paths %s' % [str(x) for x in val if not x.exists()])
if not s or not autodownload:
raise Exception('Dataset not found ❌')
raise FileNotFoundError('Dataset not found ❌')
t = time.time()
if s.startswith('http') and s.endswith('.zip'): # URL
f = Path(s).name # filename