IMAG

IMAG

configs/Base-AGW.yml

@@ -0,0 +1,19 @@
+_BASE_: Base-bagtricks.yml
+
+MODEL:
+  BACKBONE:
+    WITH_NL: True
+
+  HEADS:
+    POOL_LAYER: GeneralizedMeanPooling
+
+  LOSSES:
+    NAME: ("CrossEntropyLoss", "TripletLoss")
+    CE:
+      EPSILON: 0.1
+      SCALE: 1.0
+
+    TRI:
+      MARGIN: 0.0
+      HARD_MINING: False
+      SCALE: 1.0

configs/Base-MGN.yml

@@ -0,0 +1,12 @@
+_BASE_: Base-SBS.yml
+
+MODEL:
+  META_ARCHITECTURE: MGN
+
+  FREEZE_LAYERS: [backbone, b1, b2, b3,]
+
+  BACKBONE:
+    WITH_NL: False
+
+  HEADS:
+    EMBEDDING_DIM: 256

configs/Base-SBS.yml

@@ -0,0 +1,63 @@
+_BASE_: Base-bagtricks.yml
+
+MODEL:
+  FREEZE_LAYERS: [ backbone ]
+
+  BACKBONE:
+    WITH_NL: True
+
+  HEADS:
+    NECK_FEAT: after
+    POOL_LAYER: GeneralizedMeanPoolingP
+    CLS_LAYER: CircleSoftmax
+    SCALE: 64
+    MARGIN: 0.35
+
+  LOSSES:
+    NAME: ("CrossEntropyLoss", "TripletLoss",)
+    CE:
+      EPSILON: 0.1
+      SCALE: 1.0
+
+    TRI:
+      MARGIN: 0.0
+      HARD_MINING: True
+      NORM_FEAT: False
+      SCALE: 1.0
+
+INPUT:
+  SIZE_TRAIN: [ 384, 128 ]
+  SIZE_TEST: [ 384, 128 ]
+
+  AUTOAUG:
+    ENABLED: True
+    PROB: 0.1
+
+DATALOADER:
+  NUM_INSTANCE: 16
+
+SOLVER:
+  AMP:
+    ENABLED: True
+  OPT: Adam
+  MAX_EPOCH: 60
+  BASE_LR: 0.00035
+  WEIGHT_DECAY: 0.0005
+  IMS_PER_BATCH: 64
+
+  SCHED: CosineAnnealingLR
+  DELAY_EPOCHS: 30
+  ETA_MIN_LR: 0.0000007
+
+  WARMUP_FACTOR: 0.1
+  WARMUP_ITERS: 2000
+
+  FREEZE_ITERS: 1000
+
+  CHECKPOINT_PERIOD: 20
+
+TEST:
+  EVAL_PERIOD: 10
+  IMS_PER_BATCH: 128
+
+CUDNN_BENCHMARK: True

configs/Base-bagtricks.yml

@@ -0,0 +1,76 @@
+MODEL:
+  META_ARCHITECTURE: Baseline
+
+  BACKBONE:
+    NAME: build_resnet_backbone
+    NORM: BN
+    DEPTH: 50x
+    LAST_STRIDE: 1
+    FEAT_DIM: 2048
+    WITH_IBN: False
+    PRETRAIN: True
+
+  HEADS:
+    NAME: EmbeddingHead
+    NORM: BN
+    WITH_BNNECK: True
+    POOL_LAYER: GlobalAvgPool
+    NECK_FEAT: before
+    CLS_LAYER: Linear
+
+  LOSSES:
+    NAME: ("CrossEntropyLoss", "TripletLoss",)
+
+    CE:
+      EPSILON: 0.1
+      SCALE: 1.
+
+    TRI:
+      MARGIN: 0.3
+      HARD_MINING: True
+      NORM_FEAT: False
+      SCALE: 1.
+
+INPUT:
+  SIZE_TRAIN: [ 256, 128 ]
+  SIZE_TEST: [ 256, 128 ]
+
+  REA:
+    ENABLED: True
+    PROB: 0.5
+
+  FLIP:
+    ENABLED: True
+
+  PADDING:
+    ENABLED: True
+
+DATALOADER:
+  SAMPLER_TRAIN: NaiveIdentitySampler
+  NUM_INSTANCE: 4
+  NUM_WORKERS: 8
+
+SOLVER:
+  AMP:
+    ENABLED: True
+  OPT: Adam
+  MAX_EPOCH: 120
+  BASE_LR: 0.00035
+  WEIGHT_DECAY: 0.0005
+  WEIGHT_DECAY_NORM: 0.0005
+  IMS_PER_BATCH: 64
+
+  SCHED: MultiStepLR
+  STEPS: [ 40, 90 ]
+  GAMMA: 0.1
+
+  WARMUP_FACTOR: 0.1
+  WARMUP_ITERS: 2000
+
+  CHECKPOINT_PERIOD: 30
+
+TEST:
+  EVAL_PERIOD: 30
+  IMS_PER_BATCH: 128
+
+CUDNN_BENCHMARK: True

configs/baseline.yaml

@@ -0,0 +1,51 @@
+_BASE_: Base-SBS.yml
+
+MODEL:
+  BACKBONE:
+    NAME: build_resnet_backbone
+    WITH_IBN: True
+    DEPTH: 50x
+    FEAT_DIM: 2048
+    PRETRAIN: True
+    PRETRAIN_PATH: pretrain/resnet50_ibn_a-d9d0bb7b.pth
+
+
+INPUT:
+  SIZE_TRAIN: [ 256, 256 ]
+  SIZE_TEST: [ 256, 256 ]
+
+
+SOLVER:
+  MAX_EPOCH: 40
+  DELAY_EPOCHS: 5
+  BASE_LR: 0.00035
+  CHECKPOINT_PERIOD: 5
+  IMS_PER_BATCH: 64
+
+  WARMUP_FACTOR: 0.1
+  WARMUP_ITERS: 400
+
+  FREEZE_ITERS: 1000
+
+DATALOADER:
+  SAMPLER_TRAIN: NaiveIdentitySampler
+  NUM_INSTANCE: 2
+  NUM_WORKERS: 8
+
+TEST:
+  EVAL_PERIOD: 5
+
+  RERANK:
+    ENABLED: False
+    K1: 20
+    K2: 3
+    LAMBDA: 0.8
+
+  FLIP:
+    ENABLED: False
+
+DATASETS:
+  NAMES: ("PetID",)
+  TESTS: ("PetID",)
+
+OUTPUT_DIR: logs/baseline

configs/baselinev1_s101_224.yaml

@@ -0,0 +1,131 @@
+_BASE_: Base-SBS.yml
+
+MODEL:
+  BACKBONE:
+    NAME: build_resnest_backbone
+    WITH_IBN: True    
+    WITH_NL:  True    
+    WITH_SE: False
+    DEPTH: 101x
+    FEAT_DIM: 2048
+    PRETRAIN: True
+    PRETRAIN_PATH:  'pretrain/resnest101-22405ba7.pth'
+    NORM: BN   
+
+  HEADS:
+    NECK_FEAT: after
+    POOL_LAYER: GeneralizedMeanPoolingP
+    CLS_LAYER: CosSoftmax     
+    SCALE: 64
+    MARGIN: 0.35         
+    NORM: BN   
+
+
+  LOSSES:
+    NAME: ( "TripletLoss", "CircleLoss", "CrossEntropyLoss", )    
+    CE:
+      EPSILON: 0.1
+      SCALE: 1.0
+
+    CIRCLE:
+      MARGIN: 0.35
+      GAMMA: 64
+      SCALE: 1.0
+
+
+    TRI:
+      MARGIN: 0.0
+      HARD_MINING: True    
+      NORM_FEAT: False
+      SCALE: 1.0
+INPUT:
+  SIZE_TRAIN: [224, 224]
+  SIZE_TEST: [224, 224]
+
+  CROP:
+    ENABLED: True
+    SIZE: [224, 224]    
+    RATIO: [0.16, 1]
+    SCALE:  [0.75, 1.33333]
+
+  REA:
+    ENABLED: False
+    PROB: 0.5
+    VALUE: [0, 0, 0]
+  RPT:
+    ENABLED: False
+    PROB: 0.5
+
+  BLUR:
+    ENABLED: True
+    KERNEL_SIZE : (5, 9)
+
+  FLIP:
+    ENABLED: True
+    PROB: 0.5
+
+  VFLIP:
+    ENABLED: False
+    PROB: 0.5
+
+  PADDING:
+    ENABLED: True
+    SIZE: 10
+
+  AUTOAUG:
+    ENABLED: True
+    PROB: 0.5
+
+  AUGMIX:
+    ENABLED: True
+    PROB: 0.5
+
+  AFFINE:
+    ENABLED: True
+
+  CJ:
+    ENABLED: True
+    BRIGHTNESS: 0.15
+    CONTRAST: 0.15
+    SATURATION: 0.1
+    HUE: 0.1
+    PROB: 0.5
+
+SOLVER:
+  OPT: Adam
+  MAX_EPOCH: 35
+  DELAY_EPOCHS: 5
+  BASE_LR: 0.00035   
+  HEADS_LR_FACTOR: 1.0
+  CHECKPOINT_PERIOD: 5
+  IMS_PER_BATCH: 80
+
+  WARMUP_FACTOR: 0.1
+  WARMUP_ITERS: 400
+
+  FREEZE_ITERS: 1000
+
+DATALOADER:
+  SAMPLER_TRAIN: NaiveIdentitySampler  
+  NUM_INSTANCE: 4
+  NUM_WORKERS: 8
+
+TEST:
+  EVAL_PERIOD: 100000
+
+  METRIC: 'cosine'
+
+  RERANK:
+    ENABLED: False
+    K1: 20
+    K2: 3
+    LAMBDA: 0.8
+
+  FLIP:
+    ENABLED: False
+
+DATASETS:
+  NAMES: ("PetID",)
+  TESTS: ("PetID",)
+
+OUTPUT_DIR: logs/s101_224

configs/baselinev1_s101_256.yaml

@@ -0,0 +1,13 @@
+_BASE_: baselinev1_s101.yaml
+
+
+
+INPUT:
+  SIZE_TRAIN: [256, 256]
+  SIZE_TEST: [256, 256]
+
+  CROP:
+    ENABLED: True
+    SIZE: [256, 256] 
+
+OUTPUT_DIR: logs/s101_256

configs/baselinev1_s101_288.yaml

@@ -0,0 +1,12 @@
+_BASE_: baselinev1_s101.yaml
+
+
+INPUT:
+  SIZE_TRAIN: [288, 288]
+  SIZE_TEST: [288, 288]
+
+  CROP:
+    ENABLED: True
+    SIZE: [288, 288] 
+
+OUTPUT_DIR: logs/s101_288