add backbone (e8b15150) · Commits · IntelligentTEAM / ECCV 2020 Domain Adaption

configs/resnet101_clipart.yaml

0 → 100644

+19 −0

Original line number	Diff line number	Diff line
		MODEL:
		BACKBONE:
		NAME: 'resnet101'
		ROI_BOX_HEAD:
		NUM_CLASSES: 21
		BOX_PREDICTOR: 'resnet101_predictor'
		DATASETS:
		TRAINS: ['voc_2007_trainval', 'voc_2012_trainval']
		TESTS: ['voc_clipart_traintest']
		SOLVER:
		EPOCHS: 20
		STEPS: (16, 18)
		LR: 1e-5
		WEIGHT_DECAY: 0.0001
		BATCH_SIZE: 1
		TEST:
		EVAL_TYPES: ['voc']

		WORK_DIR: './work_dir/clipart'
		No newline at end of file

configs/vgg16_cityscapes.yaml

+1 −1

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		MODEL:
		BACKBONE:
		NAME: 'VGG16'
		NAME: 'vgg16'
		ROI_BOX_HEAD:
		NUM_CLASSES: 9
		BOX_PREDICTOR: 'vgg16_predictor'

detection/config/defaults.py

+4 −2

Original line number	Diff line number	Diff line
		@@ -16,7 +16,7 @@ _C.DATASETS.TARGETS = ()
		# Backbone options
		# ---------------------------------------------------------------------------- #
		_C.MODEL.BACKBONE = CN()
		_C.MODEL.BACKBONE.NAME = "VGG16"
		_C.MODEL.BACKBONE.NAME = "vgg16"

		# -----------------------------------------------------------------------------
		# INPUT options
		@@ -39,6 +39,7 @@ _C.MODEL.RPN = CN()
		_C.MODEL.RPN.ANCHOR_SIZES = (32, 64, 128, 256, 512)
		_C.MODEL.RPN.ASPECT_RATIOS = (0.5, 1, 2)
		_C.MODEL.RPN.ANCHOR_STRIDE = 16
		_C.MODEL.RPN.NUM_CHANNELS = 512
		_C.MODEL.RPN.BATCH_SIZE_PER_IMAGE = 256
		_C.MODEL.RPN.PRE_NMS_TOP_N_TRAIN = 12000
		_C.MODEL.RPN.PRE_NMS_TOP_N_TEST = 6000
		@@ -61,7 +62,8 @@ _C.MODEL.ROI_HEADS.DETECTIONS_PER_IMG = 100
		_C.MODEL.ROI_BOX_HEAD = CN()
		_C.MODEL.ROI_BOX_HEAD.NUM_CLASSES = 9
		_C.MODEL.ROI_BOX_HEAD.POOL_SPATIAL_SCALE = 1.0 / 16
		_C.MODEL.ROI_BOX_HEAD.POOLER_RESOLUTION = 7
		_C.MODEL.ROI_BOX_HEAD.POOL_RESOLUTION = 7
		_C.MODEL.ROI_BOX_HEAD.POOL_TYPE = "align"
		_C.MODEL.ROI_BOX_HEAD.BOX_PREDICTOR = 'vgg16_predictor'

		# ---------------------------------------------------------------------------- #

detection/data/build.py

+2 −18

Original line number	Diff line number	Diff line
		@@ -11,103 +11,86 @@ DATASETS = {
		'cityscapes_train': {
		'ann_file': '/data7/lufficc/cityscapes/cityscapes_coco_train.json',
		'root': cityscapes_images_dir,
		'train': True,
		},

		'cityscapes_val': {
		'ann_file': '/data7/lufficc/cityscapes/cityscapes_coco_val.json',
		'root': cityscapes_images_dir,
		'train': False,
		},

		'cityscapes_test': {
		'ann_file': '/data7/lufficc/cityscapes/cityscapes_coco_test.json',
		'root': cityscapes_images_dir,
		'train': False,
		},

		'foggy_cityscapes_train': {
		'ann_file': '/data7/lufficc/cityscapes/foggy_cityscapes_coco_train.json',
		'root': foggy_cityscapes_images_dir,
		'train': True,
		},

		'foggy_cityscapes_val': {
		'ann_file': '/data7/lufficc/cityscapes/foggy_cityscapes_coco_val.json',
		'root': foggy_cityscapes_images_dir,
		'train': False,
		},

		'foggy_cityscapes_test': {
		'ann_file': '/data7/lufficc/cityscapes/foggy_cityscapes_coco_test.json',
		'root': foggy_cityscapes_images_dir,
		'train': False,
		},
		"coco_2017_train": {
		"ann_file": "/data7/lufficc/coco/annotations/instances_train2017.json",
		"root": "/data7/lufficc/coco/train2017",
		'train': True,
		},
		"coco_2017_val": {
		"ann_file": "/data7/lufficc/coco/annotations/instances_val2017.json",
		"root": "/data7/lufficc/coco/val2017",
		'train': False,
		},

		'voc_2007_trainval': {
		'root': '/data7/lufficc/voc/VOCdevkit/VOC2007',
		'split': 'trainval',
		'train': True,
		},

		'voc_2012_trainval': {
		'root': '/data7/lufficc/voc/VOCdevkit/VOC2012',
		'split': 'trainval',
		'train': True,
		},

		'voc_2007_test': {
		'root': '/data7/lufficc/voc/VOCdevkit/VOC2007',
		'split': 'test',
		'train': False,
		},

		'voc_watercolor_train': {
		'root': '/data7/lufficc/cross_domain_detection/watercolor',
		'split': 'train',
		'train': True,
		},
		'voc_watercolor_test': {
		'root': '/data7/lufficc/cross_domain_detection/watercolor',
		'split': 'test',
		'train': False,
		},

		'voc_comic_train': {
		'root': '/data7/lufficc/cross_domain_detection/comic',
		'split': 'train',
		'train': True,
		},
		'voc_comic_test': {
		'root': '/data7/lufficc/cross_domain_detection/comic',
		'split': 'test',
		'train': False,
		},
		'voc_clipart_train': {
		'root': '/data7/lufficc/cross_domain_detection/clipart',
		'split': 'train',
		'train': True,
		},
		'voc_clipart_test': {
		'root': '/data7/lufficc/cross_domain_detection/clipart',
		'split': 'test',
		'train': False,
		},
		'voc_clipart_traintest': {
		'root': '/data7/lufficc/cross_domain_detection/clipart',
		'split': 'traintest',
		'train': False,
		},

		}


		@@ -117,6 +100,7 @@ def build_datasets(names, is_train=True):
		for name in names:
		cfg = DATASETS[name].copy()
		cfg['dataset_name'] = name
		cfg['train'] = is_train
		if 'cityscapes' in name:
		dataset = CityscapeDataset(**cfg)
		elif 'coco' in name:

detection/data/datasets/cityscape.py

+1 −1

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		@@ -44,6 +44,6 @@ test_transforms = [
		class CityscapeDataset(COCODataset):
		CLASSES = ('__background__', 'person', 'rider', 'car', 'truck', 'bus', 'train', 'motorcycle', 'bicycle',)

		def __init__(self, train=True, **kwargs):
		def __init__(self, train, **kwargs):
		transforms = train_transforms if train else test_transforms
		super().__init__(transforms=transforms, remove_empty=train, **kwargs)