Bnneck implementation

.gitignore

@@ -127,3 +127,22 @@ dmypy.json
 
 # Pyre type checker
 .pyre/
+
+# Dataset
+toDataset/
+/gdrive/Shared drives/REID/ReId-Survey-Paper/ReID-Survey/log/
+/content/gdrive/Shared drives/REID/ReId-Survey-Paper/ReID-Survey/toDataset/
+/content/gdrive/Shared drives/REID/ReId-Survey-Paper/ReID-Survey/resnet50-19c8e357.pth
+/content/gdrive/Shared drives/REID/ReId-Survey-Paper/ReID-Survey/log
+/content/gdrive/Shared drives/REID/ReId-Survey-Paper/ReID-Survey/log/
+*.pth
+feature-pickle.pkl
+*/feature-pickle.pkl
+*.pkl
+*.png
+**/market1501/
+**/test_image/
+**/writer/
+**/log
+log/*
+log/

.vscode/settings.json

@@ -0,0 +1,4 @@
+{
+ "python.linting.pylintEnabled": true,
+ "python.linting.enabled": true
+}

Experiment-AGW-market.sh

@@ -8,5 +8,5 @@
 # weight regularized triplet loss
 # generalized mean pooling
 # non local blocks
-python3 tools/main.py --config_file='configs/AGW_baseline.yml' MODEL.DEVICE_ID "('3')" \
-DATASETS.NAMES "('market1501')" OUTPUT_DIR "('./log/market1501/Experiment-AGW-baseline')"
+python3 tools/main.py --config_file='configs/AGW_baseline.yml' MODEL.DEVICE_ID "('0')" \
+DATASETS.NAMES "('market1501')" OUTPUT_DIR "('./log/market1501/AGW-new-conf-1')"

Experiment-arcface_baseline-market.sh

@@ -0,0 +1,12 @@
+# Dataset: market1501
+# imagesize: 256x128
+# batchsize: 16x4
+# warmup_step 10
+# random erase prob 0.5
+# last stride 1
+# with center loss
+# weight regularized triplet loss
+# generalized mean pooling
+# non local blocks
+python3 tools/main.py --config_file='configs/arcface_baseline.yml' MODEL.DEVICE_ID "('0')" \
+DATASETS.NAMES "('market1501')" OUTPUT_DIR "('./log/market1501/arcface_baseline-1')"

Experiment-arcface_center-market.sh

@@ -0,0 +1,12 @@
+# Dataset: market1501
+# imagesize: 256x128
+# batchsize: 16x4
+# warmup_step 10
+# random erase prob 0.5
+# last stride 1
+# with center loss
+# weight regularized triplet loss
+# generalized mean pooling
+# non local blocks
+python3 tools/main.py --config_file='configs/arcface_center.yml' MODEL.DEVICE_ID "('0')" \
+DATASETS.NAMES "('market1501')" OUTPUT_DIR "('./log/market1501/arcface_center-1')"

Experiment-cosface_center-market.sh

@@ -0,0 +1,12 @@
+# Dataset: market1501
+# imagesize: 256x128
+# batchsize: 16x4
+# warmup_step 10
+# random erase prob 0.5
+# last stride 1
+# with center loss
+# weight regularized triplet loss
+# generalized mean pooling
+# non local blocks
+python3 tools/main.py --config_file='configs/cosface_center.yml' MODEL.DEVICE_ID "('0')" \
+DATASETS.NAMES "('market1501')" OUTPUT_DIR "('./log/market1501/cosface_center-completed-1')"

Test-Oxygen-Transfer.sh

@@ -0,0 +1,7 @@
+python tools/main.py --config_file='configs/AGW_baseline.yml' \
+ MODEL.DEVICE_ID "('0')" \
+ DATASETS.NAMES "('oxygen')" \
+ MODEL.PRETRAIN_CHOICE "('self')" \
+ TEST.WEIGHT "('./log/oxygen1/Experiment-AGW-baseline/resnet50_nl_model_120.pth')" \
+ TEST.EVALUATE_ONLY "('on')" \
+ OUTPUT_DIR "('./log/Oxygen_Test')"

Train-Oxygen-Transfer.sh

@@ -0,0 +1,6 @@
+python ./tools/main.py --config_file='configs/AGW_baseline.yml' \
+ MODEL.DEVICE_ID "('0')" \
+ DATASETS.NAMES "('oxygen')" \
+ MODEL.TRANSFER_MODE "('on')" \
+ MODEL.PRETRAIN_CHOICE "('self')" \
+ MODEL.PRETRAIN_PATH "('./log/market1501/Experiment-AGW-baseline/resnet50_nl_model_160.pth')"

Visalize-no-label.sh

@@ -0,0 +1,23 @@
+# GO TO ROOT DIRECTORY
+# rm -rf ./toDataset/oxygen1
+# rm -rf ./toDataset/oxygen1/gallery
+# mkdir ./toDataset/oxygen1
+# mkdir ./toDataset/oxygen1/gallery
+# Then you put oxygen folder in gallery folder
+# And the structure must be like /gallery/mbk-12-4/*.jpg
+# rm -rf ./log/oxygen1
+# rm -rf ./log/oxygen1/query_image
+# mkdir ./log/oxygen1
+# mkdir ./log/oxygen1/query_image
+
+# and run this command in single line
+python ./tools/main.py --config_file='configs/AGW_baseline.yml' \
+ MODEL.DEVICE_ID "('0')" \
+ DATASETS.NAMES "('oxygen1')" \
+ MODEL.PRETRAIN_CHOICE "('self')" \
+ TEST.WEIGHT "('/home/thanit456/capstone/ReID-Survey/log/market1501/local-AGW-baseline-2/resnet50_nl_model_120.pth')" \
+ VISUALIZE.OPTION "('on_no_label')" \
+ VISUALIZE.INDEX "(-1)" \
+ VISUALIZE.NEED_NEW_FEAT_EMBED "('off')" \
+ VISUALIZE.TOP_RANK "(20)" \
+ VISUALIZE.RE_RANK "('on')" 

Visualize-Oxygen-label.sh

@@ -0,0 +1,9 @@
+python ./tools/main.py --config_file='configs/AGW_baseline.yml' \
+ VISUALIZE.INDEX "(-1)" \
+ MODEL.DEVICE_ID "('0')" \
+ DATASETS.NAMES "('oxygen')" \
+ MODEL.PRETRAIN_CHOICE "('self')" \
+ TEST.WEIGHT "('./log/oxygen/Experiment-AGW-baseline/resnet50_nl_model_120.pth')" \
+ VISUALIZE.OPTION "('on')" \
+ OUTPUT_DIR "('./log/Oxygen/visualize_label_log.txt')" 
+

command.sh

@@ -0,0 +1,11 @@
+conda create -n reid python=3.6
+conda activate reid
+pip install yacs
+pip install -U scipy==1.2.0
+conda install -c pytorch pytorch torchvision ignite==0.1.2 
+
+conda install ipykernel
+
+
+# source activate reid
+# python -m ipykernel install --user --name REID --display-name "Python (REID)"

config/defaults.py

@@ -22,22 +22,30 @@
 # ID number of GPU
 _C.MODEL.DEVICE_ID = '0'
 # Name of backbone
-_C.MODEL.NAME = 'resnet50'
+_C.MODEL.BACKBONE = 'resnet50'
 # Last stride of backbone
 _C.MODEL.LAST_STRIDE = 1
 # Path to pretrained model of backbone
 _C.MODEL.PRETRAIN_PATH = ''
+_C.MODEL.TRANSFER_MODE ="off"
 # Use ImageNet pretrained model to initialize backbone or use self trained model to initialize the whole model
 # Options: 'imagenet' or 'self'
 _C.MODEL.PRETRAIN_CHOICE = 'imagenet'
-# If train with center loss, options: 'bnneck' or 'no'
-_C.MODEL.CENTER_LOSS = 'on'
-_C.MODEL.CENTER_FEAT_DIM = 2048
 # If train with weighted regularized triplet loss, options: 'on', 'off'
 _C.MODEL.WEIGHT_REGULARIZED_TRIPLET = 'off'
-# If train with generalized mean pooling, options: 'on', 'off'
-_C.MODEL.GENERALIZED_MEAN_POOL = 'off'
-
+# If train with cos 
+_C.MODEL.USE_COS = False
+# If train with dropout
+_C.MODEL.USE_DROPOUT = False
+
+# for baseline 
+_C.MODEL.BASELINE = CN()
+_C.MODEL.BASELINE.POOL_TYPE = 'avg'
+_C.MODEL.BASELINE.COSINE_LOSS_TYPE = ''
+_C.MODEL.BASELINE.SCALING_FACTOR = 60.0
+_C.MODEL.BASELINE.MARGIN = 0.35
+_C.MODEL.BASELINE.USE_BNBIAS = False 
+_C.MODEL.BASELINE.USE_SESTN = False 
 
 # -----------------------------------------------------------------------------
 # INPUT
@@ -49,6 +57,7 @@
 _C.INPUT.PROB = 0.5
 # Random probability for random erasing
 _C.INPUT.RE_PROB = 0.5
+_C.INPUT.RE_MAX_RATIO = 0.4
 # Values to be used for image normalization
 _C.INPUT.PIXEL_MEAN = [0.485, 0.456, 0.406]
 # Values to be used for image normalization
@@ -90,10 +99,20 @@
 _C.SOLVER.MOMENTUM = 0.9
 # Margin of triplet loss
 _C.SOLVER.MARGIN = 0.3
-# Learning rate of SGD to learn the centers of center loss
-_C.SOLVER.CENTER_LR = 0.5
-# Balanced weight of center loss
-_C.SOLVER.CENTER_LOSS_WEIGHT = 0.0005
+
+###### Center loss ######
+
+_C.SOLVER.CENTER_LOSS = CN()
+
+_C.SOLVER.CENTER_LOSS.USE = False
+# # Learning rate of SGD to learn the centers of center loss
+_C.SOLVER.CENTER_LOSS.LR = 0.5
+_C.SOLVER.CENTER_LOSS.WEIGHT = 0.0005
+# _C.SOLVER.CENTER_LOSS.ALPHA = 1.0
+
+_C.SOLVER.CENTER_LOSS.NUM_FEATS = 2048
+
+##########################
 
 # Settings of weight decay
 _C.SOLVER.WEIGHT_DECAY = 0.0005
@@ -136,6 +155,25 @@
 _C.TEST.FEAT_NORM = 'on'
 _C.TEST.EVALUATE_ONLY = 'off'
 
+# ---------------------------------------------------------------------------- #
+# Visualize
+# ---------------------------------------------------------------------------- #
+_C.VISUALIZE = CN()
+# option
+_C.VISUALIZE.OPTION = "off"
+_C.VISUALIZE.CAM_OPTION = "allow_other"
+_C.VISUALIZE.IMS_PER_BATCH = 256
+_C.VISUALIZE.NEED_NEW_FEAT_EMBED = "off"
+_C.VISUALIZE.INDEX = 0
+_C.VISUALIZE.TOP_RANK = 10
+_C.VISUALIZE.RE_RANK = "off"
+# ---------------------------------------------------------------------------- #
+# Embedding projector
+# ---------------------------------------------------------------------------- #
+_C.EMBEDDING_PROJECTOR = CN()
+# option 
+_C.EMBEDDING_PROJECTOR.OPTION = "off"
+
 # ---------------------------------------------------------------------------- #
 # Misc options
 # ---------------------------------------------------------------------------- #

configs/AGW_baseline.yml

@@ -1,16 +1,23 @@
 MODEL:
  PRETRAIN_CHOICE: 'imagenet'
- PRETRAIN_PATH: '/home/cgv841/.cache/torch/checkpoints/resnet50-19c8e357.pth'
- CENTER_LOSS: 'on'
- CENTER_FEAT_DIM: 2048
- NAME: 'resnet50_nl'
+ # PRETRAIN_PATH: "/content/drive/Shared drives/REID/ReId-Survey-Paper/ReID-Survey/log/market1501/local-AGW-baseline/resnet50_nl_model_120.pth"
+ PRETRAIN_PATH: '/home/thanit456/torch/weights/resnet50-19c8e357.pth'
+ TRANSFER_MODE : 'off'
+ BACKBONE: 'resnet50_nl'
  WEIGHT_REGULARIZED_TRIPLET: 'on'
- GENERALIZED_MEAN_POOL: 'on'
+ USE_COS: False # unused config
+ USE_DROPOUT: False
+ BASELINE: 
+ POOL_TYPE: 'gem'
+ COSINE_LOSS_TYPE: ''
+ SCALING_FACTOR: 60.0
+ MARGIN: 0.35
 
 INPUT:
  IMG_SIZE: [256, 128]
  PROB: 0.5 # random horizontal flip
  RE_PROB: 0.5 # random erasing
+ RE_MAX_RATIO: 0.4 # correspond to actual baseline
  PADDING: 10
 
 DATASETS:
@@ -25,12 +32,19 @@ SOLVER:
  OPTIMIZER_NAME: 'Adam'
  MAX_EPOCHS: 120
  BASE_LR: 0.00035
+ MARGIN: 0.3
 
- CENTER_LR: 0.5
- CENTER_LOSS_WEIGHT: 0.0005
+ CENTER_LOSS:
+ USE: True
+ LR: 0.5
+ # ALPHA: 0.5
+ WEIGHT: 0.0005
+ NUM_FEATS: 2048
 
- WEIGHT_DECAY: 0.0005
+ WEIGHT_DECAY: 5e-4
  IMS_PER_BATCH: 64
+ # IMS_PER_BATCH: 32
+
 
  STEPS: [40, 70]
  GAMMA: 0.1
@@ -39,16 +53,26 @@ SOLVER:
  WARMUP_ITERS: 10
  WARMUP_METHOD: 'linear'
 
- CHECKPOINT_PERIOD: 40
+ CHECKPOINT_PERIOD: 20
  LOG_PERIOD: 20
  EVAL_PERIOD: 40
 
 TEST:
- IMS_PER_BATCH: 128
+ IMS_PER_BATCH: 64
  RE_RANKING: 'off'
  WEIGHT: "path"
  FEAT_NORM: 'on'
  EVALUATE_ONLY: 'off'
+VISUALIZE :
+ OPTION : "off"
+ IMS_PER_BATCH : 256
+ NEED_NEW_FEAT_EMBED : "off"
+ INDEX : 0
+ TOP_RANK : 10 
+ RE_RANK : "off"
+ CAM_OPTION : "none"
+EMBEDDING_PROJECTOR:
+ OPTION: "off"
 
 OUTPUT_DIR: "./log/market1501/Experiment-AGW-baseline"