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flair-2-config.yml
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data:
path_aerial_train: "" # ./flair_aerial_train/
path_sen_train: "" # ./flair_sen_train/
path_labels_train: "" # ./flair_labels_train/
path_aerial_test: "" # ./flair_2_aerial_test/
path_sen_test: "" # ./flair_2_sen_test/
path_labels_test: ""
path_sp_centroids: "" # ./flair_2_centroids_sp_to_patch.json
path_metadata_aerial: "" # ./flair_aerial_metadata.json
out_folder: "./flair2/"
out_model_name: "flair-2-baseline"
#Fusion
sat_patch_size: 40 # in [8,112] and multiple of 8
w_unet_utae: [1,1]
drop_utae_modality: 0.0 # 1 = dropping U-TAE branch
# MTD and AUG
aerial_metadata: True
geo_enc_size: 32
use_augmentation: True
# Sentinel Time Series filtering
filter_clouds: True
average_month: True
# Weighting
weights_aerial_satellite:
building : [1,1]
pervious surface : [1,1]
impervious surface : [1,1]
bare soil : [1,1]
water : [1,1]
coniferous : [1,1]
deciduous : [1,1]
brushwood : [1,1]
vineyard : [1,1]
herbaceous vegetation : [1,1]
agricutural land : [1,1]
plowed land : [1,0]
other : [0,0]
# Inputs
num_classes: 13
num_channels_aerial: 5
num_channels_sat: 10
# Training
num_epochs: 100
batch_size: 10
batch_size_inference: 1
lr: 0.001
# Computation
num_workers: 10
accelerator: gpu # or cpu
gpus_per_node: 1
num_nodes: 1
strategy: null # ddp if multi-gpu
# UTAE Model
encoder_widths: [64,64,128,128] # 1st and last must be equivalent to decoder_widths
decoder_widths: [64,64,128,128] # 1st and last must be equivalent to encoder_widths
out_conv: [32, 13]
str_conv_k: 4
str_conv_s: 2
str_conv_p: 1
agg_mode: att_group
encoder_norm: group
n_head: 16
d_model: 256
d_k: 4
ref_year: 2021 # defined for whole dataset
ref_date: 05-15 # defined for whole dataset
pad_value: 0
padding_mode: reflect
#Tracking
enable_progress_bar: True
progress_rate: 10