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Add the option to seed training. #1085

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Add the option to seed training. #1085

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fb61c3f
Add the option to seed training.
martinzlocha Jul 25, 2019
6928f94
Pass seed to random_transform_generator.
martinzlocha Aug 9, 2019
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1 change: 1 addition & 0 deletions CONTRIBUTORS.md
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Original file line number Diff line number Diff line change
Expand Up @@ -36,3 +36,4 @@ please create an issue or pull request at https://github.com/fizyr/keras-retinan
* Eduardo Ramos
* DiegoAgher
* Alexander Pacha
* Martin Zlocha
16 changes: 15 additions & 1 deletion keras_retinanet/bin/train.py
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Expand Up @@ -21,9 +21,11 @@
import sys
import warnings

import random
import keras
import keras.preprocessing.image
import tensorflow as tf
import numpy as np

# Allow relative imports when being executed as script.
if __name__ == "__main__" and __package__ is None:
Expand Down Expand Up @@ -223,6 +225,11 @@ def create_generators(args, preprocess_image):
'preprocess_image' : preprocess_image,
}

prng = None

if args.seed:
prng = np.random.RandomState(args.seed)

# create random transform generator for augmenting training data
if args.random_transform:
transform_generator = random_transform_generator(
Expand All @@ -236,6 +243,7 @@ def create_generators(args, preprocess_image):
max_scaling=(1.1, 1.1),
flip_x_chance=0.5,
flip_y_chance=0.5,
prng=prng
)
visual_effect_generator = random_visual_effect_generator(
contrast_range=(0.9, 1.1),
Expand All @@ -244,7 +252,7 @@ def create_generators(args, preprocess_image):
saturation_range=(0.95, 1.05)
)
else:
transform_generator = random_transform_generator(flip_x_chance=0.5)
transform_generator = random_transform_generator(flip_x_chance=0.5, prng=prng)
visual_effect_generator = None

if args.dataset_type == 'coco':
Expand Down Expand Up @@ -429,6 +437,7 @@ def csv_list(string):
parser.add_argument('--config', help='Path to a configuration parameters .ini file.')
parser.add_argument('--weighted-average', help='Compute the mAP using the weighted average of precisions among classes.', action='store_true')
parser.add_argument('--compute-val-loss', help='Compute validation loss during training', dest='compute_val_loss', action='store_true')
parser.add_argument('--seed', help='Seed value to use for training.')

# Fit generator arguments
parser.add_argument('--multiprocessing', help='Use multiprocessing in fit_generator.', action='store_true')
Expand All @@ -444,6 +453,11 @@ def main(args=None):
args = sys.argv[1:]
args = parse_args(args)

if args.seed:
np.random.seed(args.seed)
tf.set_random_seed(args.seed)
random.seed(args.seed)

# create object that stores backbone information
backbone = models.backbone(args.backbone)

Expand Down