diff --git a/configs/cityscape.yaml b/configs/cityscape.yaml index 6b304c04760d4dd549038d03a2bf77e8c0f68a4a..0650d58a068e19c6cfe36f2d01c8e37dd5935045 100644 --- a/configs/cityscape.yaml +++ b/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 diff --git a/configs/coco.yaml b/configs/coco.yaml index eaf50eb9a901d4b7de9c79231ec8dbd904f016e6..fe0cd0ecd549623fe0fff9b51a8fd03a8dcf5b91 100644 --- a/configs/coco.yaml +++ b/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 diff --git a/configs/humanseg.yaml b/configs/humanseg.yaml deleted file mode 100644 index e2a81de49218ecf5655fee25b74eb367b2f9f7d5..0000000000000000000000000000000000000000 --- a/configs/humanseg.yaml +++ /dev/null @@ -1,57 +0,0 @@ -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" diff --git a/configs/line.yaml b/configs/line.yaml deleted file mode 100644 index fe0d195cd27ee9e9493d322ab1499007c6d785d8..0000000000000000000000000000000000000000 --- a/configs/line.yaml +++ /dev/null @@ -1,57 +0,0 @@ -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 diff --git a/configs/unet_pet.yaml b/configs/unet_pet.yaml index 63c874f97235dbc2652637c0fe9875e3e3e183d9..23bd68d5918fe89c3771cdc2e46871918b54e29c 100644 --- a/configs/unet_pet.yaml +++ b/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 diff --git a/pdseg/utils/config.py b/pdseg/utils/config.py index 8d4deb076fd15d808836a0225a8f35075249a7f1..0f11284df315d4c0b8a497aaad64b0fbe4bab9f9 100644 --- a/pdseg/utils/config.py +++ b/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） diff --git a/test/configs/deeplabv3p_mobilenetv2_line.yaml b/test/configs/deeplabv3p_mobilenetv2_line.yaml deleted file mode 100644 index 836428530b76f9af5601a7e17b0b6e7e696c72a7..0000000000000000000000000000000000000000 --- a/test/configs/deeplabv3p_mobilenetv2_line.yaml +++ /dev/null @@ -1,55 +0,0 @@ -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 diff --git a/test/configs/deeplabv3p_xception65_cityscapes.yaml b/test/configs/deeplabv3p_xception65_cityscapes.yaml index c699045bce2fac17afa31c1deace209f7834bc8e..612ac31bb304081a6c8900ff08d3ef61df62fbdf 100644 --- a/test/configs/deeplabv3p_xception65_cityscapes.yaml +++ b/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 diff --git a/test/configs/deeplabv3p_xception65_humanseg.yaml b/test/configs/deeplabv3p_xception65_humanseg.yaml deleted file mode 100644 index 883b06471a3fe7dad0205e5ee89ba43f16727c52..0000000000000000000000000000000000000000 --- a/test/configs/deeplabv3p_xception65_humanseg.yaml +++ /dev/null @@ -1,57 +0,0 @@ -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" diff --git a/test/configs/unet_coco.yaml b/test/configs/unet_coco.yaml index 157a1b91823e601790aa0e0bb3696632cb90db88..dd8c94d63b9e01d1f332920b6d56354e9667e8a6 100644 --- a/test/configs/unet_coco.yaml +++ b/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 diff --git a/test/configs/unet_pet.yaml b/test/configs/unet_pet.yaml index 1c73686bba91a6f9c7cc2dd288eeba1c7cfea82d..e561e463bbdaddbe532d47a862c3e29095909f95 100644 --- a/test/configs/unet_pet.yaml +++ b/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