File size: 2,166 Bytes
f7f604d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | Model:
name: "InSPyReNet_Res2Net50"
depth: 64
pretrained: True
base_size: [384, 384]
threshold: NULL
Train:
Dataset:
type: "RGB_Dataset"
root: "data/Train_Dataset"
sets: ['DUTS-TR']
transforms:
static_resize:
size: [384, 384]
random_scale_crop:
range: [0.75, 1.25]
random_flip:
lr: True
ud: False
random_rotate:
range: [-10, 10]
random_image_enhance:
methods: ['contrast', 'sharpness', 'brightness']
tonumpy: NULL
normalize:
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
totensor: NULL
Dataloader:
batch_size: 6
shuffle: True
num_workers: 8
pin_memory: True
Optimizer:
type: "Adam"
lr: 1.0e-05
weight_decay: 0.0
mixed_precision: False
Scheduler:
type: "PolyLr"
epoch: 60
gamma: 0.9
minimum_lr: 1.0e-07
warmup_iteration: 12000
Checkpoint:
checkpoint_epoch: 1
checkpoint_dir: "snapshots/InSPyReNet_Res2Net50"
Debug:
keys: ['saliency', 'laplacian']
Test:
Dataset:
type: "RGB_Dataset"
root: "data/Test_Dataset"
sets: ['DUTS-TE', 'DUT-OMRON', 'ECSSD', 'HKU-IS', 'PASCAL-S', 'DAVIS-S', 'HRSOD', 'UHRSD-TE']
transforms:
static_resize:
size: [384, 384]
tonumpy: NULL
normalize:
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
totensor: NULL
Dataloader:
num_workers: 8
pin_memory: True
Checkpoint:
checkpoint_dir: "snapshots/InSPyReNet_Res2Net50"
Eval:
gt_root: "data/Test_Dataset"
pred_root: "snapshots/InSPyReNet_Res2Net50"
result_path: "results"
datasets: ['DUTS-TE', 'DUT-OMRON', 'ECSSD', 'HKU-IS', 'PASCAL-S', 'DAVIS-S', 'HRSOD', 'UHRSD-TE']
metrics: ['Sm', 'mae', 'adpEm', 'maxEm', 'avgEm', 'adpFm', 'maxFm', 'avgFm', 'wFm', 'mBA']
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