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config-default.yaml
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config-default.yaml
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general:
working_dir: ./
logging_level: INFO
models:
inception_resnet_v1:
keep_probability: 0.8
bottleneck_layer_size: 128
dropout_keep_prob: 0.8
reuse: null
common_layer_regularizer: 0.1
age_regularizer: 0.1
gender_regularizer: 0.1
resnet_v2_50:
learning_rates:
exponential:
learning_rate: 0.001
decay_steps: 3000
decay_rate: 0.9
staircase: True
cyclic:
learning_rate: 0.001
max_lr: 0.1
step_size: 20
gamma: 0.99994
mode: exp_range
linear:
learning_rate: 0.001
decay_steps: 1000
num_periods: 1000 # при совпадении с decay_steps, lr будет меняться от learning_rate до 0
alpha: 0
beta: 0
prepare:
general:
dataset_path: data/dataset.json
test_size: 0.2
processed_dataset_path: data/processed_data
n_jobs: 8
image:
size: 256
height_scale: 1.7
width_scale: 1.2
face_score_threshold: 0.75
face_area_threshold: 2500
datasets:
UTKFace:
images_path: data/UTK_aligned
full_desc_path: data/UTK_aligned/dataset.json
train_desc_path: data/UTK_aligned/train.json
test_desc_path: data/UTK_aligned/test.json
balance:
ages: [20, 50 ,100]
weights: [3.13, 1, 3.10]
imdb_wiki_crop:
images_path: data/imdb_wiki
full_desc_path: data/imdb_wiki/dataset.json
train_desc_path: data/imdb_wiki/train.json
test_desc_path: data/imdb_wiki/test.json
balance:
ages: [20, 50 ,100]
weights: [13.67, 1, 4.22]
train:
dataset: UTKFace
balance_dataset: False
# варианты: 1) inception_resnet_v1 2) resnet_v2_50
model: inception_resnet_v1
# файл модели или папка с файлами для загрузки с диска
# model_path models/pretrained_models
model_path: null
# частота сохранения моделей
save_frequency: 15000
val_frequency: 5
num_prefetch: 2
num_parallel_calls: 2
# от значения train_mode зависит, куда будут сохраняться модели
# 1) start - во вновь созданную папку
# 2) continue - в папку с предобученной моделью
# 3) test - запустить анализ результатов для обученной модели model_path
mode: start
# значения могут быть: linear, exponential, cyclic, test_lr
learning_rate: exponential
epochs: 50
batch_size: 16 # 30 максимум для GeForce 1060
cuda: True
face_area_threshold: 2500
inference:
batch_size: 16
dataset_path: data/UTK_aligned/dataset.json
model_path: experiments/2019_07_08_18_31 #/model.ckpt-14001
cuda: True
results_path: results.json