Ailusion-VTON-DEMO-v1
/
preprocess
/humanparsing
/mhp_extension
/detectron2
/configs
/my_Base-RCNN-FPN.yaml
MODEL: | |
META_ARCHITECTURE: "GeneralizedRCNN" | |
BACKBONE: | |
NAME: "build_resnet_fpn_backbone" | |
RESNETS: | |
OUT_FEATURES: ["res2", "res3", "res4", "res5"] | |
FPN: | |
IN_FEATURES: ["res2", "res3", "res4", "res5"] | |
ANCHOR_GENERATOR: | |
SIZES: [[32], [64], [128], [256], [512]] # One size for each in feature map | |
ASPECT_RATIOS: [[0.5, 1.0, 2.0]] # Three aspect ratios (same for all in feature maps) | |
RPN: | |
IN_FEATURES: ["p2", "p3", "p4", "p5", "p6"] | |
PRE_NMS_TOPK_TRAIN: 2000 # Per FPN level | |
PRE_NMS_TOPK_TEST: 1000 # Per FPN level | |
# Detectron1 uses 2000 proposals per-batch, | |
# (See "modeling/rpn/rpn_outputs.py" for details of this legacy issue) | |
# which is approximately 1000 proposals per-image since the default batch size for FPN is 2. | |
POST_NMS_TOPK_TRAIN: 1000 | |
POST_NMS_TOPK_TEST: 1000 | |
ROI_HEADS: | |
NAME: "StandardROIHeads" | |
IN_FEATURES: ["p2", "p3", "p4", "p5"] | |
ROI_BOX_HEAD: | |
NAME: "FastRCNNConvFCHead" | |
NUM_FC: 2 | |
POOLER_RESOLUTION: 7 | |
ROI_MASK_HEAD: | |
NAME: "MaskRCNNConvUpsampleHead" | |
NUM_CONV: 4 | |
POOLER_RESOLUTION: 14 | |
DATASETS: | |
TRAIN: ("coco_2017_train",) | |
TEST: ("coco_2017_val",) | |
SOLVER: | |
IMS_PER_BATCH: 2 | |
BASE_LR: 0.02 | |
STEPS: (60000, 80000) | |
MAX_ITER: 90000 | |
INPUT: | |
MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800) | |
VERSION: 2 | |