Skip to content

Commit

Permalink
Merge pull request #26 from MortenTabaka/Train_model_with_similar_set…
Browse files Browse the repository at this point in the history 
…tings_as_in_original_Deeplabv3plus_paper

Optimizer: tensorflow.python.keras.optimizer_v2.adam.Adam with decaying learning rate (rate_decay = 0.94) and weight decay (decay=4e-5).

SemanticSegmentationLoss.basnet_hybrid_loss
  • Loading branch information
@MortenTabaka
MortenTabaka committed Apr 11, 2023
2 parents 68d98f6 + bc28be4 commit 9e71e92
Show file tree
Hide file tree
Showing 6 changed files with 948 additions and 140 deletions.
330 changes: 330 additions & 0 deletions models/models_revisions.yaml
View file
Original file line number Diff line number Diff line change
Expand Up @@ -107,3 +107,333 @@ deeplabv3plus_v11.0.1:
- 0.8716736435890198
test_mIoU:
- 0.44352978467941284
deeplabv3plus_v12.0.1:
model_name: deeplabv3plus
revision: 12.0.1
dataset_parameters:
input_image_height: 512
input_image_width: 512
number_of_classes: 5
batch_size: 4
model_build_parameters:
pretrained_weights: cityscapes
second_input: null
input_shape:
input_image_height: 512
input_image_width: 512
channels: 3
num_classes: 5
backbone: xception
output_stride: 16
alpha: 1.0
activation: softmax
model_compile_parameters:
optimizer: <tensorflow.python.keras.optimizer_v2.adam.Adam object at 0x7f63805937c0>
loss_function:
object: <bound method SemanticSegmentationLoss.unet3p_hybrid_loss of <src.features.loss_functions.SemanticSegmentationLoss
object at 0x7f62e01897f0>>
initial_learning_rate: 0.05
final_learning_rate: null
metrics:
- accuracy
- <src.features.metrics.CustomMeanIoU object at 0x7f62e017ea90>
deeplabv3plus_v12.1.1:
model_name: deeplabv3plus
revision: 12.1.1
dataset_parameters:
input_image_height: 512
input_image_width: 512
number_of_classes: 5
batch_size: 8
model_build_parameters:
pretrained_weights: cityscapes
second_input: null
input_shape:
input_image_height: 512
input_image_width: 512
channels: 3
num_classes: 5
backbone: xception
output_stride: 16
alpha: 1.0
activation: softmax
model_compile_parameters:
optimizer: <tensorflow.python.keras.optimizer_v2.adam.Adam object at 0x7f37581ccee0>
loss_function:
object: <bound method SemanticSegmentationLoss.basnet_hybrid_loss of <src.features.loss_functions.SemanticSegmentationLoss
object at 0x7f37581ccbb0>>
initial_learning_rate: 0.005
final_learning_rate: null
metrics:
- accuracy
- <src.features.metrics.CustomMeanIoU object at 0x7f373b7d90d0>
history_and_evaluation:
loss:
- 0.893105685710907
- 0.7731820940971375
- 0.632534921169281
- 0.5076855421066284
- 0.43058332800865173
- 0.37186551094055176
- 0.32428067922592163
- 0.28995466232299805
accuracy:
- 0.739052414894104
- 0.7835270762443542
- 0.8342221975326538
- 0.870703935623169
- 0.8915104269981384
- 0.9079511165618896
- 0.9206518530845642
- 0.9297395348548889
mIoU:
- 0.2750715911388397
- 0.33152368664741516
- 0.43089085817337036
- 0.5192099213600159
- 0.5810223817825317
- 0.628042459487915
- 0.6663795709609985
- 0.693867564201355
val_loss:
- 0.7037246227264404
- 0.5621010661125183
- 0.5564318895339966
- 0.5417349338531494
- 0.5246396064758301
- 0.5276296138763428
- 0.5404360294342041
- 0.5412373542785645
val_accuracy:
- 0.7965981364250183
- 0.8518159985542297
- 0.8638916015625
- 0.8632866740226746
- 0.8687572479248047
- 0.8697471022605896
- 0.865138828754425
- 0.8659769296646118
val_mIoU:
- 0.28303393721580505
- 0.3937259912490845
- 0.5468068718910217
- 0.5735112428665161
- 0.5930857062339783
- 0.5997530221939087
- 0.5935394763946533
- 0.5961015224456787
training_set:
best_loss: 0.28995466232299805
best_accuracy: 0.9297395348548889
best_mIoU: 0.693867564201355
validation_set:
best_val_loss: 0.5246396064758301
best_val_accuracy: 0.8697471022605896
best_val_mIoU: 0.5997530221939087
testing_set:
test_loss:
- 0.5434367060661316
test_accuracy:
- 0.8641740679740906
test_mIoU:
- 0.5976591110229492
deeplabv3plus_v12.1.2:
model_name: deeplabv3plus
revision: 12.1.2
dataset_parameters:
input_image_height: 512
input_image_width: 512
number_of_classes: 5
batch_size: 4
model_build_parameters:
pretrained_weights: cityscapes
second_input: null
input_shape:
input_image_height: 512
input_image_width: 512
channels: 3
num_classes: 5
backbone: xception
output_stride: 16
alpha: 1.0
activation: softmax
model_compile_parameters:
optimizer: <tensorflow.python.keras.optimizer_v2.adam.Adam object at 0x7f37200b7130>
loss_function:
object: <bound method SemanticSegmentationLoss.basnet_hybrid_loss of <src.features.loss_functions.SemanticSegmentationLoss
object at 0x7f37581ccbb0>>
initial_learning_rate: 0.0001
final_learning_rate: null
metrics:
- accuracy
- <src.features.metrics.CustomMeanIoU object at 0x7f373b7d90d0>
history_and_evaluation:
loss:
- 0.5320228338241577
- 0.379629909992218
- 0.3005774915218353
- 0.25602877140045166
- 0.22254985570907593
- 0.19794374704360962
- 0.17857863008975983
- 0.16180071234703064
- 0.14944235980510712
- 0.13775938749313354
accuracy:
- 0.8594179153442383
- 0.9043959379196167
- 0.9276505708694458
- 0.9394705891609192
- 0.9482050538063049
- 0.954479992389679
- 0.9592324495315552
- 0.9634354710578918
- 0.9664245247840881
- 0.9693020582199097
mIoU:
- 0.5168450474739075
- 0.6134913563728333
- 0.6783340573310852
- 0.7152823209762573
- 0.7455981373786926
- 0.7696963548660278
- 0.789281964302063
- 0.8064092397689819
- 0.8194147348403931
- 0.8321843147277832
val_loss:
- 0.4509657621383667
- 0.42736947536468506
- 0.3927899897098541
- 0.4045372009277344
- 0.3830377459526062
- 0.36208099126815796
- 0.34700730443000793
- 0.346681147813797
- 0.3391178548336029
- 0.34919124841690063
val_accuracy:
- 0.8815209865570068
- 0.8895505666732788
- 0.9000356197357178
- 0.8974916934967041
- 0.9033209085464478
- 0.9093674421310425
- 0.9137521386146545
- 0.9159703850746155
- 0.9174870848655701
- 0.9141018390655518
val_mIoU:
- 0.6176990270614624
- 0.6323135495185852
- 0.6555559039115906
- 0.6568180322647095
- 0.6762748956680298
- 0.6816496849060059
- 0.6929003596305847
- 0.709352433681488
- 0.7068096995353699
- 0.7052137851715088
training_set:
best_loss: 0.13775938749313354
best_accuracy: 0.9693020582199097
best_mIoU: 0.8321843147277832
validation_set:
best_val_loss: 0.3391178548336029
best_val_accuracy: 0.9174870848655701
best_val_mIoU: 0.709352433681488
testing_set:
test_loss:
- 0.3643128573894501
test_accuracy:
- 0.9113060235977173
test_mIoU:
- 0.70816969871521
deeplabv3plus_v12.1.3:
model_name: deeplabv3plus
revision: 12.1.3
dataset_parameters:
input_image_height: 512
input_image_width: 512
number_of_classes: 5
batch_size: 4
model_build_parameters:
pretrained_weights: cityscapes
second_input: null
input_shape:
input_image_height: 512
input_image_width: 512
channels: 3
num_classes: 5
backbone: xception
output_stride: 16
alpha: 1.0
activation: softmax
model_compile_parameters:
optimizer: <tensorflow.python.keras.optimizer_v2.adam.Adam object at 0x7ff7bc6fb4f0>
loss_function:
object: <bound method SemanticSegmentationLoss.basnet_hybrid_loss of <src.features.loss_functions.SemanticSegmentationLoss
object at 0x7ff7ec657f10>>
initial_learning_rate: 1.0e-05
final_learning_rate: null
metrics:
- accuracy
- <src.features.metrics.CustomMeanIoU object at 0x7ff7ec657460>
history_and_evaluation:
loss:
- 0.1806638240814209
- 0.15898723900318146
- 0.14795738458633423
- 0.1401384174823761
- 0.13411937654018402
- 0.12945543229579926
accuracy:
- 0.9584441184997559
- 0.9641492962837219
- 0.9670787453651428
- 0.9691571593284607
- 0.9707059264183044
- 0.9719213247299194
mIoU:
- 0.7917389869689941
- 0.8073371648788452
- 0.8170927166938782
- 0.8247373700141907
- 0.8304632902145386
- 0.8354042172431946
val_loss:
- 0.3413395285606384
- 0.3419068157672882
- 0.3428400754928589
- 0.34714850783348083
- 0.35025814175605774
- 0.35276564955711365
val_accuracy:
- 0.9163888692855835
- 0.9164921045303345
- 0.9163609147071838
- 0.9151012301445007
- 0.9143058657646179
- 0.9137394428253174
val_mIoU:
- 0.699703574180603
- 0.7033711671829224
- 0.7035443186759949
- 0.7005492448806763
- 0.7002022862434387
- 0.6981862783432007
training_set:
best_loss: 0.12945543229579926
best_accuracy: 0.9719213247299194
best_mIoU: 0.8354042172431946
validation_set:
best_val_loss: 0.3413395285606384
best_val_accuracy: 0.9164921045303345
best_val_mIoU: 0.7035443186759949
testing_set:
test_loss:
- 0.36516308784484863
test_accuracy:
- 0.9106625318527222
test_mIoU:
- 0.7011236548423767
13 changes: 10 additions & 3 deletions models/scripts/run_prediction_on_folder.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -12,10 +12,17 @@ class TypeOfWeightsToLoad(str, Enum):
loss = "loss"


class AvailableRevisions(str, Enum):
version_5_10_2 = "deeplabv3plus_v5.10.2"
version_10_0_1 = "deeplabv3plus_v10.0.1"
version_12_1_2 = "deeplabv3plus_v12.1.2"


def main(
model_revision: str = typer.Option(
default="deeplabv3plus_v5.10.2",
help="Choose model revision for predictions",
model_revision: AvailableRevisions = typer.Option(
default=AvailableRevisions.version_5_10_2,
help="Choose model revision for predictions.",
show_choices=True
),
weights: TypeOfWeightsToLoad = typer.Option(
default=TypeOfWeightsToLoad.miou,
Expand Down

0 comments on commit 9e71e92

Please sign in to comment.