DeticChatGPT / configs /Base-DeformDETR_L_R50_4x.yaml
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Duplicate from akhaliq/Detic
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MODEL:
META_ARCHITECTURE: "DeformableDetr"
WEIGHTS: "detectron2://ImageNetPretrained/torchvision/R-50.pkl"
PIXEL_MEAN: [123.675, 116.280, 103.530]
PIXEL_STD: [58.395, 57.120, 57.375]
MASK_ON: False
RESNETS:
DEPTH: 50
STRIDE_IN_1X1: False
OUT_FEATURES: ["res3", "res4", "res5"]
DETR:
CLS_WEIGHT: 2.0
GIOU_WEIGHT: 2.0
L1_WEIGHT: 5.0
NUM_OBJECT_QUERIES: 300
DIM_FEEDFORWARD: 1024
WITH_BOX_REFINE: True
TWO_STAGE: True
NUM_CLASSES: 1203
USE_FED_LOSS: True
DATASETS:
TRAIN: ("lvis_v1_train",)
TEST: ("lvis_v1_val",)
SOLVER:
CHECKPOINT_PERIOD: 10000000
USE_CUSTOM_SOLVER: True
IMS_PER_BATCH: 32
BASE_LR: 0.0002
STEPS: (150000,)
MAX_ITER: 180000
WARMUP_FACTOR: 1.0
WARMUP_ITERS: 10
WEIGHT_DECAY: 0.0001
OPTIMIZER: "ADAMW"
BACKBONE_MULTIPLIER: 0.1
CLIP_GRADIENTS:
ENABLED: True
CLIP_TYPE: "full_model"
CLIP_VALUE: 0.01
NORM_TYPE: 2.0
CUSTOM_MULTIPLIER: 0.1
CUSTOM_MULTIPLIER_NAME: ['reference_points', 'sampling_offsets']
INPUT:
FORMAT: "RGB"
MIN_SIZE_TRAIN: (480, 512, 544, 576, 608, 640, 672, 704, 736, 768, 800)
CROP:
ENABLED: True
TYPE: "absolute_range"
SIZE: (384, 600)
CUSTOM_AUG: "DETR"
TEST:
DETECTIONS_PER_IMAGE: 300
DATALOADER:
FILTER_EMPTY_ANNOTATIONS: False
NUM_WORKERS: 4
SAMPLER_TRAIN: "RepeatFactorTrainingSampler"
REPEAT_THRESHOLD: 0.001
OUTPUT_DIR: "output/Detic/auto"
VERSION: 2