From dafa65b07d2f1fa96ee60a77dd17c8a4fb8be45b Mon Sep 17 00:00:00 2001
From: Andre Anjos <andre.anjos@idiap.ch>
Date: Mon, 4 Sep 2017 14:38:46 +0200
Subject: [PATCH] Load only what is annotated (allow flexibility)
---
bob/bio/vein/script/markdet.py | 18 +++++++++++++-----
1 file changed, 13 insertions(+), 5 deletions(-)
diff --git a/bob/bio/vein/script/markdet.py b/bob/bio/vein/script/markdet.py
index a59b48c..c15bb50 100644
--- a/bob/bio/vein/script/markdet.py
+++ b/bob/bio/vein/script/markdet.py
@@ -99,7 +99,7 @@ def validate(args):
'--batch': schema.Use(int),
'--iterations': schema.Use(int),
'<database>': lambda n: n in ('fv3d',),
- '<protocol>': lambda n: n in ('central',),
+ '<protocol>': lambda n: n in ('central', 'left', 'right'),
'<group>': lambda n: n in ('dev',),
str: object, #ignores strings we don't care about
}, ignore_extra_keys=True)
@@ -142,17 +142,20 @@ def main(user_input=None):
from ..preprocessor.utils import poly_to_mask
features = None
target = None
+ loaded = 0
for k, sample in enumerate(objects):
- if args['--samples'] is not None and k >= args['--samples']: break
+ if args['--samples'] is not None and loaded >= args['--samples']:
+ break
path = sample.make_path(directory=db.original_directory,
extension=db.original_extension)
- logger.info('Loading sample %d/%d (%s)...', k, len(objects), path)
+ logger.info('Loading sample %d/%d (%s)...', loaded, len(objects), path)
image = sample.load(directory=db.original_directory,
extension=db.original_extension)
if not (hasattr(image, 'metadata') and 'roi' in image.metadata):
logger.info('Skipping sample (no ROI)')
continue
+ loaded += 1
# copy() required by skimage.util.shape.view_as_windows()
image = image.copy().astype('float64') / 255.
@@ -169,12 +172,17 @@ def main(user_input=None):
mask = mask[1:-1, 1:-1]
for y in range(windows.shape[0]):
for x in range(windows.shape[1]):
- idx = (k*windows.shape[0]*windows.shape[1]) + (y*windows.shape[1]) + x
+ idx = ((loaded-1)*windows.shape[0]*windows.shape[1]) + \
+ (y*windows.shape[1]) + x
features[idx,:-2] = windows[y,x].flatten()
features[idx,-2] = y+1
features[idx,-1] = x+1
target[idx] = mask[y,x]
+ # if number of loaded samples is smaller than expected, clip features array
+ features = features[:loaded*windows.shape[0]*windows.shape[1]]
+ target = target[:loaded*windows.shape[0]*windows.shape[1]]
+
# normalize w.r.t. dimensions
features[:,-2] /= image.shape[0]
features[:,-1] /= image.shape[1]
@@ -214,7 +222,7 @@ def main(user_input=None):
except KeyboardInterrupt:
print() #avoids the ^C line
logger.info('Gracefully stopping training before limit (%d iterations)',
- args['--batch']
+ args['--batch'])
break
# describe errors
--
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