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ModelZoo
ResNet50_tensorflow
Commits
5a2cf36f
Commit
5a2cf36f
authored
Jul 23, 2020
by
Kaushik Shivakumar
Browse files
Merge remote-tracking branch 'upstream/master' into newavarecords
parents
258ddfc3
a829e648
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research/object_detection/configs/tf2/faster_rcnn_resnet152_v1_1024x1024_coco17_tpu-8.config
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research/object_detection/configs/tf2/faster_rcnn_resnet152_v1_640x640_coco17_tpu-8.config
.../tf2/faster_rcnn_resnet152_v1_640x640_coco17_tpu-8.config
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research/object_detection/configs/tf2/faster_rcnn_resnet152_v1_800x1333_coco17_gpu-8.config
...tf2/faster_rcnn_resnet152_v1_800x1333_coco17_gpu-8.config
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research/object_detection/configs/tf2/faster_rcnn_resnet50_v1_1024x1024_coco17_tpu-8.config
...tf2/faster_rcnn_resnet50_v1_1024x1024_coco17_tpu-8.config
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research/object_detection/configs/tf2/faster_rcnn_resnet50_v1_640x640_coco17_tpu-8.config
...s/tf2/faster_rcnn_resnet50_v1_640x640_coco17_tpu-8.config
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research/object_detection/configs/tf2/faster_rcnn_resnet50_v1_800x1333_coco17_gpu-8.config
.../tf2/faster_rcnn_resnet50_v1_800x1333_coco17_gpu-8.config
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research/object_detection/configs/tf2/mask_rcnn_inception_resnet_v2_1024x1024_coco17_gpu-8.config
...sk_rcnn_inception_resnet_v2_1024x1024_coco17_gpu-8.config
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research/object_detection/configs/tf2/ssd_efficientdet_d0_512x512_coco17_tpu-8.config
...nfigs/tf2/ssd_efficientdet_d0_512x512_coco17_tpu-8.config
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research/object_detection/configs/tf2/ssd_efficientdet_d1_640x640_coco17_tpu-8.config
...nfigs/tf2/ssd_efficientdet_d1_640x640_coco17_tpu-8.config
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research/object_detection/configs/tf2/ssd_efficientdet_d2_768x768_coco17_tpu-8.config
...nfigs/tf2/ssd_efficientdet_d2_768x768_coco17_tpu-8.config
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research/object_detection/configs/tf2/ssd_efficientdet_d3_896x896_coco17_tpu-32.config
...figs/tf2/ssd_efficientdet_d3_896x896_coco17_tpu-32.config
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research/object_detection/configs/tf2/ssd_efficientdet_d4_1024x1024_coco17_tpu-32.config
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research/object_detection/configs/tf2/ssd_efficientdet_d5_1280x1280_coco17_tpu-32.config
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research/object_detection/configs/tf2/ssd_efficientdet_d6_1408x1408_coco17_tpu-32.config
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research/object_detection/configs/tf2/ssd_efficientdet_d7_1536x1536_coco17_tpu-32.config
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research/object_detection/configs/tf2/ssd_mobilenet_v1_fpn_640x640_coco17_tpu-8.config
...figs/tf2/ssd_mobilenet_v1_fpn_640x640_coco17_tpu-8.config
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research/object_detection/configs/tf2/ssd_mobilenet_v2_320x320_coco17_tpu-8.config
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research/object_detection/configs/tf2/ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8.config
.../tf2/ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8.config
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research/object_detection/configs/tf2/ssd_mobilenet_v2_fpnlite_640x640_coco17_tpu-8.config
.../tf2/ssd_mobilenet_v2_fpnlite_640x640_coco17_tpu-8.config
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research/object_detection/configs/tf2/ssd_resnet101_v1_fpn_1024x1024_coco17_tpu-8.config
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research/object_detection/configs/tf2/faster_rcnn_resnet152_v1_1024x1024_coco17_tpu-8.config
0 → 100644
View file @
5a2cf36f
# Faster R-CNN with Resnet-152 (v1)
# w/high res inputs, long training schedule
# Trained on COCO, initialized from Imagenet classification checkpoint
#
# Train on TPU-8
#
# Achieves 37.6 mAP on COCO17 val
model
{
faster_rcnn
{
num_classes
:
90
image_resizer
{
fixed_shape_resizer
{
width
:
1024
height
:
1024
}
}
feature_extractor
{
type
:
'faster_rcnn_resnet152_keras'
batch_norm_trainable
:
true
}
first_stage_anchor_generator
{
grid_anchor_generator
{
scales
: [
0
.
25
,
0
.
5
,
1
.
0
,
2
.
0
]
aspect_ratios
: [
0
.
5
,
1
.
0
,
2
.
0
]
height_stride
:
16
width_stride
:
16
}
}
first_stage_box_predictor_conv_hyperparams
{
op
:
CONV
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
01
}
}
}
first_stage_nms_score_threshold
:
0
.
0
first_stage_nms_iou_threshold
:
0
.
7
first_stage_max_proposals
:
300
first_stage_localization_loss_weight
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2
.
0
first_stage_objectness_loss_weight
:
1
.
0
initial_crop_size
:
14
maxpool_kernel_size
:
2
maxpool_stride
:
2
second_stage_box_predictor
{
mask_rcnn_box_predictor
{
use_dropout
:
false
dropout_keep_probability
:
1
.
0
fc_hyperparams
{
op
:
FC
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
variance_scaling_initializer
{
factor
:
1
.
0
uniform
:
true
mode
:
FAN_AVG
}
}
}
share_box_across_classes
:
true
}
}
second_stage_post_processing
{
batch_non_max_suppression
{
score_threshold
:
0
.
0
iou_threshold
:
0
.
6
max_detections_per_class
:
100
max_total_detections
:
300
}
score_converter
:
SOFTMAX
}
second_stage_localization_loss_weight
:
2
.
0
second_stage_classification_loss_weight
:
1
.
0
use_static_shapes
:
true
use_matmul_crop_and_resize
:
true
clip_anchors_to_image
:
true
use_static_balanced_label_sampler
:
true
use_matmul_gather_in_matcher
:
true
}
}
train_config
: {
batch_size
:
64
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
num_steps
:
100000
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
: .
04
total_steps
:
100000
warmup_learning_rate
: .
013333
warmup_steps
:
2000
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/resnet152.ckpt-1"
fine_tune_checkpoint_type
:
"classification"
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_adjust_hue
{
}
}
data_augmentation_options
{
random_adjust_contrast
{
}
}
data_augmentation_options
{
random_adjust_saturation
{
}
}
data_augmentation_options
{
random_square_crop_by_scale
{
scale_min
:
0
.
6
scale_max
:
1
.
3
}
}
max_number_of_boxes
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unpad_groundtruth_tensors
:
false
use_bfloat16
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true
# works only on TPUs
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/faster_rcnn_resnet152_v1_640x640_coco17_tpu-8.config
0 → 100644
View file @
5a2cf36f
# Faster R-CNN with Resnet-152 (v1)
# Trained on COCO, initialized from Imagenet classification checkpoint
#
# Train on TPU-8
#
# Achieves 32.4 mAP on COCO17 val
model
{
faster_rcnn
{
num_classes
:
90
image_resizer
{
keep_aspect_ratio_resizer
{
min_dimension
:
640
max_dimension
:
640
pad_to_max_dimension
:
true
}
}
feature_extractor
{
type
:
'faster_rcnn_resnet152_keras'
batch_norm_trainable
:
true
}
first_stage_anchor_generator
{
grid_anchor_generator
{
scales
: [
0
.
25
,
0
.
5
,
1
.
0
,
2
.
0
]
aspect_ratios
: [
0
.
5
,
1
.
0
,
2
.
0
]
height_stride
:
16
width_stride
:
16
}
}
first_stage_box_predictor_conv_hyperparams
{
op
:
CONV
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
01
}
}
}
first_stage_nms_score_threshold
:
0
.
0
first_stage_nms_iou_threshold
:
0
.
7
first_stage_max_proposals
:
300
first_stage_localization_loss_weight
:
2
.
0
first_stage_objectness_loss_weight
:
1
.
0
initial_crop_size
:
14
maxpool_kernel_size
:
2
maxpool_stride
:
2
second_stage_box_predictor
{
mask_rcnn_box_predictor
{
use_dropout
:
false
dropout_keep_probability
:
1
.
0
fc_hyperparams
{
op
:
FC
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
variance_scaling_initializer
{
factor
:
1
.
0
uniform
:
true
mode
:
FAN_AVG
}
}
}
share_box_across_classes
:
true
}
}
second_stage_post_processing
{
batch_non_max_suppression
{
score_threshold
:
0
.
0
iou_threshold
:
0
.
6
max_detections_per_class
:
100
max_total_detections
:
300
}
score_converter
:
SOFTMAX
}
second_stage_localization_loss_weight
:
2
.
0
second_stage_classification_loss_weight
:
1
.
0
use_static_shapes
:
true
use_matmul_crop_and_resize
:
true
clip_anchors_to_image
:
true
use_static_balanced_label_sampler
:
true
use_matmul_gather_in_matcher
:
true
}
}
train_config
: {
batch_size
:
64
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
num_steps
:
25000
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
: .
04
total_steps
:
25000
warmup_learning_rate
: .
013333
warmup_steps
:
2000
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/resnet152.ckpt-1"
fine_tune_checkpoint_type
:
"classification"
data_augmentation_options
{
random_horizontal_flip
{
}
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
use_bfloat16
:
true
# works only on TPUs
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/faster_rcnn_resnet152_v1_800x1333_coco17_gpu-8.config
0 → 100644
View file @
5a2cf36f
# Faster R-CNN with Resnet-152 (v1),
# Initialized from Imagenet classification checkpoint
#
# Train on GPU-8
#
# Achieves 37.3 mAP on COCO17 val
model
{
faster_rcnn
{
num_classes
:
90
image_resizer
{
keep_aspect_ratio_resizer
{
min_dimension
:
800
max_dimension
:
1333
pad_to_max_dimension
:
true
}
}
feature_extractor
{
type
:
'faster_rcnn_resnet152_keras'
}
first_stage_anchor_generator
{
grid_anchor_generator
{
scales
: [
0
.
25
,
0
.
5
,
1
.
0
,
2
.
0
]
aspect_ratios
: [
0
.
5
,
1
.
0
,
2
.
0
]
height_stride
:
16
width_stride
:
16
}
}
first_stage_box_predictor_conv_hyperparams
{
op
:
CONV
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
01
}
}
}
first_stage_nms_score_threshold
:
0
.
0
first_stage_nms_iou_threshold
:
0
.
7
first_stage_max_proposals
:
300
first_stage_localization_loss_weight
:
2
.
0
first_stage_objectness_loss_weight
:
1
.
0
initial_crop_size
:
14
maxpool_kernel_size
:
2
maxpool_stride
:
2
second_stage_box_predictor
{
mask_rcnn_box_predictor
{
use_dropout
:
false
dropout_keep_probability
:
1
.
0
fc_hyperparams
{
op
:
FC
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
variance_scaling_initializer
{
factor
:
1
.
0
uniform
:
true
mode
:
FAN_AVG
}
}
}
}
}
second_stage_post_processing
{
batch_non_max_suppression
{
score_threshold
:
0
.
0
iou_threshold
:
0
.
6
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SOFTMAX
}
second_stage_localization_loss_weight
:
2
.
0
second_stage_classification_loss_weight
:
1
.
0
}
}
train_config
: {
batch_size
:
16
num_steps
:
200000
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
:
0
.
01
total_steps
:
200000
warmup_learning_rate
:
0
.
0
warmup_steps
:
5000
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
gradient_clipping_by_norm
:
10
.
0
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/resnet152.ckpt-1"
fine_tune_checkpoint_type
:
"classification"
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_adjust_hue
{
}
}
data_augmentation_options
{
random_adjust_contrast
{
}
}
data_augmentation_options
{
random_adjust_saturation
{
}
}
data_augmentation_options
{
random_square_crop_by_scale
{
scale_min
:
0
.
6
scale_max
:
1
.
3
}
}
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/faster_rcnn_resnet50_v1_1024x1024_coco17_tpu-8.config
0 → 100644
View file @
5a2cf36f
# Faster R-CNN with Resnet-50 (v1),
# w/high res inputs, long training schedule
# Trained on COCO, initialized from Imagenet classification checkpoint
#
# Train on TPU-8
#
# Achieves 31.0 mAP on COCO17 val
model
{
faster_rcnn
{
num_classes
:
90
image_resizer
{
fixed_shape_resizer
{
width
:
1024
height
:
1024
}
}
feature_extractor
{
type
:
'faster_rcnn_resnet50_keras'
batch_norm_trainable
:
true
}
first_stage_anchor_generator
{
grid_anchor_generator
{
scales
: [
0
.
25
,
0
.
5
,
1
.
0
,
2
.
0
]
aspect_ratios
: [
0
.
5
,
1
.
0
,
2
.
0
]
height_stride
:
16
width_stride
:
16
}
}
first_stage_box_predictor_conv_hyperparams
{
op
:
CONV
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
01
}
}
}
first_stage_nms_score_threshold
:
0
.
0
first_stage_nms_iou_threshold
:
0
.
7
first_stage_max_proposals
:
300
first_stage_localization_loss_weight
:
2
.
0
first_stage_objectness_loss_weight
:
1
.
0
initial_crop_size
:
14
maxpool_kernel_size
:
2
maxpool_stride
:
2
second_stage_box_predictor
{
mask_rcnn_box_predictor
{
use_dropout
:
false
dropout_keep_probability
:
1
.
0
fc_hyperparams
{
op
:
FC
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
variance_scaling_initializer
{
factor
:
1
.
0
uniform
:
true
mode
:
FAN_AVG
}
}
}
share_box_across_classes
:
true
}
}
second_stage_post_processing
{
batch_non_max_suppression
{
score_threshold
:
0
.
0
iou_threshold
:
0
.
6
max_detections_per_class
:
100
max_total_detections
:
300
}
score_converter
:
SOFTMAX
}
second_stage_localization_loss_weight
:
2
.
0
second_stage_classification_loss_weight
:
1
.
0
use_static_shapes
:
true
use_matmul_crop_and_resize
:
true
clip_anchors_to_image
:
true
use_static_balanced_label_sampler
:
true
use_matmul_gather_in_matcher
:
true
}
}
train_config
: {
batch_size
:
64
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
num_steps
:
100000
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
: .
04
total_steps
:
100000
warmup_learning_rate
: .
013333
warmup_steps
:
2000
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/resnet50.ckpt-1"
fine_tune_checkpoint_type
:
"classification"
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_adjust_hue
{
}
}
data_augmentation_options
{
random_adjust_contrast
{
}
}
data_augmentation_options
{
random_adjust_saturation
{
}
}
data_augmentation_options
{
random_square_crop_by_scale
{
scale_min
:
0
.
6
scale_max
:
1
.
3
}
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
use_bfloat16
:
true
# works only on TPUs
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/faster_rcnn_resnet50_v1_640x640_coco17_tpu-8.config
0 → 100644
View file @
5a2cf36f
# Faster R-CNN with Resnet-50 (v1) with 640x640 input resolution
# Trained on COCO, initialized from Imagenet classification checkpoint
#
# Train on TPU-8
#
# Achieves 29.3 mAP on COCO17 Val
model
{
faster_rcnn
{
num_classes
:
90
image_resizer
{
keep_aspect_ratio_resizer
{
min_dimension
:
640
max_dimension
:
640
pad_to_max_dimension
:
true
}
}
feature_extractor
{
type
:
'faster_rcnn_resnet50_keras'
batch_norm_trainable
:
true
}
first_stage_anchor_generator
{
grid_anchor_generator
{
scales
: [
0
.
25
,
0
.
5
,
1
.
0
,
2
.
0
]
aspect_ratios
: [
0
.
5
,
1
.
0
,
2
.
0
]
height_stride
:
16
width_stride
:
16
}
}
first_stage_box_predictor_conv_hyperparams
{
op
:
CONV
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
01
}
}
}
first_stage_nms_score_threshold
:
0
.
0
first_stage_nms_iou_threshold
:
0
.
7
first_stage_max_proposals
:
300
first_stage_localization_loss_weight
:
2
.
0
first_stage_objectness_loss_weight
:
1
.
0
initial_crop_size
:
14
maxpool_kernel_size
:
2
maxpool_stride
:
2
second_stage_box_predictor
{
mask_rcnn_box_predictor
{
use_dropout
:
false
dropout_keep_probability
:
1
.
0
fc_hyperparams
{
op
:
FC
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
variance_scaling_initializer
{
factor
:
1
.
0
uniform
:
true
mode
:
FAN_AVG
}
}
}
share_box_across_classes
:
true
}
}
second_stage_post_processing
{
batch_non_max_suppression
{
score_threshold
:
0
.
0
iou_threshold
:
0
.
6
max_detections_per_class
:
100
max_total_detections
:
300
}
score_converter
:
SOFTMAX
}
second_stage_localization_loss_weight
:
2
.
0
second_stage_classification_loss_weight
:
1
.
0
use_static_shapes
:
true
use_matmul_crop_and_resize
:
true
clip_anchors_to_image
:
true
use_static_balanced_label_sampler
:
true
use_matmul_gather_in_matcher
:
true
}
}
train_config
: {
batch_size
:
64
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
num_steps
:
25000
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
: .
04
total_steps
:
25000
warmup_learning_rate
: .
013333
warmup_steps
:
2000
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/resnet50.ckpt-1"
fine_tune_checkpoint_type
:
"classification"
data_augmentation_options
{
random_horizontal_flip
{
}
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
use_bfloat16
:
true
# works only on TPUs
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/faster_rcnn_resnet50_v1_800x1333_coco17_gpu-8.config
0 → 100644
View file @
5a2cf36f
# Faster R-CNN with Resnet-50 (v1),
# Initialized from Imagenet classification checkpoint
#
# Train on GPU-8
#
# Achieves 31.4 mAP on COCO17 val
model
{
faster_rcnn
{
num_classes
:
90
image_resizer
{
keep_aspect_ratio_resizer
{
min_dimension
:
800
max_dimension
:
1333
pad_to_max_dimension
:
true
}
}
feature_extractor
{
type
:
'faster_rcnn_resnet50_keras'
}
first_stage_anchor_generator
{
grid_anchor_generator
{
scales
: [
0
.
25
,
0
.
5
,
1
.
0
,
2
.
0
]
aspect_ratios
: [
0
.
5
,
1
.
0
,
2
.
0
]
height_stride
:
16
width_stride
:
16
}
}
first_stage_box_predictor_conv_hyperparams
{
op
:
CONV
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
01
}
}
}
first_stage_nms_score_threshold
:
0
.
0
first_stage_nms_iou_threshold
:
0
.
7
first_stage_max_proposals
:
300
first_stage_localization_loss_weight
:
2
.
0
first_stage_objectness_loss_weight
:
1
.
0
initial_crop_size
:
14
maxpool_kernel_size
:
2
maxpool_stride
:
2
second_stage_box_predictor
{
mask_rcnn_box_predictor
{
use_dropout
:
false
dropout_keep_probability
:
1
.
0
fc_hyperparams
{
op
:
FC
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
variance_scaling_initializer
{
factor
:
1
.
0
uniform
:
true
mode
:
FAN_AVG
}
}
}
}
}
second_stage_post_processing
{
batch_non_max_suppression
{
score_threshold
:
0
.
0
iou_threshold
:
0
.
6
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SOFTMAX
}
second_stage_localization_loss_weight
:
2
.
0
second_stage_classification_loss_weight
:
1
.
0
}
}
train_config
: {
batch_size
:
16
num_steps
:
200000
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
:
0
.
01
total_steps
:
200000
warmup_learning_rate
:
0
.
0
warmup_steps
:
5000
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
gradient_clipping_by_norm
:
10
.
0
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/resnet50.ckpt-1"
fine_tune_checkpoint_type
:
"classification"
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_adjust_hue
{
}
}
data_augmentation_options
{
random_adjust_contrast
{
}
}
data_augmentation_options
{
random_adjust_saturation
{
}
}
data_augmentation_options
{
random_square_crop_by_scale
{
scale_min
:
0
.
6
scale_max
:
1
.
3
}
}
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/mask_rcnn_inception_resnet_v2_1024x1024_coco17_gpu-8.config
0 → 100644
View file @
5a2cf36f
# Mask R-CNN with Inception Resnet v2 (no atrous)
# Sync-trained on COCO (with 8 GPUs) with batch size 16 (1024x1024 resolution)
# Initialized from Imagenet classification checkpoint
#
# Train on GPU-8
#
# Achieves 40.4 box mAP and 35.5 mask mAP on COCO17 val
model
{
faster_rcnn
{
number_of_stages
:
3
num_classes
:
90
image_resizer
{
fixed_shape_resizer
{
height
:
1024
width
:
1024
}
}
feature_extractor
{
type
:
'faster_rcnn_inception_resnet_v2_keras'
}
first_stage_anchor_generator
{
grid_anchor_generator
{
scales
: [
0
.
25
,
0
.
5
,
1
.
0
,
2
.
0
]
aspect_ratios
: [
0
.
5
,
1
.
0
,
2
.
0
]
height_stride
:
16
width_stride
:
16
}
}
first_stage_box_predictor_conv_hyperparams
{
op
:
CONV
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
01
}
}
}
first_stage_nms_score_threshold
:
0
.
0
first_stage_nms_iou_threshold
:
0
.
7
first_stage_max_proposals
:
300
first_stage_localization_loss_weight
:
2
.
0
first_stage_objectness_loss_weight
:
1
.
0
initial_crop_size
:
17
maxpool_kernel_size
:
1
maxpool_stride
:
1
second_stage_box_predictor
{
mask_rcnn_box_predictor
{
use_dropout
:
false
dropout_keep_probability
:
1
.
0
fc_hyperparams
{
op
:
FC
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
variance_scaling_initializer
{
factor
:
1
.
0
uniform
:
true
mode
:
FAN_AVG
}
}
}
mask_height
:
33
mask_width
:
33
mask_prediction_conv_depth
:
0
mask_prediction_num_conv_layers
:
4
conv_hyperparams
{
op
:
CONV
regularizer
{
l2_regularizer
{
weight
:
0
.
0
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
01
}
}
}
predict_instance_masks
:
true
}
}
second_stage_post_processing
{
batch_non_max_suppression
{
score_threshold
:
0
.
0
iou_threshold
:
0
.
6
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SOFTMAX
}
second_stage_localization_loss_weight
:
2
.
0
second_stage_classification_loss_weight
:
1
.
0
second_stage_mask_prediction_loss_weight
:
4
.
0
resize_masks
:
false
}
}
train_config
: {
batch_size
:
16
num_steps
:
200000
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
:
0
.
008
total_steps
:
200000
warmup_learning_rate
:
0
.
0
warmup_steps
:
5000
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
gradient_clipping_by_norm
:
10
.
0
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/inception_resnet_v2.ckpt-1"
fine_tune_checkpoint_type
:
"classification"
data_augmentation_options
{
random_horizontal_flip
{
}
}
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
load_instance_masks
:
true
mask_type
:
PNG_MASKS
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
metrics_set
:
"coco_mask_metrics"
eval_instance_masks
:
true
use_moving_averages
:
false
batch_size
:
1
include_metrics_per_category
:
true
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
load_instance_masks
:
true
mask_type
:
PNG_MASKS
}
research/object_detection/configs/tf2/ssd_efficientdet_d0_512x512_coco17_tpu-8.config
0 → 100644
View file @
5a2cf36f
# SSD with EfficientNet-b0 + BiFPN feature extractor,
# shared box predictor and focal loss (a.k.a EfficientDet-d0).
# See EfficientDet, Tan et al, https://arxiv.org/abs/1911.09070
# See Lin et al, https://arxiv.org/abs/1708.02002
# Trained on COCO, initialized from an EfficientNet-b0 checkpoint.
#
# Train on TPU-8
model
{
ssd
{
inplace_batchnorm_update
:
true
freeze_batchnorm
:
false
num_classes
:
90
add_background_class
:
false
box_coder
{
faster_rcnn_box_coder
{
y_scale
:
10
.
0
x_scale
:
10
.
0
height_scale
:
5
.
0
width_scale
:
5
.
0
}
}
matcher
{
argmax_matcher
{
matched_threshold
:
0
.
5
unmatched_threshold
:
0
.
5
ignore_thresholds
:
false
negatives_lower_than_unmatched
:
true
force_match_for_each_row
:
true
use_matmul_gather
:
true
}
}
similarity_calculator
{
iou_similarity
{
}
}
encode_background_as_zeros
:
true
anchor_generator
{
multiscale_anchor_generator
{
min_level
:
3
max_level
:
7
anchor_scale
:
4
.
0
aspect_ratios
: [
1
.
0
,
2
.
0
,
0
.
5
]
scales_per_octave
:
3
}
}
image_resizer
{
keep_aspect_ratio_resizer
{
min_dimension
:
512
max_dimension
:
512
pad_to_max_dimension
:
true
}
}
box_predictor
{
weight_shared_convolutional_box_predictor
{
depth
:
64
class_prediction_bias_init
: -
4
.
6
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
decay
:
0
.
99
epsilon
:
0
.
001
}
}
num_layers_before_predictor
:
3
kernel_size
:
3
use_depthwise
:
true
}
}
feature_extractor
{
type
:
'ssd_efficientnet-b0_bifpn_keras'
bifpn
{
min_level
:
3
max_level
:
7
num_iterations
:
3
num_filters
:
64
}
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
03
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
99
,
epsilon
:
0
.
001
,
}
}
}
loss
{
classification_loss
{
weighted_sigmoid_focal
{
alpha
:
0
.
25
gamma
:
1
.
5
}
}
localization_loss
{
weighted_smooth_l1
{
}
}
classification_weight
:
1
.
0
localization_weight
:
1
.
0
}
normalize_loss_by_num_matches
:
true
normalize_loc_loss_by_codesize
:
true
post_processing
{
batch_non_max_suppression
{
score_threshold
:
1
e
-
8
iou_threshold
:
0
.
5
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SIGMOID
}
}
}
train_config
: {
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/ckpt-0"
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint_type
:
"classification"
batch_size
:
128
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
use_bfloat16
:
true
num_steps
:
300000
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_scale_crop_and_pad_to_square
{
output_size
:
512
scale_min
:
0
.
1
scale_max
:
2
.
0
}
}
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
:
8
e
-
2
total_steps
:
300000
warmup_learning_rate
: .
001
warmup_steps
:
2500
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/ssd_efficientdet_d1_640x640_coco17_tpu-8.config
0 → 100644
View file @
5a2cf36f
# SSD with EfficientNet-b1 + BiFPN feature extractor,
# shared box predictor and focal loss (a.k.a EfficientDet-d1).
# See EfficientDet, Tan et al, https://arxiv.org/abs/1911.09070
# See Lin et al, https://arxiv.org/abs/1708.02002
# Trained on COCO, initialized from an EfficientNet-b1 checkpoint.
#
# Train on TPU-8
model
{
ssd
{
inplace_batchnorm_update
:
true
freeze_batchnorm
:
false
num_classes
:
90
add_background_class
:
false
box_coder
{
faster_rcnn_box_coder
{
y_scale
:
10
.
0
x_scale
:
10
.
0
height_scale
:
5
.
0
width_scale
:
5
.
0
}
}
matcher
{
argmax_matcher
{
matched_threshold
:
0
.
5
unmatched_threshold
:
0
.
5
ignore_thresholds
:
false
negatives_lower_than_unmatched
:
true
force_match_for_each_row
:
true
use_matmul_gather
:
true
}
}
similarity_calculator
{
iou_similarity
{
}
}
encode_background_as_zeros
:
true
anchor_generator
{
multiscale_anchor_generator
{
min_level
:
3
max_level
:
7
anchor_scale
:
4
.
0
aspect_ratios
: [
1
.
0
,
2
.
0
,
0
.
5
]
scales_per_octave
:
3
}
}
image_resizer
{
keep_aspect_ratio_resizer
{
min_dimension
:
640
max_dimension
:
640
pad_to_max_dimension
:
true
}
}
box_predictor
{
weight_shared_convolutional_box_predictor
{
depth
:
88
class_prediction_bias_init
: -
4
.
6
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
decay
:
0
.
99
epsilon
:
0
.
001
}
}
num_layers_before_predictor
:
3
kernel_size
:
3
use_depthwise
:
true
}
}
feature_extractor
{
type
:
'ssd_efficientnet-b1_bifpn_keras'
bifpn
{
min_level
:
3
max_level
:
7
num_iterations
:
4
num_filters
:
88
}
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
03
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
99
,
epsilon
:
0
.
001
,
}
}
}
loss
{
classification_loss
{
weighted_sigmoid_focal
{
alpha
:
0
.
25
gamma
:
1
.
5
}
}
localization_loss
{
weighted_smooth_l1
{
}
}
classification_weight
:
1
.
0
localization_weight
:
1
.
0
}
normalize_loss_by_num_matches
:
true
normalize_loc_loss_by_codesize
:
true
post_processing
{
batch_non_max_suppression
{
score_threshold
:
1
e
-
8
iou_threshold
:
0
.
5
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SIGMOID
}
}
}
train_config
: {
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/ckpt-0"
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint_type
:
"classification"
batch_size
:
128
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
use_bfloat16
:
true
num_steps
:
300000
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_scale_crop_and_pad_to_square
{
output_size
:
640
scale_min
:
0
.
1
scale_max
:
2
.
0
}
}
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
:
8
e
-
2
total_steps
:
300000
warmup_learning_rate
: .
001
warmup_steps
:
2500
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/ssd_efficientdet_d2_768x768_coco17_tpu-8.config
0 → 100644
View file @
5a2cf36f
# SSD with EfficientNet-b2 + BiFPN feature extractor,
# shared box predictor and focal loss (a.k.a EfficientDet-d2).
# See EfficientDet, Tan et al, https://arxiv.org/abs/1911.09070
# See Lin et al, https://arxiv.org/abs/1708.02002
# Trained on COCO, initialized from an EfficientNet-b2 checkpoint.
#
# Train on TPU-8
model
{
ssd
{
inplace_batchnorm_update
:
true
freeze_batchnorm
:
false
num_classes
:
90
add_background_class
:
false
box_coder
{
faster_rcnn_box_coder
{
y_scale
:
10
.
0
x_scale
:
10
.
0
height_scale
:
5
.
0
width_scale
:
5
.
0
}
}
matcher
{
argmax_matcher
{
matched_threshold
:
0
.
5
unmatched_threshold
:
0
.
5
ignore_thresholds
:
false
negatives_lower_than_unmatched
:
true
force_match_for_each_row
:
true
use_matmul_gather
:
true
}
}
similarity_calculator
{
iou_similarity
{
}
}
encode_background_as_zeros
:
true
anchor_generator
{
multiscale_anchor_generator
{
min_level
:
3
max_level
:
7
anchor_scale
:
4
.
0
aspect_ratios
: [
1
.
0
,
2
.
0
,
0
.
5
]
scales_per_octave
:
3
}
}
image_resizer
{
keep_aspect_ratio_resizer
{
min_dimension
:
768
max_dimension
:
768
pad_to_max_dimension
:
true
}
}
box_predictor
{
weight_shared_convolutional_box_predictor
{
depth
:
112
class_prediction_bias_init
: -
4
.
6
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
decay
:
0
.
99
epsilon
:
0
.
001
}
}
num_layers_before_predictor
:
3
kernel_size
:
3
use_depthwise
:
true
}
}
feature_extractor
{
type
:
'ssd_efficientnet-b2_bifpn_keras'
bifpn
{
min_level
:
3
max_level
:
7
num_iterations
:
5
num_filters
:
112
}
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
03
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
99
,
epsilon
:
0
.
001
,
}
}
}
loss
{
classification_loss
{
weighted_sigmoid_focal
{
alpha
:
0
.
25
gamma
:
1
.
5
}
}
localization_loss
{
weighted_smooth_l1
{
}
}
classification_weight
:
1
.
0
localization_weight
:
1
.
0
}
normalize_loss_by_num_matches
:
true
normalize_loc_loss_by_codesize
:
true
post_processing
{
batch_non_max_suppression
{
score_threshold
:
1
e
-
8
iou_threshold
:
0
.
5
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SIGMOID
}
}
}
train_config
: {
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/ckpt-0"
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint_type
:
"classification"
batch_size
:
128
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
use_bfloat16
:
true
num_steps
:
300000
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_scale_crop_and_pad_to_square
{
output_size
:
768
scale_min
:
0
.
1
scale_max
:
2
.
0
}
}
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
:
8
e
-
2
total_steps
:
300000
warmup_learning_rate
: .
001
warmup_steps
:
2500
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/ssd_efficientdet_d3_896x896_coco17_tpu-32.config
0 → 100644
View file @
5a2cf36f
# SSD with EfficientNet-b3 + BiFPN feature extractor,
# shared box predictor and focal loss (a.k.a EfficientDet-d3).
# See EfficientDet, Tan et al, https://arxiv.org/abs/1911.09070
# See Lin et al, https://arxiv.org/abs/1708.02002
# Trained on COCO, initialized from an EfficientNet-b3 checkpoint.
#
# Train on TPU-32
model
{
ssd
{
inplace_batchnorm_update
:
true
freeze_batchnorm
:
false
num_classes
:
90
add_background_class
:
false
box_coder
{
faster_rcnn_box_coder
{
y_scale
:
10
.
0
x_scale
:
10
.
0
height_scale
:
5
.
0
width_scale
:
5
.
0
}
}
matcher
{
argmax_matcher
{
matched_threshold
:
0
.
5
unmatched_threshold
:
0
.
5
ignore_thresholds
:
false
negatives_lower_than_unmatched
:
true
force_match_for_each_row
:
true
use_matmul_gather
:
true
}
}
similarity_calculator
{
iou_similarity
{
}
}
encode_background_as_zeros
:
true
anchor_generator
{
multiscale_anchor_generator
{
min_level
:
3
max_level
:
7
anchor_scale
:
4
.
0
aspect_ratios
: [
1
.
0
,
2
.
0
,
0
.
5
]
scales_per_octave
:
3
}
}
image_resizer
{
keep_aspect_ratio_resizer
{
min_dimension
:
896
max_dimension
:
896
pad_to_max_dimension
:
true
}
}
box_predictor
{
weight_shared_convolutional_box_predictor
{
depth
:
160
class_prediction_bias_init
: -
4
.
6
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
decay
:
0
.
99
epsilon
:
0
.
001
}
}
num_layers_before_predictor
:
4
kernel_size
:
3
use_depthwise
:
true
}
}
feature_extractor
{
type
:
'ssd_efficientnet-b3_bifpn_keras'
bifpn
{
min_level
:
3
max_level
:
7
num_iterations
:
6
num_filters
:
160
}
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
03
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
99
,
epsilon
:
0
.
001
,
}
}
}
loss
{
classification_loss
{
weighted_sigmoid_focal
{
alpha
:
0
.
25
gamma
:
1
.
5
}
}
localization_loss
{
weighted_smooth_l1
{
}
}
classification_weight
:
1
.
0
localization_weight
:
1
.
0
}
normalize_loss_by_num_matches
:
true
normalize_loc_loss_by_codesize
:
true
post_processing
{
batch_non_max_suppression
{
score_threshold
:
1
e
-
8
iou_threshold
:
0
.
5
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SIGMOID
}
}
}
train_config
: {
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/ckpt-0"
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint_type
:
"classification"
batch_size
:
128
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
use_bfloat16
:
true
num_steps
:
300000
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_scale_crop_and_pad_to_square
{
output_size
:
896
scale_min
:
0
.
1
scale_max
:
2
.
0
}
}
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
:
8
e
-
2
total_steps
:
300000
warmup_learning_rate
: .
001
warmup_steps
:
2500
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/ssd_efficientdet_d4_1024x1024_coco17_tpu-32.config
0 → 100644
View file @
5a2cf36f
# SSD with EfficientNet-b4 + BiFPN feature extractor,
# shared box predictor and focal loss (a.k.a EfficientDet-d4).
# See EfficientDet, Tan et al, https://arxiv.org/abs/1911.09070
# See Lin et al, https://arxiv.org/abs/1708.02002
# Trained on COCO, initialized from an EfficientNet-b4 checkpoint.
#
# Train on TPU-32
model
{
ssd
{
inplace_batchnorm_update
:
true
freeze_batchnorm
:
false
num_classes
:
90
add_background_class
:
false
box_coder
{
faster_rcnn_box_coder
{
y_scale
:
10
.
0
x_scale
:
10
.
0
height_scale
:
5
.
0
width_scale
:
5
.
0
}
}
matcher
{
argmax_matcher
{
matched_threshold
:
0
.
5
unmatched_threshold
:
0
.
5
ignore_thresholds
:
false
negatives_lower_than_unmatched
:
true
force_match_for_each_row
:
true
use_matmul_gather
:
true
}
}
similarity_calculator
{
iou_similarity
{
}
}
encode_background_as_zeros
:
true
anchor_generator
{
multiscale_anchor_generator
{
min_level
:
3
max_level
:
7
anchor_scale
:
4
.
0
aspect_ratios
: [
1
.
0
,
2
.
0
,
0
.
5
]
scales_per_octave
:
3
}
}
image_resizer
{
keep_aspect_ratio_resizer
{
min_dimension
:
1024
max_dimension
:
1024
pad_to_max_dimension
:
true
}
}
box_predictor
{
weight_shared_convolutional_box_predictor
{
depth
:
224
class_prediction_bias_init
: -
4
.
6
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
decay
:
0
.
99
epsilon
:
0
.
001
}
}
num_layers_before_predictor
:
4
kernel_size
:
3
use_depthwise
:
true
}
}
feature_extractor
{
type
:
'ssd_efficientnet-b4_bifpn_keras'
bifpn
{
min_level
:
3
max_level
:
7
num_iterations
:
7
num_filters
:
224
}
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
03
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
99
,
epsilon
:
0
.
001
,
}
}
}
loss
{
classification_loss
{
weighted_sigmoid_focal
{
alpha
:
0
.
25
gamma
:
1
.
5
}
}
localization_loss
{
weighted_smooth_l1
{
}
}
classification_weight
:
1
.
0
localization_weight
:
1
.
0
}
normalize_loss_by_num_matches
:
true
normalize_loc_loss_by_codesize
:
true
post_processing
{
batch_non_max_suppression
{
score_threshold
:
1
e
-
8
iou_threshold
:
0
.
5
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SIGMOID
}
}
}
train_config
: {
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/ckpt-0"
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint_type
:
"classification"
batch_size
:
128
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
use_bfloat16
:
true
num_steps
:
300000
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_scale_crop_and_pad_to_square
{
output_size
:
1024
scale_min
:
0
.
1
scale_max
:
2
.
0
}
}
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
:
8
e
-
2
total_steps
:
300000
warmup_learning_rate
: .
001
warmup_steps
:
2500
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/ssd_efficientdet_d5_1280x1280_coco17_tpu-32.config
0 → 100644
View file @
5a2cf36f
# SSD with EfficientNet-b5 + BiFPN feature extractor,
# shared box predictor and focal loss (a.k.a EfficientDet-d5).
# See EfficientDet, Tan et al, https://arxiv.org/abs/1911.09070
# See Lin et al, https://arxiv.org/abs/1708.02002
# Trained on COCO, initialized from an EfficientNet-b5 checkpoint.
#
# Train on TPU-32
model
{
ssd
{
inplace_batchnorm_update
:
true
freeze_batchnorm
:
false
num_classes
:
90
add_background_class
:
false
box_coder
{
faster_rcnn_box_coder
{
y_scale
:
10
.
0
x_scale
:
10
.
0
height_scale
:
5
.
0
width_scale
:
5
.
0
}
}
matcher
{
argmax_matcher
{
matched_threshold
:
0
.
5
unmatched_threshold
:
0
.
5
ignore_thresholds
:
false
negatives_lower_than_unmatched
:
true
force_match_for_each_row
:
true
use_matmul_gather
:
true
}
}
similarity_calculator
{
iou_similarity
{
}
}
encode_background_as_zeros
:
true
anchor_generator
{
multiscale_anchor_generator
{
min_level
:
3
max_level
:
7
anchor_scale
:
4
.
0
aspect_ratios
: [
1
.
0
,
2
.
0
,
0
.
5
]
scales_per_octave
:
3
}
}
image_resizer
{
keep_aspect_ratio_resizer
{
min_dimension
:
1280
max_dimension
:
1280
pad_to_max_dimension
:
true
}
}
box_predictor
{
weight_shared_convolutional_box_predictor
{
depth
:
288
class_prediction_bias_init
: -
4
.
6
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
decay
:
0
.
99
epsilon
:
0
.
001
}
}
num_layers_before_predictor
:
4
kernel_size
:
3
use_depthwise
:
true
}
}
feature_extractor
{
type
:
'ssd_efficientnet-b5_bifpn_keras'
bifpn
{
min_level
:
3
max_level
:
7
num_iterations
:
7
num_filters
:
288
}
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
03
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
99
,
epsilon
:
0
.
001
,
}
}
}
loss
{
classification_loss
{
weighted_sigmoid_focal
{
alpha
:
0
.
25
gamma
:
1
.
5
}
}
localization_loss
{
weighted_smooth_l1
{
}
}
classification_weight
:
1
.
0
localization_weight
:
1
.
0
}
normalize_loss_by_num_matches
:
true
normalize_loc_loss_by_codesize
:
true
post_processing
{
batch_non_max_suppression
{
score_threshold
:
1
e
-
8
iou_threshold
:
0
.
5
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SIGMOID
}
}
}
train_config
: {
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/ckpt-0"
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint_type
:
"classification"
batch_size
:
128
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
use_bfloat16
:
true
num_steps
:
300000
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_scale_crop_and_pad_to_square
{
output_size
:
1280
scale_min
:
0
.
1
scale_max
:
2
.
0
}
}
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
:
8
e
-
2
total_steps
:
300000
warmup_learning_rate
: .
001
warmup_steps
:
2500
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/ssd_efficientdet_d6_1408x1408_coco17_tpu-32.config
0 → 100644
View file @
5a2cf36f
# SSD with EfficientNet-b6 + BiFPN feature extractor,
# shared box predictor and focal loss (a.k.a EfficientDet-d6).
# See EfficientDet, Tan et al, https://arxiv.org/abs/1911.09070
# See Lin et al, https://arxiv.org/abs/1708.02002
# Trained on COCO, initialized from an EfficientNet-b6 checkpoint.
#
# Train on TPU-32
model
{
ssd
{
inplace_batchnorm_update
:
true
freeze_batchnorm
:
false
num_classes
:
90
add_background_class
:
false
box_coder
{
faster_rcnn_box_coder
{
y_scale
:
10
.
0
x_scale
:
10
.
0
height_scale
:
5
.
0
width_scale
:
5
.
0
}
}
matcher
{
argmax_matcher
{
matched_threshold
:
0
.
5
unmatched_threshold
:
0
.
5
ignore_thresholds
:
false
negatives_lower_than_unmatched
:
true
force_match_for_each_row
:
true
use_matmul_gather
:
true
}
}
similarity_calculator
{
iou_similarity
{
}
}
encode_background_as_zeros
:
true
anchor_generator
{
multiscale_anchor_generator
{
min_level
:
3
max_level
:
7
anchor_scale
:
4
.
0
aspect_ratios
: [
1
.
0
,
2
.
0
,
0
.
5
]
scales_per_octave
:
3
}
}
image_resizer
{
keep_aspect_ratio_resizer
{
min_dimension
:
1408
max_dimension
:
1408
pad_to_max_dimension
:
true
}
}
box_predictor
{
weight_shared_convolutional_box_predictor
{
depth
:
384
class_prediction_bias_init
: -
4
.
6
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
decay
:
0
.
99
epsilon
:
0
.
001
}
}
num_layers_before_predictor
:
5
kernel_size
:
3
use_depthwise
:
true
}
}
feature_extractor
{
type
:
'ssd_efficientnet-b6_bifpn_keras'
bifpn
{
min_level
:
3
max_level
:
7
num_iterations
:
8
num_filters
:
384
# Use unweighted sum for stability.
combine_method
:
'sum'
}
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
03
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
99
,
epsilon
:
0
.
001
,
}
}
}
loss
{
classification_loss
{
weighted_sigmoid_focal
{
alpha
:
0
.
25
gamma
:
1
.
5
}
}
localization_loss
{
weighted_smooth_l1
{
}
}
classification_weight
:
1
.
0
localization_weight
:
1
.
0
}
normalize_loss_by_num_matches
:
true
normalize_loc_loss_by_codesize
:
true
post_processing
{
batch_non_max_suppression
{
score_threshold
:
1
e
-
8
iou_threshold
:
0
.
5
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SIGMOID
}
}
}
train_config
: {
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/ckpt-0"
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint_type
:
"classification"
batch_size
:
128
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
use_bfloat16
:
true
num_steps
:
300000
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_scale_crop_and_pad_to_square
{
output_size
:
1408
scale_min
:
0
.
1
scale_max
:
2
.
0
}
}
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
:
8
e
-
2
total_steps
:
300000
warmup_learning_rate
: .
001
warmup_steps
:
2500
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/ssd_efficientdet_d7_1536x1536_coco17_tpu-32.config
0 → 100644
View file @
5a2cf36f
# SSD with EfficientNet-b6 + BiFPN feature extractor,
# shared box predictor and focal loss (a.k.a EfficientDet-d7).
# See EfficientDet, Tan et al, https://arxiv.org/abs/1911.09070
# See Lin et al, https://arxiv.org/abs/1708.02002
# Trained on COCO, initialized from an EfficientNet-b6 checkpoint.
#
# Train on TPU-32
model
{
ssd
{
inplace_batchnorm_update
:
true
freeze_batchnorm
:
false
num_classes
:
90
add_background_class
:
false
box_coder
{
faster_rcnn_box_coder
{
y_scale
:
10
.
0
x_scale
:
10
.
0
height_scale
:
5
.
0
width_scale
:
5
.
0
}
}
matcher
{
argmax_matcher
{
matched_threshold
:
0
.
5
unmatched_threshold
:
0
.
5
ignore_thresholds
:
false
negatives_lower_than_unmatched
:
true
force_match_for_each_row
:
true
use_matmul_gather
:
true
}
}
similarity_calculator
{
iou_similarity
{
}
}
encode_background_as_zeros
:
true
anchor_generator
{
multiscale_anchor_generator
{
min_level
:
3
max_level
:
7
anchor_scale
:
4
.
0
aspect_ratios
: [
1
.
0
,
2
.
0
,
0
.
5
]
scales_per_octave
:
3
}
}
image_resizer
{
keep_aspect_ratio_resizer
{
min_dimension
:
1536
max_dimension
:
1536
pad_to_max_dimension
:
true
}
}
box_predictor
{
weight_shared_convolutional_box_predictor
{
depth
:
384
class_prediction_bias_init
: -
4
.
6
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
decay
:
0
.
99
epsilon
:
0
.
001
}
}
num_layers_before_predictor
:
5
kernel_size
:
3
use_depthwise
:
true
}
}
feature_extractor
{
type
:
'ssd_efficientnet-b6_bifpn_keras'
bifpn
{
min_level
:
3
max_level
:
7
num_iterations
:
8
num_filters
:
384
# Use unweighted sum for stability.
combine_method
:
'sum'
}
conv_hyperparams
{
force_use_bias
:
true
activation
:
SWISH
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
03
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
99
,
epsilon
:
0
.
001
,
}
}
}
loss
{
classification_loss
{
weighted_sigmoid_focal
{
alpha
:
0
.
25
gamma
:
1
.
5
}
}
localization_loss
{
weighted_smooth_l1
{
}
}
classification_weight
:
1
.
0
localization_weight
:
1
.
0
}
normalize_loss_by_num_matches
:
true
normalize_loc_loss_by_codesize
:
true
post_processing
{
batch_non_max_suppression
{
score_threshold
:
1
e
-
8
iou_threshold
:
0
.
5
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SIGMOID
}
}
}
train_config
: {
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/ckpt-0"
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint_type
:
"classification"
batch_size
:
128
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
use_bfloat16
:
true
num_steps
:
300000
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_scale_crop_and_pad_to_square
{
output_size
:
1536
scale_min
:
0
.
1
scale_max
:
2
.
0
}
}
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
:
8
e
-
2
total_steps
:
300000
warmup_learning_rate
: .
001
warmup_steps
:
2500
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BEE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/ssd_mobilenet_v1_fpn_640x640_coco17_tpu-8.config
0 → 100644
View file @
5a2cf36f
# SSD with Mobilenet v1 FPN feature extractor, shared box predictor and focal
# loss (a.k.a Retinanet).
# See Lin et al, https://arxiv.org/abs/1708.02002
# Trained on COCO, initialized from Imagenet classification checkpoint
# Train on TPU-8
#
# Achieves 29.1 mAP on COCO17 Val
model
{
ssd
{
inplace_batchnorm_update
:
true
freeze_batchnorm
:
false
num_classes
:
90
box_coder
{
faster_rcnn_box_coder
{
y_scale
:
10
.
0
x_scale
:
10
.
0
height_scale
:
5
.
0
width_scale
:
5
.
0
}
}
matcher
{
argmax_matcher
{
matched_threshold
:
0
.
5
unmatched_threshold
:
0
.
5
ignore_thresholds
:
false
negatives_lower_than_unmatched
:
true
force_match_for_each_row
:
true
use_matmul_gather
:
true
}
}
similarity_calculator
{
iou_similarity
{
}
}
encode_background_as_zeros
:
true
anchor_generator
{
multiscale_anchor_generator
{
min_level
:
3
max_level
:
7
anchor_scale
:
4
.
0
aspect_ratios
: [
1
.
0
,
2
.
0
,
0
.
5
]
scales_per_octave
:
2
}
}
image_resizer
{
fixed_shape_resizer
{
height
:
640
width
:
640
}
}
box_predictor
{
weight_shared_convolutional_box_predictor
{
depth
:
256
class_prediction_bias_init
: -
4
.
6
conv_hyperparams
{
activation
:
RELU_6
,
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
997
,
epsilon
:
0
.
001
,
}
}
num_layers_before_predictor
:
4
kernel_size
:
3
}
}
feature_extractor
{
type
:
'ssd_mobilenet_v1_fpn_keras'
fpn
{
min_level
:
3
max_level
:
7
}
min_depth
:
16
depth_multiplier
:
1
.
0
conv_hyperparams
{
activation
:
RELU_6
,
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
997
,
epsilon
:
0
.
001
,
}
}
override_base_feature_extractor_hyperparams
:
true
}
loss
{
classification_loss
{
weighted_sigmoid_focal
{
alpha
:
0
.
25
gamma
:
2
.
0
}
}
localization_loss
{
weighted_smooth_l1
{
}
}
classification_weight
:
1
.
0
localization_weight
:
1
.
0
}
normalize_loss_by_num_matches
:
true
normalize_loc_loss_by_codesize
:
true
post_processing
{
batch_non_max_suppression
{
score_threshold
:
1
e
-
8
iou_threshold
:
0
.
6
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SIGMOID
}
}
}
train_config
: {
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/mobilenet_v1.ckpt-1"
fine_tune_checkpoint_type
:
"classification"
batch_size
:
64
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
num_steps
:
25000
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_crop_image
{
min_object_covered
:
0
.
0
min_aspect_ratio
:
0
.
75
max_aspect_ratio
:
3
.
0
min_area
:
0
.
75
max_area
:
1
.
0
overlap_thresh
:
0
.
0
}
}
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
: .
04
total_steps
:
25000
warmup_learning_rate
: .
013333
warmup_steps
:
2000
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
batch_size
:
1
;
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/ssd_mobilenet_v2_320x320_coco17_tpu-8.config
0 → 100644
View file @
5a2cf36f
# SSD with Mobilenet v2
# Trained on COCO17, initialized from Imagenet classification checkpoint
# Train on TPU-8
#
# Achieves 22.2 mAP on COCO17 Val
model
{
ssd
{
inplace_batchnorm_update
:
true
freeze_batchnorm
:
false
num_classes
:
90
box_coder
{
faster_rcnn_box_coder
{
y_scale
:
10
.
0
x_scale
:
10
.
0
height_scale
:
5
.
0
width_scale
:
5
.
0
}
}
matcher
{
argmax_matcher
{
matched_threshold
:
0
.
5
unmatched_threshold
:
0
.
5
ignore_thresholds
:
false
negatives_lower_than_unmatched
:
true
force_match_for_each_row
:
true
use_matmul_gather
:
true
}
}
similarity_calculator
{
iou_similarity
{
}
}
encode_background_as_zeros
:
true
anchor_generator
{
ssd_anchor_generator
{
num_layers
:
6
min_scale
:
0
.
2
max_scale
:
0
.
95
aspect_ratios
:
1
.
0
aspect_ratios
:
2
.
0
aspect_ratios
:
0
.
5
aspect_ratios
:
3
.
0
aspect_ratios
:
0
.
3333
}
}
image_resizer
{
fixed_shape_resizer
{
height
:
300
width
:
300
}
}
box_predictor
{
convolutional_box_predictor
{
min_depth
:
0
max_depth
:
0
num_layers_before_predictor
:
0
use_dropout
:
false
dropout_keep_probability
:
0
.
8
kernel_size
:
1
box_code_size
:
4
apply_sigmoid_to_scores
:
false
class_prediction_bias_init
: -
4
.
6
conv_hyperparams
{
activation
:
RELU_6
,
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
train
:
true
,
scale
:
true
,
center
:
true
,
decay
:
0
.
97
,
epsilon
:
0
.
001
,
}
}
}
}
feature_extractor
{
type
:
'ssd_mobilenet_v2_keras'
min_depth
:
16
depth_multiplier
:
1
.
0
conv_hyperparams
{
activation
:
RELU_6
,
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
03
mean
:
0
.
0
}
}
batch_norm
{
train
:
true
,
scale
:
true
,
center
:
true
,
decay
:
0
.
97
,
epsilon
:
0
.
001
,
}
}
override_base_feature_extractor_hyperparams
:
true
}
loss
{
classification_loss
{
weighted_sigmoid_focal
{
alpha
:
0
.
75
,
gamma
:
2
.
0
}
}
localization_loss
{
weighted_smooth_l1
{
delta
:
1
.
0
}
}
classification_weight
:
1
.
0
localization_weight
:
1
.
0
}
normalize_loss_by_num_matches
:
true
normalize_loc_loss_by_codesize
:
true
post_processing
{
batch_non_max_suppression
{
score_threshold
:
1
e
-
8
iou_threshold
:
0
.
6
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SIGMOID
}
}
}
train_config
: {
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/mobilenet_v2.ckpt-1"
fine_tune_checkpoint_type
:
"classification"
batch_size
:
512
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
num_steps
:
50000
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
ssd_random_crop
{
}
}
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
: .
8
total_steps
:
50000
warmup_learning_rate
:
0
.
13333
warmup_steps
:
2000
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8.config
0 → 100644
View file @
5a2cf36f
# SSD with Mobilenet v2 FPN-lite (go/fpn-lite) feature extractor, shared box
# predictor and focal loss (a mobile version of Retinanet).
# Retinanet: see Lin et al, https://arxiv.org/abs/1708.02002
# Trained on COCO, initialized from Imagenet classification checkpoint
# Train on TPU-8
#
# Achieves 22.2 mAP on COCO17 Val
model
{
ssd
{
inplace_batchnorm_update
:
true
freeze_batchnorm
:
false
num_classes
:
90
box_coder
{
faster_rcnn_box_coder
{
y_scale
:
10
.
0
x_scale
:
10
.
0
height_scale
:
5
.
0
width_scale
:
5
.
0
}
}
matcher
{
argmax_matcher
{
matched_threshold
:
0
.
5
unmatched_threshold
:
0
.
5
ignore_thresholds
:
false
negatives_lower_than_unmatched
:
true
force_match_for_each_row
:
true
use_matmul_gather
:
true
}
}
similarity_calculator
{
iou_similarity
{
}
}
encode_background_as_zeros
:
true
anchor_generator
{
multiscale_anchor_generator
{
min_level
:
3
max_level
:
7
anchor_scale
:
4
.
0
aspect_ratios
: [
1
.
0
,
2
.
0
,
0
.
5
]
scales_per_octave
:
2
}
}
image_resizer
{
fixed_shape_resizer
{
height
:
320
width
:
320
}
}
box_predictor
{
weight_shared_convolutional_box_predictor
{
depth
:
128
class_prediction_bias_init
: -
4
.
6
conv_hyperparams
{
activation
:
RELU_6
,
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
997
,
epsilon
:
0
.
001
,
}
}
num_layers_before_predictor
:
4
share_prediction_tower
:
true
use_depthwise
:
true
kernel_size
:
3
}
}
feature_extractor
{
type
:
'ssd_mobilenet_v2_fpn_keras'
use_depthwise
:
true
fpn
{
min_level
:
3
max_level
:
7
additional_layer_depth
:
128
}
min_depth
:
16
depth_multiplier
:
1
.
0
conv_hyperparams
{
activation
:
RELU_6
,
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
997
,
epsilon
:
0
.
001
,
}
}
override_base_feature_extractor_hyperparams
:
true
}
loss
{
classification_loss
{
weighted_sigmoid_focal
{
alpha
:
0
.
25
gamma
:
2
.
0
}
}
localization_loss
{
weighted_smooth_l1
{
}
}
classification_weight
:
1
.
0
localization_weight
:
1
.
0
}
normalize_loss_by_num_matches
:
true
normalize_loc_loss_by_codesize
:
true
post_processing
{
batch_non_max_suppression
{
score_threshold
:
1
e
-
8
iou_threshold
:
0
.
6
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SIGMOID
}
}
}
train_config
: {
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/mobilenet_v2.ckpt-1"
fine_tune_checkpoint_type
:
"classification"
batch_size
:
128
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
num_steps
:
50000
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_crop_image
{
min_object_covered
:
0
.
0
min_aspect_ratio
:
0
.
75
max_aspect_ratio
:
3
.
0
min_area
:
0
.
75
max_area
:
1
.
0
overlap_thresh
:
0
.
0
}
}
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
: .
08
total_steps
:
50000
warmup_learning_rate
: .
026666
warmup_steps
:
1000
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/ssd_mobilenet_v2_fpnlite_640x640_coco17_tpu-8.config
0 → 100644
View file @
5a2cf36f
# SSD with Mobilenet v2 FPN-lite (go/fpn-lite) feature extractor, shared box
# predictor and focal loss (a mobile version of Retinanet).
# Retinanet: see Lin et al, https://arxiv.org/abs/1708.02002
# Trained on COCO, initialized from Imagenet classification checkpoint
# Train on TPU-8
#
# Achieves 28.2 mAP on COCO17 Val
model
{
ssd
{
inplace_batchnorm_update
:
true
freeze_batchnorm
:
false
num_classes
:
90
box_coder
{
faster_rcnn_box_coder
{
y_scale
:
10
.
0
x_scale
:
10
.
0
height_scale
:
5
.
0
width_scale
:
5
.
0
}
}
matcher
{
argmax_matcher
{
matched_threshold
:
0
.
5
unmatched_threshold
:
0
.
5
ignore_thresholds
:
false
negatives_lower_than_unmatched
:
true
force_match_for_each_row
:
true
use_matmul_gather
:
true
}
}
similarity_calculator
{
iou_similarity
{
}
}
encode_background_as_zeros
:
true
anchor_generator
{
multiscale_anchor_generator
{
min_level
:
3
max_level
:
7
anchor_scale
:
4
.
0
aspect_ratios
: [
1
.
0
,
2
.
0
,
0
.
5
]
scales_per_octave
:
2
}
}
image_resizer
{
fixed_shape_resizer
{
height
:
640
width
:
640
}
}
box_predictor
{
weight_shared_convolutional_box_predictor
{
depth
:
128
class_prediction_bias_init
: -
4
.
6
conv_hyperparams
{
activation
:
RELU_6
,
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
997
,
epsilon
:
0
.
001
,
}
}
num_layers_before_predictor
:
4
share_prediction_tower
:
true
use_depthwise
:
true
kernel_size
:
3
}
}
feature_extractor
{
type
:
'ssd_mobilenet_v2_fpn_keras'
use_depthwise
:
true
fpn
{
min_level
:
3
max_level
:
7
additional_layer_depth
:
128
}
min_depth
:
16
depth_multiplier
:
1
.
0
conv_hyperparams
{
activation
:
RELU_6
,
regularizer
{
l2_regularizer
{
weight
:
0
.
00004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
997
,
epsilon
:
0
.
001
,
}
}
override_base_feature_extractor_hyperparams
:
true
}
loss
{
classification_loss
{
weighted_sigmoid_focal
{
alpha
:
0
.
25
gamma
:
2
.
0
}
}
localization_loss
{
weighted_smooth_l1
{
}
}
classification_weight
:
1
.
0
localization_weight
:
1
.
0
}
normalize_loss_by_num_matches
:
true
normalize_loc_loss_by_codesize
:
true
post_processing
{
batch_non_max_suppression
{
score_threshold
:
1
e
-
8
iou_threshold
:
0
.
6
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SIGMOID
}
}
}
train_config
: {
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/mobilenet_v2.ckpt-1"
fine_tune_checkpoint_type
:
"classification"
batch_size
:
128
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
num_steps
:
50000
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_crop_image
{
min_object_covered
:
0
.
0
min_aspect_ratio
:
0
.
75
max_aspect_ratio
:
3
.
0
min_area
:
0
.
75
max_area
:
1
.
0
overlap_thresh
:
0
.
0
}
}
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
: .
08
total_steps
:
50000
warmup_learning_rate
: .
026666
warmup_steps
:
1000
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
research/object_detection/configs/tf2/ssd_resnet101_v1_fpn_1024x1024_coco17_tpu-8.config
0 → 100644
View file @
5a2cf36f
# SSD with Resnet 101 v1 FPN feature extractor, shared box predictor and focal
# loss (a.k.a Retinanet).
# See Lin et al, https://arxiv.org/abs/1708.02002
# Trained on COCO, initialized from Imagenet classification checkpoint
# Train on TPU-8
#
# Achieves 39.5 mAP on COCO17 Val
model
{
ssd
{
inplace_batchnorm_update
:
true
freeze_batchnorm
:
false
num_classes
:
90
box_coder
{
faster_rcnn_box_coder
{
y_scale
:
10
.
0
x_scale
:
10
.
0
height_scale
:
5
.
0
width_scale
:
5
.
0
}
}
matcher
{
argmax_matcher
{
matched_threshold
:
0
.
5
unmatched_threshold
:
0
.
5
ignore_thresholds
:
false
negatives_lower_than_unmatched
:
true
force_match_for_each_row
:
true
use_matmul_gather
:
true
}
}
similarity_calculator
{
iou_similarity
{
}
}
encode_background_as_zeros
:
true
anchor_generator
{
multiscale_anchor_generator
{
min_level
:
3
max_level
:
7
anchor_scale
:
4
.
0
aspect_ratios
: [
1
.
0
,
2
.
0
,
0
.
5
]
scales_per_octave
:
2
}
}
image_resizer
{
fixed_shape_resizer
{
height
:
1024
width
:
1024
}
}
box_predictor
{
weight_shared_convolutional_box_predictor
{
depth
:
256
class_prediction_bias_init
: -
4
.
6
conv_hyperparams
{
activation
:
RELU_6
,
regularizer
{
l2_regularizer
{
weight
:
0
.
0004
}
}
initializer
{
random_normal_initializer
{
stddev
:
0
.
01
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
997
,
epsilon
:
0
.
001
,
}
}
num_layers_before_predictor
:
4
kernel_size
:
3
}
}
feature_extractor
{
type
:
'ssd_resnet101_v1_fpn_keras'
fpn
{
min_level
:
3
max_level
:
7
}
min_depth
:
16
depth_multiplier
:
1
.
0
conv_hyperparams
{
activation
:
RELU_6
,
regularizer
{
l2_regularizer
{
weight
:
0
.
0004
}
}
initializer
{
truncated_normal_initializer
{
stddev
:
0
.
03
mean
:
0
.
0
}
}
batch_norm
{
scale
:
true
,
decay
:
0
.
997
,
epsilon
:
0
.
001
,
}
}
override_base_feature_extractor_hyperparams
:
true
}
loss
{
classification_loss
{
weighted_sigmoid_focal
{
alpha
:
0
.
25
gamma
:
2
.
0
}
}
localization_loss
{
weighted_smooth_l1
{
}
}
classification_weight
:
1
.
0
localization_weight
:
1
.
0
}
normalize_loss_by_num_matches
:
true
normalize_loc_loss_by_codesize
:
true
post_processing
{
batch_non_max_suppression
{
score_threshold
:
1
e
-
8
iou_threshold
:
0
.
6
max_detections_per_class
:
100
max_total_detections
:
100
}
score_converter
:
SIGMOID
}
}
}
train_config
: {
fine_tune_checkpoint_version
:
V2
fine_tune_checkpoint
:
"PATH_TO_BE_CONFIGURED/resnet101.ckpt-1"
fine_tune_checkpoint_type
:
"classification"
batch_size
:
64
sync_replicas
:
true
startup_delay_steps
:
0
replicas_to_aggregate
:
8
use_bfloat16
:
true
num_steps
:
100000
data_augmentation_options
{
random_horizontal_flip
{
}
}
data_augmentation_options
{
random_crop_image
{
min_object_covered
:
0
.
0
min_aspect_ratio
:
0
.
75
max_aspect_ratio
:
3
.
0
min_area
:
0
.
75
max_area
:
1
.
0
overlap_thresh
:
0
.
0
}
}
optimizer
{
momentum_optimizer
: {
learning_rate
: {
cosine_decay_learning_rate
{
learning_rate_base
: .
04
total_steps
:
100000
warmup_learning_rate
: .
013333
warmup_steps
:
2000
}
}
momentum_optimizer_value
:
0
.
9
}
use_moving_average
:
false
}
max_number_of_boxes
:
100
unpad_groundtruth_tensors
:
false
}
train_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
}
}
eval_config
: {
metrics_set
:
"coco_detection_metrics"
use_moving_averages
:
false
}
eval_input_reader
: {
label_map_path
:
"PATH_TO_BE_CONFIGURED/label_map.txt"
shuffle
:
false
num_epochs
:
1
tf_record_input_reader
{
input_path
:
"PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
}
}
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