Vincentqyw
update: features and matchers
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### [Model parameters]
model_name: "lcnn_simple"
model_architecture: "simple"
# Backbone related config
backbone: "lcnn"
backbone_cfg:
input_channel: 1 # Use RGB images or grayscale images.
depth: 4
num_stacks: 2
num_blocks: 1
num_classes: 5
# Junction decoder related config
junction_decoder: "superpoint_decoder"
junc_decoder_cfg:
# Heatmap decoder related config
heatmap_decoder: "pixel_shuffle"
heatmap_decoder_cfg:
# Descriptor decoder related config
descriptor_decoder: "superpoint_descriptor"
descriptor_decoder_cfg:
# Shared configurations
grid_size: 8
keep_border_valid: True
# Threshold of junction detection
detection_thresh: 0.0153846 # 1/65
# Threshold of heatmap detection
prob_thresh: 0.5
### [Loss parameters]
weighting_policy: "dynamic"
# [Heatmap loss]
w_heatmap: 0.
w_heatmap_class: 1
heatmap_loss_func: "cross_entropy"
heatmap_loss_cfg:
policy: "dynamic"
# [Junction loss]
w_junc: 0.
junction_loss_func: "superpoint"
junction_loss_cfg:
policy: "dynamic"
# [Descriptor loss]
w_desc: 0.
descriptor_loss_func: "regular_sampling"
descriptor_loss_cfg:
dist_threshold: 8
grid_size: 4
margin: 1
policy: "dynamic"
### [Training parameters]
learning_rate: 0.0005
epochs: 130
train:
batch_size: 4
num_workers: 8
test:
batch_size: 4
num_workers: 8
disp_freq: 100
summary_freq: 200
max_ckpt: 130