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model:
arch: CMP
total_iter: 42000
lr_steps: [24000, 36000]
lr_mults: [0.1, 0.1]
lr: 0.1
optim: SGD
warmup_lr: []
warmup_steps: []
module:
arch: CMP
image_encoder: resnet50
sparse_encoder: shallownet8x
flow_decoder: MotionDecoderSkipLayer
skip_layer: True
img_enc_dim: 256
sparse_enc_dim: 16
output_dim: 198
decoder_combo: [1,2,4]
pretrained_image_encoder: False
flow_criterion: "DiscreteLoss"
nbins: 99
fmax: 50
data:
workers: 2
batch_size: 8
batch_size_test: 1
data_mean: [123.675, 116.28, 103.53] # RGB
data_div: [58.395, 57.12, 57.375]
short_size: 416
crop_size: [384, 384]
sample_strategy: ['grid', 'watershed']
sample_bg_ratio: 5.74e-5
nms_ks: 41
max_num_guide: -1
flow_file_type: "jpg"
image_flow_aug:
flip: False
flow_aug:
reverse: False
scale: False
rotate: False
train_source:
- data/VIP/lists/train.txt
- data/MPII/lists/train.txt
val_source:
- data/VIP/lists/randval.txt
memcached: False
trainer:
initial_val: True
print_freq: 100
val_freq: 5000
save_freq: 5000
val_iter: -1
val_disp_start_iter: 0
val_disp_end_iter: 16
loss_record: ['loss_flow']
tensorboard: True
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