Detic / configs /Base-C2_L_R5021k_640b64_4x.yaml
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Duplicate from akhaliq/Detic
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MODEL:
META_ARCHITECTURE: "CustomRCNN"
MASK_ON: True
PROPOSAL_GENERATOR:
NAME: "CenterNet"
WEIGHTS: "models/resnet50_miil_21k.pkl"
BACKBONE:
NAME: build_p67_timm_fpn_backbone
TIMM:
BASE_NAME: resnet50_in21k
FPN:
IN_FEATURES: ["layer3", "layer4", "layer5"]
PIXEL_MEAN: [123.675, 116.280, 103.530]
PIXEL_STD: [58.395, 57.12, 57.375]
ROI_HEADS:
NAME: DeticCascadeROIHeads
IN_FEATURES: ["p3", "p4", "p5"]
IOU_THRESHOLDS: [0.6]
NUM_CLASSES: 1203
SCORE_THRESH_TEST: 0.02
NMS_THRESH_TEST: 0.5
ROI_BOX_CASCADE_HEAD:
IOUS: [0.6, 0.7, 0.8]
ROI_BOX_HEAD:
NAME: "FastRCNNConvFCHead"
NUM_FC: 2
POOLER_RESOLUTION: 7
CLS_AGNOSTIC_BBOX_REG: True
MULT_PROPOSAL_SCORE: True
USE_SIGMOID_CE: True
USE_FED_LOSS: True
ROI_MASK_HEAD:
NAME: "MaskRCNNConvUpsampleHead"
NUM_CONV: 4
POOLER_RESOLUTION: 14
CLS_AGNOSTIC_MASK: True
CENTERNET:
NUM_CLASSES: 1203
REG_WEIGHT: 1.
NOT_NORM_REG: True
ONLY_PROPOSAL: True
WITH_AGN_HM: True
INFERENCE_TH: 0.0001
PRE_NMS_TOPK_TRAIN: 4000
POST_NMS_TOPK_TRAIN: 2000
PRE_NMS_TOPK_TEST: 1000
POST_NMS_TOPK_TEST: 256
NMS_TH_TRAIN: 0.9
NMS_TH_TEST: 0.9
POS_WEIGHT: 0.5
NEG_WEIGHT: 0.5
IGNORE_HIGH_FP: 0.85
DATASETS:
TRAIN: ("lvis_v1_train",)
TEST: ("lvis_v1_val",)
DATALOADER:
SAMPLER_TRAIN: "RepeatFactorTrainingSampler"
REPEAT_THRESHOLD: 0.001
NUM_WORKERS: 8
TEST:
DETECTIONS_PER_IMAGE: 300
SOLVER:
LR_SCHEDULER_NAME: "WarmupCosineLR"
CHECKPOINT_PERIOD: 1000000000
WARMUP_ITERS: 10000
WARMUP_FACTOR: 0.0001
USE_CUSTOM_SOLVER: True
OPTIMIZER: "ADAMW"
MAX_ITER: 90000
IMS_PER_BATCH: 64
BASE_LR: 0.0002
CLIP_GRADIENTS:
ENABLED: True
INPUT:
FORMAT: RGB
CUSTOM_AUG: EfficientDetResizeCrop
TRAIN_SIZE: 640
OUTPUT_DIR: "./output/Detic/auto"
EVAL_PROPOSAL_AR: False
VERSION: 2
FP16: True