Unverified Commit 5245161c authored by vivek rathod's avatar vivek rathod Committed by GitHub
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Merged commit includes the following changes: (#8830)



320622111  by rathodv:

    Internal Change.

--

PiperOrigin-RevId: 320622111
Co-authored-by: default avatarTF Object Detection Team <no-reply@google.com>
parent c9eb3554
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# CenterNet meta-architecture from the "Objects as Points" [2] paper with the
# hourglass[1] backbone.
# [1]: https://arxiv.org/abs/1603.06937
# [2]: https://arxiv.org/abs/1904.07850
# Trained on COCO, initialized from Extremenet Detection checkpoint
# Train on TPU-32 v3
#
# Achieves 44.6 mAP on COCO17 Val
model {
center_net {
num_classes: 90
feature_extractor {
type: "hourglass_104"
bgr_ordering: true
channel_means: [104.01362025, 114.03422265, 119.9165958 ]
channel_stds: [73.6027665 , 69.89082075, 70.9150767 ]
}
image_resizer {
keep_aspect_ratio_resizer {
min_dimension: 1024
max_dimension: 1024
pad_to_max_dimension: true
}
}
object_detection_task {
task_loss_weight: 1.0
offset_loss_weight: 1.0
scale_loss_weight: 0.1
localization_loss {
l1_localization_loss {
}
}
}
object_center_params {
object_center_loss_weight: 1.0
min_box_overlap_iou: 0.7
max_box_predictions: 100
classification_loss {
penalty_reduced_logistic_focal_loss {
alpha: 2.0
beta: 4.0
}
}
}
}
}
train_config: {
batch_size: 128
num_steps: 50000
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_adjust_brightness {
}
}
data_augmentation_options {
random_square_crop_by_scale {
scale_min: 0.6
scale_max: 1.3
}
}
optimizer {
adam_optimizer: {
epsilon: 1e-7 # Match tf.keras.optimizers.Adam's default.
learning_rate: {
cosine_decay_learning_rate {
learning_rate_base: 1e-3
total_steps: 50000
warmup_learning_rate: 2.5e-4
warmup_steps: 5000
}
}
}
use_moving_average: false
}
max_number_of_boxes: 100
unpad_groundtruth_tensors: false
fine_tune_checkpoint_version: V2
fine_tune_checkpoint: "PATH_TO_BE_CONFIGURED/ckpt-1"
fine_tune_checkpoint_type: "detection"
}
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"
}
}
# CenterNet meta-architecture from the "Objects as Points" [2] paper with the
# hourglass[1] backbone.
# [1]: https://arxiv.org/abs/1603.06937
# [2]: https://arxiv.org/abs/1904.07850
# Trained on COCO, initialized from Extremenet Detection checkpoint
# Train on TPU-8
#
# Achieves 41.9 mAP on COCO17 Val
model {
center_net {
num_classes: 90
feature_extractor {
type: "hourglass_104"
bgr_ordering: true
channel_means: [104.01362025, 114.03422265, 119.9165958 ]
channel_stds: [73.6027665 , 69.89082075, 70.9150767 ]
}
image_resizer {
keep_aspect_ratio_resizer {
min_dimension: 512
max_dimension: 512
pad_to_max_dimension: true
}
}
object_detection_task {
task_loss_weight: 1.0
offset_loss_weight: 1.0
scale_loss_weight: 0.1
localization_loss {
l1_localization_loss {
}
}
}
object_center_params {
object_center_loss_weight: 1.0
min_box_overlap_iou: 0.7
max_box_predictions: 100
classification_loss {
penalty_reduced_logistic_focal_loss {
alpha: 2.0
beta: 4.0
}
}
}
}
}
train_config: {
batch_size: 128
num_steps: 140000
data_augmentation_options {
random_horizontal_flip {
}
}
data_augmentation_options {
random_crop_image {
min_aspect_ratio: 0.5
max_aspect_ratio: 1.7
random_coef: 0.25
}
}
data_augmentation_options {
random_adjust_hue {
}
}
data_augmentation_options {
random_adjust_contrast {
}
}
data_augmentation_options {
random_adjust_saturation {
}
}
data_augmentation_options {
random_adjust_brightness {
}
}
data_augmentation_options {
random_absolute_pad_image {
max_height_padding: 200
max_width_padding: 200
pad_color: [0, 0, 0]
}
}
optimizer {
adam_optimizer: {
epsilon: 1e-7 # Match tf.keras.optimizers.Adam's default.
learning_rate: {
manual_step_learning_rate {
initial_learning_rate: 1e-3
schedule {
step: 90000
learning_rate: 1e-4
}
schedule {
step: 120000
learning_rate: 1e-5
}
}
}
}
use_moving_average: false
}
max_number_of_boxes: 100
unpad_groundtruth_tensors: false
fine_tune_checkpoint_version: V2
fine_tune_checkpoint: "PATH_TO_BE_CONFIGURED/ckpt-1"
fine_tune_checkpoint_type: "detection"
}
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"
}
}
# CenterNet meta-architecture from the "Objects as Points" [1] paper
# with the ResNet-v1-101 FPN backbone.
# [1]: https://arxiv.org/abs/1904.07850
# Train on TPU-8
#
# Achieves 34.18 mAP on COCO17 Val
model {
center_net {
num_classes: 90
feature_extractor {
type: "resnet_v2_101"
}
image_resizer {
keep_aspect_ratio_resizer {
min_dimension: 512
max_dimension: 512
pad_to_max_dimension: true
}
}
object_detection_task {
task_loss_weight: 1.0
offset_loss_weight: 1.0
scale_loss_weight: 0.1
localization_loss {
l1_localization_loss {
}
}
}
object_center_params {
object_center_loss_weight: 1.0
min_box_overlap_iou: 0.7
max_box_predictions: 100
classification_loss {
penalty_reduced_logistic_focal_loss {
alpha: 2.0
beta: 4.0
}
}
}
}
}
train_config: {
batch_size: 128
num_steps: 140000
data_augmentation_options {
random_horizontal_flip {
}
}
data_augmentation_options {
random_crop_image {
min_aspect_ratio: 0.5
max_aspect_ratio: 1.7
random_coef: 0.25
}
}
data_augmentation_options {
random_adjust_hue {
}
}
data_augmentation_options {
random_adjust_contrast {
}
}
data_augmentation_options {
random_adjust_saturation {
}
}
data_augmentation_options {
random_adjust_brightness {
}
}
data_augmentation_options {
random_absolute_pad_image {
max_height_padding: 200
max_width_padding: 200
pad_color: [0, 0, 0]
}
}
optimizer {
adam_optimizer: {
epsilon: 1e-7 # Match tf.keras.optimizers.Adam's default.
learning_rate: {
manual_step_learning_rate {
initial_learning_rate: 1e-3
schedule {
step: 90000
learning_rate: 1e-4
}
schedule {
step: 120000
learning_rate: 1e-5
}
}
}
}
use_moving_average: false
}
max_number_of_boxes: 100
unpad_groundtruth_tensors: false
fine_tune_checkpoint_version: V2
fine_tune_checkpoint: "PATH_TO_BE_CONFIGURED/weights-1"
fine_tune_checkpoint_type: "classification"
}
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"
}
}
# Faster R-CNN with Resnet-101 (v1),
# w/high res inputs, long training schedule
# Trained on COCO, initialized from Imagenet classification checkpoint
#
# Train on TPU-8
#
# Achieves 37.1 mAP on COCO17 val
model {
faster_rcnn {
num_classes: 90
image_resizer {
fixed_shape_resizer {
width: 1024
height: 1024
}
}
feature_extractor {
type: 'faster_rcnn_resnet101_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/resnet101.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"
}
}
# Faster R-CNN with Resnet-50 (v1)
# Trained on COCO, initialized from Imagenet classification checkpoint
#
# Train on TPU-8
#
# Achieves 31.8 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_resnet101_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/resnet101.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"
}
}
# Faster R-CNN with Resnet-101 (v1),
# Initialized from Imagenet classification checkpoint
#
# Train on GPU-8
#
# Achieves 36.6 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_resnet101_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/resnet101.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"
}
}
# 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: 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: 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"
}
}
# 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"
}
}
# 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"
}
}
# 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"
}
}
# 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"
}
}
# 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"
}
}
# 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
}
# 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: 1e-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: 8e-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"
}
}
# 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: 1e-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: 8e-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"
}
}
# 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: 1e-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: 8e-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"
}
}
# 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: 1e-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: 8e-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"
}
}
# 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: 1e-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: 8e-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"
}
}
# 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: 1e-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: 8e-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"
}
}
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