|
|
data: |
|
|
root: '/root/DATASET/UAV2MAP/UAV/' |
|
|
train_citys: |
|
|
- Paris |
|
|
- Berlin |
|
|
- London |
|
|
- Tokyo |
|
|
- NewYork |
|
|
val_citys: |
|
|
- Toronto |
|
|
image_size: 256 |
|
|
train: |
|
|
batch_size: 12 |
|
|
num_workers: 4 |
|
|
val: |
|
|
batch_size: ${..train.batch_size} |
|
|
num_workers: ${.batch_size} |
|
|
num_classes: |
|
|
areas: 7 |
|
|
ways: 10 |
|
|
nodes: 33 |
|
|
pixel_per_meter: 1 |
|
|
crop_size_meters: 64 |
|
|
max_init_error: 48 |
|
|
add_map_mask: true |
|
|
resize_image: 512 |
|
|
pad_to_square: true |
|
|
rectify_pitch: true |
|
|
augmentation: |
|
|
rot90: true |
|
|
flip: true |
|
|
image: |
|
|
apply: true |
|
|
brightness: 0.5 |
|
|
contrast: 0.4 |
|
|
saturation: 0.4 |
|
|
hue": 0.5/3.14 |
|
|
model: |
|
|
image_size: ${data.image_size} |
|
|
latent_dim: 128 |
|
|
val_citys: ${data.val_citys} |
|
|
image_encoder: |
|
|
name: feature_extractor_v2 |
|
|
backbone: |
|
|
encoder: resnet50 |
|
|
pretrained: true |
|
|
output_dim: 8 |
|
|
num_downsample: null |
|
|
remove_stride_from_first_conv: false |
|
|
name: orienternet |
|
|
matching_dim: 8 |
|
|
z_max: 32 |
|
|
x_max: 32 |
|
|
pixel_per_meter: 1 |
|
|
num_scale_bins: 33 |
|
|
num_rotations: 64 |
|
|
map_encoder: |
|
|
embedding_dim: 16 |
|
|
output_dim: 8 |
|
|
num_classes: |
|
|
areas: 7 |
|
|
ways: 10 |
|
|
nodes: 33 |
|
|
backbone: |
|
|
encoder: vgg19 |
|
|
pretrained: false |
|
|
output_scales: |
|
|
- 0 |
|
|
num_downsample: 3 |
|
|
decoder: |
|
|
- 128 |
|
|
- 64 |
|
|
- 64 |
|
|
padding: replicate |
|
|
unary_prior: false |
|
|
bev_net: |
|
|
num_blocks: 4 |
|
|
latent_dim: 128 |
|
|
output_dim: 8 |
|
|
confidence: true |
|
|
experiment: |
|
|
name: maplocanet_0906_diffhight |
|
|
gpus: 6 |
|
|
seed: 0 |
|
|
training: |
|
|
lr: 0.0001 |
|
|
lr_scheduler: null |
|
|
finetune_from_checkpoint: null |
|
|
trainer: |
|
|
val_check_interval: 1000 |
|
|
log_every_n_steps: 100 |
|
|
|
|
|
max_steps: 200000 |
|
|
devices: ${experiment.gpus} |
|
|
checkpointing: |
|
|
monitor: "loss/total/val" |
|
|
save_top_k: 10 |
|
|
mode: min |
|
|
|
|
|
|
