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Pass preprocess_image function to generators in evaluate.py #1290

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Mar 2, 2020
Merged

Pass preprocess_image function to generators in evaluate.py #1290

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418b7e7
Pass preprocess_image function to generators in the evaluate.py file
foghegehog Feb 25, 2020
5baaa7c
Fixed typo
foghegehog Feb 25, 2020
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14 changes: 12 additions & 2 deletions keras_retinanet/bin/evaluate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,16 +28,21 @@
from .. import models
from ..preprocessing.csv_generator import CSVGenerator
from ..preprocessing.pascal_voc import PascalVocGenerator
from ..utils.anchors import make_shapes_callback
from ..utils.config import read_config_file, parse_anchor_parameters
from ..utils.eval import evaluate
from ..utils.gpu import setup_gpu
from ..utils.keras_version import check_keras_version
from ..utils.tf_version import check_tf_version


def create_generator(args):
def create_generator(args, preprocess_image):
""" Create generators for evaluation.
"""
common_args = {
'preprocess_image': preprocess_image,
}

if args.dataset_type == 'coco':
# import here to prevent unnecessary dependency on cocoapi
from ..preprocessing.coco import CocoGenerator
Expand All @@ -49,6 +54,7 @@ def create_generator(args):
image_max_side=args.image_max_side,
config=args.config,
shuffle_groups=False,
**common_args
)
elif args.dataset_type == 'pascal':
validation_generator = PascalVocGenerator(
Expand All @@ -59,6 +65,7 @@ def create_generator(args):
image_max_side=args.image_max_side,
config=args.config,
shuffle_groups=False,
**common_args
)
elif args.dataset_type == 'csv':
validation_generator = CSVGenerator(
Expand All @@ -68,6 +75,7 @@ def create_generator(args):
image_max_side=args.image_max_side,
config=args.config,
shuffle_groups=False,
**common_args
)
else:
raise ValueError('Invalid data type received: {}'.format(args.dataset_type))
Expand Down Expand Up @@ -131,7 +139,8 @@ def main(args=None):
args.config = read_config_file(args.config)

# create the generator
generator = create_generator(args)
backbone = models.backbone(args.backbone)
generator = create_generator(args, backbone.preprocess_image)

# optionally load anchor parameters
anchor_params = None
Expand All @@ -141,6 +150,7 @@ def main(args=None):
# load the model
print('Loading model, this may take a second...')
model = models.load_model(args.model, backbone_name=args.backbone)
generator.compute_shapes = make_shapes_callback(model)
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This can also be passed to the constructor of generator. It does mean that the order of creating generators followed by loading of the model has to be the other way around, but I don't think this is an issue.


# optionally convert the model
if args.convert_model:
Expand Down