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ModelZoo
ResNet50_tensorflow
Commits
9e1eaad6
Commit
9e1eaad6
authored
Oct 01, 2021
by
Vishnu Banna
Browse files
yolo cfg
parent
dd921792
Changes
5
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official/vision/beta/projects/yolo/configs/experiments/yolov3/inference/512.yaml
...ojects/yolo/configs/experiments/yolov3/inference/512.yaml
+0
-138
official/vision/beta/projects/yolo/configs/experiments/yolov3/tpu/512.yaml
...eta/projects/yolo/configs/experiments/yolov3/tpu/512.yaml
+0
-136
official/vision/beta/projects/yolo/configs/experiments/yolov4-csp/inference/640.yaml
...ts/yolo/configs/experiments/yolov4-csp/inference/640.yaml
+0
-76
official/vision/beta/projects/yolo/configs/experiments/yolov4/inference/512.yaml
...ojects/yolo/configs/experiments/yolov4/inference/512.yaml
+0
-129
official/vision/beta/projects/yolo/configs/experiments/yolov4/tpu/512.yaml
...eta/projects/yolo/configs/experiments/yolov4/tpu/512.yaml
+0
-137
No files found.
official/vision/beta/projects/yolo/configs/experiments/yolov3/inference/512.yaml
deleted
100755 → 0
View file @
dd921792
runtime
:
distribution_strategy
:
'
mirrored'
mixed_precision_dtype
:
'
float16'
num_gpus
:
1
task
:
smart_bias_lr
:
0.0
model
:
darknet_based_model
:
True
input_size
:
[
512
,
512
,
3
]
backbone
:
type
:
'
darknet'
darknet
:
model_id
:
'
darknet53'
max_level
:
5
min_level
:
3
decoder
:
type
:
yolo_decoder
yolo_decoder
:
version
:
v3
type
:
regular
head
:
smart_bias
:
true
detection_generator
:
box_type
:
'
all'
:
original
scale_xy
:
'
5'
:
1.05
'
4'
:
1.1
'
3'
:
1.2
max_boxes
:
200
nms_type
:
greedy
iou_thresh
:
0.25
nms_thresh
:
0.45
pre_nms_points
:
500
loss
:
use_scaled_loss
:
False
box_loss_type
:
'
all'
:
ciou
ignore_thresh
:
'
all'
:
0.7
iou_normalizer
:
'
all'
:
0.07
cls_normalizer
:
'
all'
:
1.0
obj_normalizer
:
'
all'
:
1.0
objectness_smooth
:
'
all'
:
0.0
max_delta
:
'
all'
:
5.0
norm_activation
:
activation
:
leaky
norm_epsilon
:
0.0001
norm_momentum
:
0.99
use_sync_bn
:
true
num_classes
:
80
anchor_boxes
:
anchors_per_scale
:
3
boxes
:
[
box
:
[
12
,
16
],
box
:
[
19
,
36
],
box
:
[
40
,
28
],
box
:
[
36
,
75
],
box
:
[
76
,
55
],
box
:
[
72
,
146
],
box
:
[
142
,
110
],
box
:
[
192
,
243
],
box
:
[
459
,
401
]]
train_data
:
global_batch_size
:
64
dtype
:
float32
input_path
:
'
gs://cam2-datasets/coco/train*'
is_training
:
true
drop_remainder
:
true
seed
:
1000
parser
:
mosaic
:
mosaic_frequency
:
0.75
mixup_frequency
:
0.0
mosaic_crop_mode
:
'
crop'
mosaic_center
:
0.2
aug_scale_min
:
0.2
aug_scale_max
:
1.6
jitter
:
0.3
max_num_instances
:
200
letter_box
:
False
random_flip
:
True
aug_rand_saturation
:
1.5
aug_rand_brightness
:
1.5
aug_rand_hue
:
0.1
aug_scale_min
:
0.1
aug_scale_max
:
1.9
aug_rand_translate
:
0.0
jitter
:
0.3
area_thresh
:
0.1
random_pad
:
True
use_tie_breaker
:
True
anchor_thresh
:
0.213
validation_data
:
global_batch_size
:
8
dtype
:
float32
input_path
:
'
gs://cam2-datasets/coco/val*'
is_training
:
false
drop_remainder
:
true
parser
:
max_num_instances
:
200
letter_box
:
False
use_tie_breaker
:
True
anchor_thresh
:
0.213
weight_decay
:
0.000
init_checkpoint
:
'
gs://tensorflow2/darknet/cspdarknet53-golden'
init_checkpoint_modules
:
'
backbone'
annotation_file
:
null
trainer
:
train_steps
:
500500
# 160 epochs at 64 batchsize -> 500500 * 64/2
validation_steps
:
625
steps_per_loop
:
1850
summary_interval
:
1850
validation_interval
:
9250
checkpoint_interval
:
1850
optimizer_config
:
ema
:
average_decay
:
0.9998
trainable_weights_only
:
False
dynamic_decay
:
True
learning_rate
:
type
:
stepwise
stepwise
:
boundaries
:
[
400000
,
450000
]
name
:
PiecewiseConstantDecay
values
:
[
0.00131
,
0.000131
,
0.0000131
]
optimizer
:
type
:
sgd_torch
sgd_torch
:
momentum
:
0.949
momentum_start
:
0.949
nesterov
:
True
warmup_steps
:
1000
weight_decay
:
0.0005
sim_torch
:
true
name
:
SGD
warmup
:
type
:
'
linear'
linear
:
warmup_steps
:
1000
#learning rate rises from 0 to 0.0013 over 1000 steps
official/vision/beta/projects/yolo/configs/experiments/yolov3/tpu/512.yaml
deleted
100755 → 0
View file @
dd921792
runtime
:
distribution_strategy
:
'
tpu'
mixed_precision_dtype
:
'
bfloat16'
task
:
smart_bias_lr
:
0.0
model
:
darknet_based_model
:
True
input_size
:
[
512
,
512
,
3
]
backbone
:
type
:
'
darknet'
darknet
:
model_id
:
'
darknet53'
max_level
:
5
min_level
:
3
decoder
:
type
:
yolo_decoder
yolo_decoder
:
version
:
v3
type
:
regular
head
:
smart_bias
:
true
detection_generator
:
box_type
:
'
all'
:
original
scale_xy
:
'
5'
:
1.05
'
4'
:
1.1
'
3'
:
1.2
max_boxes
:
200
nms_type
:
greedy
iou_thresh
:
0.001
nms_thresh
:
0.60
loss
:
use_scaled_loss
:
False
box_loss_type
:
'
all'
:
ciou
ignore_thresh
:
'
all'
:
0.7
iou_normalizer
:
'
all'
:
0.07
cls_normalizer
:
'
all'
:
1.0
obj_normalizer
:
'
all'
:
1.0
objectness_smooth
:
'
all'
:
0.0
max_delta
:
'
all'
:
5.0
norm_activation
:
activation
:
leaky
norm_epsilon
:
0.0001
norm_momentum
:
0.99
use_sync_bn
:
true
num_classes
:
80
anchor_boxes
:
anchors_per_scale
:
3
boxes
:
[
box
:
[
12
,
16
],
box
:
[
19
,
36
],
box
:
[
40
,
28
],
box
:
[
36
,
75
],
box
:
[
76
,
55
],
box
:
[
72
,
146
],
box
:
[
142
,
110
],
box
:
[
192
,
243
],
box
:
[
459
,
401
]]
train_data
:
global_batch_size
:
64
dtype
:
float32
input_path
:
'
gs://cam2-datasets/coco/train*'
is_training
:
true
drop_remainder
:
true
seed
:
1000
parser
:
mosaic
:
mosaic_frequency
:
0.75
mixup_frequency
:
0.0
mosaic_crop_mode
:
'
crop'
mosaic_center
:
0.2
aug_scale_min
:
0.2
aug_scale_max
:
1.6
jitter
:
0.3
max_num_instances
:
200
letter_box
:
False
random_flip
:
True
aug_rand_saturation
:
1.5
aug_rand_brightness
:
1.5
aug_rand_hue
:
0.1
aug_scale_min
:
0.1
aug_scale_max
:
1.9
aug_rand_translate
:
0.0
jitter
:
0.3
area_thresh
:
0.1
random_pad
:
True
use_tie_breaker
:
True
anchor_thresh
:
0.213
validation_data
:
global_batch_size
:
8
dtype
:
float32
input_path
:
'
gs://cam2-datasets/coco/val*'
is_training
:
false
drop_remainder
:
true
parser
:
max_num_instances
:
200
letter_box
:
False
use_tie_breaker
:
True
anchor_thresh
:
0.213
weight_decay
:
0.000
init_checkpoint
:
'
gs://tensorflow2/darknet/cspdarknet53-golden'
init_checkpoint_modules
:
'
backbone'
annotation_file
:
null
trainer
:
train_steps
:
500500
# 160 epochs at 64 batchsize -> 500500 * 64/2
validation_steps
:
625
steps_per_loop
:
1850
summary_interval
:
1850
validation_interval
:
9250
checkpoint_interval
:
1850
optimizer_config
:
ema
:
average_decay
:
0.9998
trainable_weights_only
:
False
dynamic_decay
:
True
learning_rate
:
type
:
stepwise
stepwise
:
boundaries
:
[
400000
,
450000
]
name
:
PiecewiseConstantDecay
values
:
[
0.00131
,
0.000131
,
0.0000131
]
optimizer
:
type
:
sgd_torch
sgd_torch
:
momentum
:
0.949
momentum_start
:
0.949
nesterov
:
True
warmup_steps
:
1000
weight_decay
:
0.0005
sim_torch
:
true
name
:
SGD
warmup
:
type
:
'
linear'
linear
:
warmup_steps
:
1000
#learning rate rises from 0 to 0.0013 over 1000 steps
official/vision/beta/projects/yolo/configs/experiments/yolov4-csp/inference/640.yaml
deleted
100644 → 0
View file @
dd921792
runtime
:
distribution_strategy
:
'
mirrored'
mixed_precision_dtype
:
'
float16'
num_gpus
:
1
task
:
smart_bias_lr
:
0.1
model
:
darknet_based_model
:
False
input_size
:
[
640
,
640
,
3
]
backbone
:
type
:
'
darknet'
darknet
:
model_id
:
'
altered_cspdarknet53'
max_level
:
5
min_level
:
3
decoder
:
type
:
yolo_decoder
yolo_decoder
:
version
:
v4
type
:
csp
head
:
smart_bias
:
true
detection_generator
:
box_type
:
'
all'
:
scaled
scale_xy
:
'
all'
:
2.0
max_boxes
:
300
nms_type
:
greedy
# iou_thresh: 0.25
# nms_thresh: 0.45
iou_thresh
:
0.001
nms_thresh
:
0.60
pre_nms_points
:
5000
loss
:
use_scaled_loss
:
true
update_on_repeat
:
true
box_loss_type
:
'
all'
:
ciou
ignore_thresh
:
'
all'
:
0.7
iou_normalizer
:
'
all'
:
0.05
cls_normalizer
:
'
all'
:
0.3
obj_normalizer
:
'
5'
:
0.28
'
4'
:
0.70
'
3'
:
2.80
objectness_smooth
:
'
all'
:
1.0
num_classes
:
80
anchor_boxes
:
anchors_per_scale
:
3
boxes
:
[
box
:
[
12
,
16
],
box
:
[
19
,
36
],
box
:
[
40
,
28
],
box
:
[
36
,
75
],
box
:
[
76
,
55
],
box
:
[
72
,
146
],
box
:
[
142
,
110
],
box
:
[
192
,
243
],
box
:
[
459
,
401
]]
train_data
:
global_batch_size
:
1
input_path
:
'
/media/vbanna/DATA_SHARE/CV/datasets/COCO_raw/records/train*'
shuffle_buffer_size
:
10000
parser
:
mosaic
:
mosaic_frequency
:
1.0
mixup_frequency
:
0.0
mosaic_crop_mode
:
'
scale'
mosaic_center
:
0.25
aug_scale_min
:
0.1
aug_scale_max
:
1.9
letter_box
:
True
random_flip
:
True
aug_rand_translate
:
0.1
area_thresh
:
0.1
validation_data
:
global_batch_size
:
8
input_path
:
'
/media/vbanna/DATA_SHARE/CV/datasets/COCO_raw/records/val*'
\ No newline at end of file
official/vision/beta/projects/yolo/configs/experiments/yolov4/inference/512.yaml
deleted
100755 → 0
View file @
dd921792
runtime
:
distribution_strategy
:
'
mirrored'
mixed_precision_dtype
:
'
float16'
num_gpus
:
1
task
:
smart_bias_lr
:
0.0
model
:
darknet_based_model
:
True
input_size
:
[
512
,
512
,
3
]
backbone
:
type
:
'
darknet'
darknet
:
model_id
:
'
cspdarknet53'
max_level
:
5
min_level
:
3
decoder
:
type
:
yolo_decoder
yolo_decoder
:
version
:
v4
type
:
regular
activation
:
leaky
head
:
smart_bias
:
true
detection_generator
:
box_type
:
'
all'
:
original
scale_xy
:
'
5'
:
1.05
'
4'
:
1.1
'
3'
:
1.2
max_boxes
:
200
nms_type
:
greedy
iou_thresh
:
0.25
nms_thresh
:
0.45
pre_nms_points
:
500
loss
:
use_scaled_loss
:
False
box_loss_type
:
'
all'
:
ciou
ignore_thresh
:
'
all'
:
0.7
iou_normalizer
:
'
all'
:
0.07
cls_normalizer
:
'
all'
:
1.0
obj_normalizer
:
'
all'
:
1.0
objectness_smooth
:
'
all'
:
0.0
max_delta
:
'
all'
:
5.0
norm_activation
:
activation
:
mish
norm_epsilon
:
0.0001
norm_momentum
:
0.99
use_sync_bn
:
true
num_classes
:
80
anchor_boxes
:
anchors_per_scale
:
3
boxes
:
[
box
:
[
12
,
16
],
box
:
[
19
,
36
],
box
:
[
40
,
28
],
box
:
[
36
,
75
],
box
:
[
76
,
55
],
box
:
[
72
,
146
],
box
:
[
142
,
110
],
box
:
[
192
,
243
],
box
:
[
459
,
401
]]
train_data
:
# global_batch_size: 64
# dtype: float32
input_path
:
'
/media/vbanna/DATA_SHARE/CV/datasets/COCO_raw/records/train*'
# is_training: true
# drop_remainder: true
# seed: 1000
parser
:
mosaic
:
mosaic_frequency
:
1.0
mixup_frequency
:
0.0
mosaic_crop_mode
:
'
scale'
mosaic_center
:
0.25
aug_scale_min
:
0.1
aug_scale_max
:
1.9
max_num_instances
:
200
letter_box
:
True
random_flip
:
True
aug_rand_translate
:
0.1
random_pad
:
False
validation_data
:
# global_batch_size: 1
# dtype: float32
input_path
:
'
/media/vbanna/DATA_SHARE/CV/datasets/COCO_raw/records/val*'
# is_training: false
# drop_remainder: true
# parser:
# max_num_instances: 200
# letter_box: True
# use_tie_breaker: True
# anchor_thresh: 0.213
# weight_decay: 0.000
# init_checkpoint: '../checkpoints/512-wd-baseline-e1'
# init_checkpoint_modules: 'all'
# annotation_file: null
# trainer:
# train_steps: 500500 # 160 epochs at 64 batchsize -> 500500 * 64/2
# validation_steps: 625
# steps_per_loop: 1850
# summary_interval: 1850
# validation_interval: 9250
# checkpoint_interval: 1850
# optimizer_config:
# ema:
# average_decay: 0.9998
# trainable_weights_only: False
# dynamic_decay: True
# learning_rate:
# type: stepwise
# stepwise:
# boundaries: [400000, 450000]
# name: PiecewiseConstantDecay
# values: [0.00131, 0.000131, 0.0000131]
# optimizer:
# type: sgd_torch
# sgd_torch:
# momentum: 0.949
# momentum_start: 0.949
# nesterov: True
# warmup_steps: 1000
# weight_decay: 0.0005
# sim_torch: true
# name: SGD
# warmup:
# type: 'linear'
# linear:
# warmup_steps: 1000 #learning rate rises from 0 to 0.0013 over 1000 steps
official/vision/beta/projects/yolo/configs/experiments/yolov4/tpu/512.yaml
deleted
100755 → 0
View file @
dd921792
runtime
:
distribution_strategy
:
'
tpu'
mixed_precision_dtype
:
'
bfloat16'
task
:
smart_bias_lr
:
0.0
model
:
darknet_based_model
:
True
input_size
:
[
512
,
512
,
3
]
backbone
:
type
:
'
darknet'
darknet
:
model_id
:
'
cspdarknet53'
max_level
:
5
min_level
:
3
decoder
:
type
:
yolo_decoder
yolo_decoder
:
version
:
v4
type
:
regular
activation
:
leaky
head
:
smart_bias
:
true
detection_generator
:
box_type
:
'
all'
:
original
scale_xy
:
'
5'
:
1.05
'
4'
:
1.1
'
3'
:
1.2
max_boxes
:
200
nms_type
:
greedy
iou_thresh
:
0.001
nms_thresh
:
0.60
loss
:
use_scaled_loss
:
False
box_loss_type
:
'
all'
:
ciou
ignore_thresh
:
'
all'
:
0.7
iou_normalizer
:
'
all'
:
0.07
cls_normalizer
:
'
all'
:
1.0
obj_normalizer
:
'
all'
:
1.0
objectness_smooth
:
'
all'
:
0.0
max_delta
:
'
all'
:
5.0
norm_activation
:
activation
:
mish
norm_epsilon
:
0.0001
norm_momentum
:
0.99
use_sync_bn
:
true
num_classes
:
80
anchor_boxes
:
anchors_per_scale
:
3
boxes
:
[
box
:
[
12
,
16
],
box
:
[
19
,
36
],
box
:
[
40
,
28
],
box
:
[
36
,
75
],
box
:
[
76
,
55
],
box
:
[
72
,
146
],
box
:
[
142
,
110
],
box
:
[
192
,
243
],
box
:
[
459
,
401
]]
train_data
:
global_batch_size
:
64
dtype
:
float32
input_path
:
'
gs://cam2-datasets/coco/train*'
is_training
:
true
drop_remainder
:
true
seed
:
1000
parser
:
mosaic
:
mosaic_frequency
:
0.75
mixup_frequency
:
0.0
mosaic_crop_mode
:
'
crop'
mosaic_center
:
0.2
aug_scale_min
:
0.2
aug_scale_max
:
1.6
jitter
:
0.3
max_num_instances
:
200
letter_box
:
False
random_flip
:
True
aug_rand_saturation
:
1.5
aug_rand_brightness
:
1.5
aug_rand_hue
:
0.1
aug_scale_min
:
0.1
aug_scale_max
:
1.9
aug_rand_translate
:
0.0
jitter
:
0.3
area_thresh
:
0.1
random_pad
:
True
use_tie_breaker
:
True
anchor_thresh
:
0.213
validation_data
:
global_batch_size
:
8
dtype
:
float32
input_path
:
'
gs://cam2-datasets/coco/val*'
is_training
:
false
drop_remainder
:
true
parser
:
max_num_instances
:
200
letter_box
:
False
use_tie_breaker
:
True
anchor_thresh
:
0.213
weight_decay
:
0.000
init_checkpoint
:
'
gs://tensorflow2/darknet/cspdarknet53-golden'
init_checkpoint_modules
:
'
backbone'
annotation_file
:
null
trainer
:
train_steps
:
500500
# 160 epochs at 64 batchsize -> 500500 * 64/2
validation_steps
:
625
steps_per_loop
:
1850
summary_interval
:
1850
validation_interval
:
9250
checkpoint_interval
:
1850
optimizer_config
:
ema
:
average_decay
:
0.9998
trainable_weights_only
:
False
dynamic_decay
:
True
learning_rate
:
type
:
stepwise
stepwise
:
boundaries
:
[
400000
,
450000
]
name
:
PiecewiseConstantDecay
values
:
[
0.00131
,
0.000131
,
0.0000131
]
optimizer
:
type
:
sgd_torch
sgd_torch
:
momentum
:
0.949
momentum_start
:
0.949
nesterov
:
True
warmup_steps
:
1000
weight_decay
:
0.0005
sim_torch
:
true
name
:
SGD
warmup
:
type
:
'
linear'
linear
:
warmup_steps
:
1000
#learning rate rises from 0 to 0.0013 over 1000 steps
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