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Recursive directories dataset capability (#1408)

* Recursive directories dataset capability

* x.split('.')[-1]

* f += glob.glob(f"{p}{os.sep}**.*", recursive=True)

* f += glob.glob(str(p / '**.*'), recursive=True)

* remove . from image and vid formats

* .txt to txt

* str(p / '**' / '*.*')
5.0
Glenn Jocher GitHub hace 3 años
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548a98a391
No se encontró ninguna clave conocida en la base de datos para esta firma ID de clave GPG: 4AEE18F83AFDEB23
Se han modificado 2 ficheros con 15 adiciones y 16 borrados
  1. +12
    -13
      utils/datasets.py
  2. +3
    -3
      utils/general.py

+ 12
- 13
utils/datasets.py Ver fichero

@@ -23,8 +23,8 @@ from utils.torch_utils import torch_distributed_zero_first

# Parameters
help_url = 'https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data'
img_formats = ['.bmp', '.jpg', '.jpeg', '.png', '.tif', '.tiff', '.dng']
vid_formats = ['.mov', '.avi', '.mp4', '.mpg', '.mpeg', '.m4v', '.wmv', '.mkv']
img_formats = ['bmp', 'jpg', 'jpeg', 'png', 'tif', 'tiff', 'dng'] # acceptable image suffixes
vid_formats = ['mov', 'avi', 'mp4', 'mpg', 'mpeg', 'm4v', 'wmv', 'mkv'] # acceptable video suffixes

# Get orientation exif tag
for orientation in ExifTags.TAGS.keys():
@@ -125,8 +125,8 @@ class LoadImages: # for inference
else:
raise Exception('ERROR: %s does not exist' % p)

images = [x for x in files if os.path.splitext(x)[-1].lower() in img_formats]
videos = [x for x in files if os.path.splitext(x)[-1].lower() in vid_formats]
images = [x for x in files if x.split('.')[-1].lower() in img_formats]
videos = [x for x in files if x.split('.')[-1].lower() in vid_formats]
ni, nv = len(images), len(videos)

self.img_size = img_size
@@ -337,24 +337,23 @@ class LoadImagesAndLabels(Dataset): # for training/testing
def img2label_paths(img_paths):
# Define label paths as a function of image paths
sa, sb = os.sep + 'images' + os.sep, os.sep + 'labels' + os.sep # /images/, /labels/ substrings
return [x.replace(sa, sb, 1).replace(os.path.splitext(x)[-1], '.txt') for x in img_paths]
return [x.replace(sa, sb, 1).replace(x.split('.')[-1], 'txt') for x in img_paths]

try:
f = [] # image files
for p in path if isinstance(path, list) else [path]:
p = str(Path(p)) # os-agnostic
parent = str(Path(p).parent) + os.sep
if os.path.isfile(p): # file
p = Path(p) # os-agnostic
if p.is_dir(): # dir
f += glob.glob(str(p / '**' / '*.*'), recursive=True)
elif p.is_file(): # file
with open(p, 'r') as t:
t = t.read().splitlines()
parent = str(p.parent) + os.sep
f += [x.replace('./', parent) if x.startswith('./') else x for x in t] # local to global path
elif os.path.isdir(p): # folder
f += glob.iglob(p + os.sep + '*.*')
else:
raise Exception('%s does not exist' % p)
self.img_files = sorted(
[x.replace('/', os.sep) for x in f if os.path.splitext(x)[-1].lower() in img_formats])
assert len(self.img_files) > 0, 'No images found'
self.img_files = sorted([x.replace('/', os.sep) for x in f if x.split('.')[-1].lower() in img_formats])
assert self.img_files, 'No images found'
except Exception as e:
raise Exception('Error loading data from %s: %s\nSee %s' % (path, e, help_url))


+ 3
- 3
utils/general.py Ver fichero

@@ -79,9 +79,9 @@ def check_dataset(dict):
# Download dataset if not found locally
val, s = dict.get('val'), dict.get('download')
if val and len(val):
val = [os.path.abspath(x) for x in (val if isinstance(val, list) else [val])] # val path
if not all(os.path.exists(x) for x in val):
print('\nWARNING: Dataset not found, nonexistent paths: %s' % [*val])
val = [Path(x).resolve() for x in (val if isinstance(val, list) else [val])] # val path
if not all(x.exists() for x in val):
print('\nWARNING: Dataset not found, nonexistent paths: %s' % [str(x) for x in val if not x.exists()])
if s and len(s): # download script
print('Downloading %s ...' % s)
if s.startswith('http') and s.endswith('.zip'): # URL

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