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magicpoint_shapes_pair.yaml
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magicpoint_shapes_pair.yaml
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data:
# name: 'synthetic_shapes'
dataset: 'SyntheticDataset_gaussian'
primitives: 'all'
truncate: {draw_ellipses: 0.3, draw_stripes: 0.2, gaussian_noise: 0.1}
cache_in_memory: true
suffix: 'v6'
add_augmentation_to_test_set: false # set to true to evaluate with noise
gaussian_label:
enable: false
params:
GaussianBlur: {sigma: 0.2}
preprocessing: ## didn't do this
blur_size: 21
resize: [120, 160]
augmentation:
photometric:
enable: true ## for class to recognize
enable_train: true
enable_val: false
primitives: [
'random_brightness', 'random_contrast', 'additive_speckle_noise',
'additive_gaussian_noise', 'additive_shade', 'motion_blur' ]
params:
random_brightness: {max_abs_change: 75}
random_contrast: {strength_range: [0.3, 1.8]}
additive_gaussian_noise: {stddev_range: [0, 15]}
additive_speckle_noise: {prob_range: [0, 0.0035]}
additive_shade:
transparency_range: [-0.5, 0.8]
kernel_size_range: [50, 100]
motion_blur: {max_kernel_size: 7} # origin 7
homographic:
enable: true
enable_train: true
enable_val: false
params:
translation: true
rotation: true
scaling: true
perspective: true
scaling_amplitude: 0.2
perspective_amplitude_x: 0.2
perspective_amplitude_y: 0.2
patch_ratio: 0.8
max_angle: 1.57 # 3.14
allow_artifacts: true
translation_overflow: 0.05
valid_border_margin: 2
warped_pair:
enable: false # false when training only on detector
params:
translation: true
rotation: true
scaling: true
perspective: true
scaling_amplitude: 0.2
perspective_amplitude_x: 0.2
perspective_amplitude_y: 0.2
patch_ratio: 0.85
max_angle: 1.57
allow_artifacts: true # true
valid_border_margin: 3
front_end_model: 'Train_model_heatmap' # 'Train_model_frontend'
model:
name: 'SuperPointNet_gauss2'
params: {
}
detector_loss:
loss_type: 'softmax'
batch_size: 64 # 64
eval_batch_size: 16
learning_rate: 0.001
kernel_reg: 0.
detection_threshold: 0.001 # 1/65
nms: 4
lambda_loss: 0 # disable descriptor loss
dense_loss:
enable: false
params:
descriptor_dist: 4 # 4, 7.5
lambda_d: 800 # 800
sparse_loss:
enable: true
params:
num_matching_attempts: 1000
num_masked_non_matches_per_match: 100
lamda_d: 1
dist: 'cos'
method: '2d'
other_settings: 'train 2d, gauss 0.5'
retrain: True # set true for new model
reset_iter: True
train_iter: 200000 # 200000
tensorboard_interval: 1000 # 200
save_interval: 2000 # 2000
validation_interval: 1000 # one validation of entire val set every N training steps
validation_size: 10
train_show_interval: 1000 # one show of the current training from to Tensorboard every N training steps
seed: 0
# pretrained: 'logs/superpoint_syn_heat1_0/checkpoints/superPointNet_100000_checkpoint.pth.tar'