Update configs

configs/cityscape.yaml

@@ -23,8 +23,6 @@ AUG:
         CONTRAST_JITTER_RATIO: 0.5
         SATURATION_JITTER_RATIO: 0.5
 BATCH_SIZE: 4
-MEAN: [0.5, 0.5, 0.5]
-STD: [0.5, 0.5, 0.5]
 DATASET:
     DATA_DIR: "./dataset/cityscapes/"
     IMAGE_TYPE: "rgb"  # choice rgb or rgba

configs/coco.yaml

@@ -23,8 +23,6 @@ AUG:
         CONTRAST_JITTER_RATIO: 0.5
         SATURATION_JITTER_RATIO: 0.5
 BATCH_SIZE: 8
-MEAN: [104.008, 116.669, 122.675]
-STD: [1.0, 1.0, 1.0]
 DATASET:
     DATA_DIR: "./data/COCO2014/"
     IMAGE_TYPE: "rgb"  # choice rgb or rgba

configs/humanseg.yaml

-TRAIN_CROP_SIZE: (513, 513) # (width, height), for unpadding rangescaling and stepscaling
-EVAL_CROP_SIZE: (513, 513) # (width, height), for unpadding rangescaling and stepscaling
-AUG:
-    AUG_METHOD: u"unpadding" # choice unpadding rangescaling and stepscaling
-    FIX_RESIZE_SIZE: (513, 513) # (width, height), for unpadding
-    INF_RESIZE_VALUE: 513  # for rangescaling
-    MAX_RESIZE_VALUE: 400  # for rangescaling
-    MIN_RESIZE_VALUE: 513  # for rangescaling
-    MAX_SCALE_FACTOR: 2.0  # for stepscaling
-    MIN_SCALE_FACTOR: 0.5  # for stepscaling
-    SCALE_STEP_SIZE: 0.25  # for stepscaling
-    MIRROR: True
-    RICH_CROP:
-        ENABLE: True
-        ASPECT_RATIO: 0
-        BLUR: True
-        BLUR_RATIO: 0.1
-        FLIP: True
-        FLIP_RATIO: 0.2
-        MAX_ROTATION: 45
-        MIN_AREA_RATIO: 0
-        BRIGHTNESS_JITTER_RATIO: 0.5
-        CONTRAST_JITTER_RATIO: 0.5
-        SATURATION_JITTER_RATIO: 0.5
-BATCH_SIZE: 24
-MEAN: [104.008, 116.669, 122.675]
-STD: [1.0, 1.0, 1.0]
-DATASET:
-    DATA_DIR: u"./data/humanseg/"
-    IMAGE_TYPE: "rgb"  # choice rgb or rgba
-    NUM_CLASSES: 2
-    TEST_FILE_LIST: u"data/humanseg/list/val.txt"
-    TRAIN_FILE_LIST: u"data/humanseg/list/train.txt"
-    VAL_FILE_LIST: u"data/humanseg/list/val.txt"
-    IGNORE_INDEX: 255
-    SEPARATOR: "|"
-FREEZE:
-    MODEL_FILENAME: u"model"
-    PARAMS_FILENAME: u"params"
-    SAVE_DIR: u"human_freeze_model"
-MODEL:
-    DEFAULT_NORM_TYPE: u"bn"
-    MODEL_NAME: "deeplabv3p"
-    DEEPLAB:
-        BACKBONE: "xception_65"
-TEST:
-    TEST_MODEL: "snapshots/humanseg/aic_v2/final/"
-TRAIN:
-    MODEL_SAVE_DIR: "snapshots/humanseg/aic_v2/"
-    PRETRAINED_MODEL: u"pretrain/xception65_pretrained/"
-    RESUME: False
-    SNAPSHOT_EPOCH: 5
-SOLVER:
-    LR: 0.1
-    NUM_EPOCHS: 40
-    LR_POLICY: "poly"
-    OPTIMIZER: "sgd"

configs/line.yaml

-EVAL_CROP_SIZE: (1536, 576) # (width, height), for unpadding rangescaling and stepscaling
-TRAIN_CROP_SIZE: (1536, 576) # (width, height), for unpadding rangescaling and stepscaling
-AUG:
-    AUG_METHOD: u"unpadding" # choice unpadding rangescaling and stepscaling
-    FIX_RESIZE_SIZE: (1536, 576) # (width, height), for unpadding
-    INF_RESIZE_VALUE: 1280  # for rangescaling
-    MAX_RESIZE_VALUE: 1024  # for rangescaling
-    MIN_RESIZE_VALUE: 1536 # for rangescaling
-    MAX_SCALE_FACTOR: 2.0  # for stepscaling
-    MIN_SCALE_FACTOR: 0.5  # for stepscaling
-    SCALE_STEP_SIZE: 0.25  # for stepscaling
-    MIRROR: True
-    RICH_CROP:
-        ENABLE: False
-        ASPECT_RATIO: 0.33
-        BLUR: True
-        BLUR_RATIO: 0.1
-        FLIP: True
-        FLIP_RATIO: 0.2
-        MAX_ROTATION: 15
-        MIN_AREA_RATIO: 0.5
-        BRIGHTNESS_JITTER_RATIO: 0.5
-        CONTRAST_JITTER_RATIO: 0.5
-        SATURATION_JITTER_RATIO: 0.5
-BATCH_SIZE: 1
-MEAN: [127.5, 127.5, 127.5]
-STD: [127.5, 127.5, 127.5]
-DATASET:
-    DATA_DIR: "./data/line/L4_lane_mask_dataset_app/L4_360_0_2class/"
-    IMAGE_TYPE: "rgb"  # choice rgb or rgba
-    NUM_CLASSES: 2
-    TEST_FILE_LIST: "data/line/L4_lane_mask_dataset_app/L4_360_0_2class/val.txt"
-    TRAIN_FILE_LIST: "data/line/L4_lane_mask_dataset_app/L4_360_0_2class/train.txt"
-    VAL_FILE_LIST: "data/line/L4_lane_mask_dataset_app/L4_360_0_2class/val.txt"
-    SEPARATOR: " "
-    IGNORE_INDEX: 255
-FREEZE:
-    MODEL_FILENAME: "__model__"
-    PARAMS_FILENAME: "__params__"
-    SAVE_DIR: "line_freeze_model"
-MODEL:
-    DEFAULT_NORM_TYPE: "bn"
-    MODEL_NAME: "deeplabv3p"
-    DEEPLAB:
-        BACKBONE: "mobilenet"
-TEST:
-    TEST_MODEL: "snapshots/line_v4/final/"
-TRAIN:
-    MODEL_SAVE_DIR: "snapshots/line_v4/"
-    PRETRAINED_MODEL: u"pretrain/MobileNetV2_pretrained/"
-    RESUME: False
-    SNAPSHOT_EPOCH: 10
-SOLVER:
-    LR: 0.01
-    LR_POLICY: "poly"
-    OPTIMIZER: "sgd"
-    NUM_EPOCHS: 40

configs/unet_pet.yaml

@@ -25,8 +25,6 @@ AUG:
         CONTRAST_JITTER_RATIO: 0.5
         SATURATION_JITTER_RATIO: 0.5
 BATCH_SIZE: 4
-MEAN: [104.008, 116.669, 122.675]
-STD: [1.0, 1.0, 1.0]
 DATASET:
     DATA_DIR: "./dataset/mini_pet/"
     IMAGE_TYPE: "rgb"  # choice rgb or rgba

pdseg/utils/config.py

@@ -22,9 +22,9 @@ cfg = SegConfig()
 
 ########################## 基本配置 ###########################################
 # 均值，图像预处理减去的均值
-cfg.MEAN = [104.008, 116.669, 122.675]
+cfg.MEAN = [0.5, 0.5, 0.5]
 # 标准差，图像预处理除以标准差·
-cfg.STD = [1.000, 1.000, 1.000]
+cfg.STD = [0.5, 0.5, 0.5]
 # 批处理大小
 cfg.BATCH_SIZE = 1
 # 验证时图像裁剪尺寸（宽，高）

test/configs/deeplabv3p_mobilenetv2_line.yaml

-EVAL_CROP_SIZE: (1536, 576) # (width, height), for unpadding rangescaling and stepscaling
-TRAIN_CROP_SIZE: (1536, 576) # (width, height), for unpadding rangescaling and stepscaling
-AUG:
-    AUG_METHOD: "unpadding" # choice unpadding rangescaling and stepscaling
-    FIX_RESIZE_SIZE: (1536, 576) # (width, height), for unpadding
-    INF_RESIZE_VALUE: 1280  # for rangescaling
-    MAX_RESIZE_VALUE: 1024  # for rangescaling
-    MIN_RESIZE_VALUE: 1536 # for rangescaling
-    MAX_SCALE_FACTOR: 2.0  # for stepscaling
-    MIN_SCALE_FACTOR: 0.5  # for stepscaling
-    SCALE_STEP_SIZE: 0.25  # for stepscaling
-    MIRROR: True
-    RICH_CROP:
-        ENABLE: False
-        ASPECT_RATIO: 0.33
-        BLUR: True
-        BLUR_RATIO: 0.1
-        FLIP: True
-        FLIP_RATIO: 0.2
-        MAX_ROTATION: 15
-        MIN_AREA_RATIO: 0.5
-        BRIGHTNESS_JITTER_RATIO: 0.5
-        CONTRAST_JITTER_RATIO: 0.5
-        SATURATION_JITTER_RATIO: 0.5
-BATCH_SIZE: 1
-MEAN: [127.5, 127.5, 127.5]
-STD: [127.5, 127.5, 127.5]
-DATASET:
-    DATA_DIR: "./dataset/line/"
-    IMAGE_TYPE: "rgb"  # choice rgb or rgba
-    NUM_CLASSES: 2
-    TEST_FILE_LIST: "./dataset/line/test_list.txt"
-    SEPARATOR: " "
-    IGNORE_INDEX: 255
-FREEZE:
-    MODEL_FILENAME: "__model__"
-    PARAMS_FILENAME: "__params__"
-    SAVE_DIR: "line_freeze_model"
-MODEL:
-    DEFAULT_NORM_TYPE: "bn"
-    MODEL_NAME: "deeplabv3p"
-    DEEPLAB:
-        BACKBONE: "mobilenet"
-TEST:
-    TEST_MODEL: "./test/models/line/"
-TRAIN:
-    MODEL_SAVE_DIR: "snapshots/line_v4/"
-    PRETRAINED_MODEL: "./models/deeplabv3p_mobilenetv2_init/"
-    RESUME: False
-    SNAPSHOT_EPOCH: 40
-SOLVER:
-    LR: 0.01
-    LR_POLICY: "poly"
-    OPTIMIZER: "sgd"
-    SNAPSHOT: 10

test/configs/deeplabv3p_xception65_cityscapes.yaml

@@ -23,8 +23,6 @@ AUG:
         CONTRAST_JITTER_RATIO: 0.5
         SATURATION_JITTER_RATIO: 0.5
 BATCH_SIZE: 4
-MEAN: [0.5, 0.5, 0.5]
-STD: [0.5, 0.5, 0.5]
 DATASET:
     DATA_DIR: "./dataset/cityscapes/"
     IMAGE_TYPE: "rgb"  # choice rgb or rgba

test/configs/deeplabv3p_xception65_humanseg.yaml

-TRAIN_CROP_SIZE: (513, 513) # (width, height), for unpadding rangescaling and stepscaling
-EVAL_CROP_SIZE: (513, 513) # (width, height), for unpadding rangescaling and stepscaling
-AUG:
-    AUG_METHOD: u"unpadding" # choice unpadding rangescaling and stepscaling
-    FIX_RESIZE_SIZE: (513, 513) # (width, height), for unpadding
-    INF_RESIZE_VALUE: 513  # for rangescaling
-    MAX_RESIZE_VALUE: 400  # for rangescaling
-    MIN_RESIZE_VALUE: 513  # for rangescaling
-    MAX_SCALE_FACTOR: 2.0  # for stepscaling
-    MIN_SCALE_FACTOR: 0.5  # for stepscaling
-    SCALE_STEP_SIZE: 0.25  # for stepscaling
-    MIRROR: True
-    RICH_CROP:
-        ENABLE: True
-        ASPECT_RATIO: 0
-        BLUR: True
-        BLUR_RATIO: 0.1
-        FLIP: True
-        FLIP_RATIO: 0.2
-        MAX_ROTATION: 45
-        MIN_AREA_RATIO: 0
-        BRIGHTNESS_JITTER_RATIO: 0.5
-        CONTRAST_JITTER_RATIO: 0.5
-        SATURATION_JITTER_RATIO: 0.5
-BATCH_SIZE: 24
-MEAN: [104.008, 116.669, 122.675]
-STD: [1.0, 1.0, 1.0]
-DATASET:
-    DATA_DIR: u"./data/humanseg/"
-    IMAGE_TYPE: "rgb"  # choice rgb or rgba
-    NUM_CLASSES: 2
-    TEST_FILE_LIST: u"data/humanseg/list/val.txt"
-    TRAIN_FILE_LIST: u"data/humanseg/list/train.txt"
-    VAL_FILE_LIST: u"data/humanseg/list/val.txt"
-    IGNORE_INDEX: 255
-    SEPARATOR: "|"
-FREEZE:
-    MODEL_FILENAME: "__model__"
-    PARAMS_FILENAME: "__params__"
-    SAVE_DIR: "human_freeze_model"
-MODEL:
-    DEFAULT_NORM_TYPE: u"bn"
-    MODEL_NAME: "deeplabv3p"
-    DEEPLAB:
-        BACKBONE: "xception_65"
-TEST:
-    TEST_MODEL: "snapshots/humanseg/aic_v2/final/"
-TRAIN:
-    MODEL_SAVE_DIR: "snapshots/humanseg/aic_v2/"
-    PRETRAINED_MODEL: "pretrain/xception65_pretrained/"
-    RESUME: False
-    SNAPSHOT_EPOCH: 5
-SOLVER:
-    LR: 0.1
-    NUM_EPOCHS: 40
-    LR_POLICY: "poly"
-    OPTIMIZER: "sgd"

test/configs/unet_coco.yaml

@@ -23,10 +23,6 @@ AUG:
         CONTRAST_JITTER_RATIO: 0.5
         SATURATION_JITTER_RATIO: 0.5
 BATCH_SIZE: 10
-#MEAN: [104.008, 116.669, 122.675]
-#STD: [1.0, 1.0, 1.0]
-MEAN: [127.5, 127.5, 127.5]
-STD: [127.5, 127.5, 127.5]
 DATASET:
     DATA_DIR: "./data/COCO2014/"
     IMAGE_TYPE: "rgb"  # choice rgb or rgba

test/configs/unet_pet.yaml

@@ -25,8 +25,6 @@ AUG:
         CONTRAST_JITTER_RATIO: 0.5
         SATURATION_JITTER_RATIO: 0.5
 BATCH_SIZE: 6
-MEAN: [104.008, 116.669, 122.675]
-STD: [1.0, 1.0, 1.0]
 DATASET:
     DATA_DIR: "./dataset/pet/"
     IMAGE_TYPE: "rgb"  # choice rgb or rgba