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ALBUMENTATION_AUG_PATH: null
ANNOT_PATH: ./dataset/coco_2/coco_data/coco_annotations.json
IMAGE_PATH: ./dataset/coco_2/coco_data
TRAIN_MODEL_NAME: generic_new_baselines/mask_rcnn_regnety_4gf_dds_FPN_200ep_LSJ.py
dataloader:
evaluator: {_target_: detectron2.evaluation.COCOEvaluator, dataset_name: coco_2017_val}
test:
_target_: detectron2.data.build_detection_test_loader
dataset: {_target_: detectron2.data.get_detection_dataset_dicts, filter_empty: false, names: coco_2017_val}
mapper:
_target_: detectron2.data.DatasetMapper
augmentations:
- {_target_: detectron2.data.transforms.ResizeShortestEdge, max_size: 1333, short_edge_length: 800}
image_format: BGR
is_train: false
num_workers: 4
train:
_target_: detectron2.data.build_detection_train_loader
dataset: {_target_: detectron2.data.get_detection_dataset_dicts, names: coco_2017_train}
mapper:
_target_: detectron2.data.DatasetMapper
augmentations:
- {_target_: detectron2.data.transforms.ResizeScale, max_scale: 2.0, min_scale: 0.1, target_height: 1024, target_width: 1024}
- _target_: detectron2.data.transforms.FixedSizeCrop
crop_size: [1024, 1024]
- {_target_: detectron2.data.transforms.RandomFlip, horizontal: true}
image_format: BGR
is_train: true
recompute_boxes: true
use_instance_mask: true
num_workers: 4
total_batch_size: 64
lr_multiplier:
_target_: detectron2.solver.WarmupParamScheduler
scheduler:
_target_: fvcore.common.param_scheduler.MultiStepParamScheduler
milestones: [163889, 177546]
num_updates: 184375
values: [1.0, 0.1, 0.01]
warmup_factor: 0.067
warmup_length: 0.002711864406779661
model:
_target_: detectron2.modeling.GeneralizedRCNN
backbone:
_target_: detectron2.modeling.FPN
bottom_up:
_target_: detectron2.modeling.backbone.RegNet
block_class: !!python/name:detectron2.modeling.backbone.regnet.ResBottleneckBlock ''
depth: 23
group_width: 40
norm: SyncBN
out_features: [s1, s2, s3, s4]
stem_class: !!python/name:detectron2.modeling.backbone.regnet.SimpleStem ''
stem_width: 32
w_0: 96
w_a: 38.65
w_m: 2.43
in_features: [s1, s2, s3, s4]
norm: SyncBN
out_channels: 256
top_block: {_target_: detectron2.modeling.backbone.fpn.LastLevelMaxPool}
input_format: BGR
pixel_mean: [103.53, 116.28, 123.675]
pixel_std: [57.375, 57.12, 58.395]
proposal_generator:
_target_: detectron2.modeling.proposal_generator.RPN
anchor_generator:
_target_: detectron2.modeling.anchor_generator.DefaultAnchorGenerator
aspect_ratios: [0.5, 1.0, 2.0]
offset: 0.0
sizes:
- [32]
- [64]
- [128]
- [256]
- [512]
strides: [4, 8, 16, 32, 64]
anchor_matcher:
_target_: detectron2.modeling.matcher.Matcher
allow_low_quality_matches: true
labels: [0, -1, 1]
thresholds: [0.3, 0.7]
batch_size_per_image: 256
box2box_transform:
_target_: detectron2.modeling.box_regression.Box2BoxTransform
weights: [1.0, 1.0, 1.0, 1.0]
head:
_target_: detectron2.modeling.proposal_generator.StandardRPNHead
conv_dims: [-1, -1]
in_channels: 256
num_anchors: 3
in_features: [p2, p3, p4, p5, p6]
nms_thresh: 0.7
positive_fraction: 0.5
post_nms_topk: [1000, 1000]
pre_nms_topk: [2000, 1000]
roi_heads:
_target_: detectron2.modeling.StandardROIHeads
batch_size_per_image: 512
box_head:
_target_: detectron2.modeling.roi_heads.FastRCNNConvFCHead
conv_dims: [256, 256, 256, 256]
conv_norm: &id001 !!python/name:detectron2._cfg_loaderad5b.mask_rcnn_R_50_FPN_100ep_LSJ.py.%3Clambda%3E ''
fc_dims: [1024]
input_shape: !!python/object/new:detectron2.layers.shape_spec.ShapeSpec [256, 7, 7, null]
box_in_features: [p2, p3, p4, p5]
box_pooler:
_target_: detectron2.modeling.poolers.ROIPooler
output_size: 7
pooler_type: ROIAlignV2
sampling_ratio: 0
scales: [0.25, 0.125, 0.0625, 0.03125]
box_predictor:
_target_: detectron2.modeling.FastRCNNOutputLayers
box2box_transform:
_target_: detectron2.modeling.box_regression.Box2BoxTransform
weights: [10, 10, 5, 5]
input_shape: !!python/object/new:detectron2.layers.shape_spec.ShapeSpec [1024, null, null, null]
num_classes: 80
test_score_thresh: 0.05
mask_head:
_target_: detectron2.modeling.roi_heads.MaskRCNNConvUpsampleHead
conv_dims: [256, 256, 256, 256, 256]
conv_norm: *id001
input_shape: !!python/object/new:detectron2.layers.shape_spec.ShapeSpec [256, 14, 14, null]
num_classes: 80
mask_in_features: [p2, p3, p4, p5]
mask_pooler:
_target_: detectron2.modeling.poolers.ROIPooler
output_size: 14
pooler_type: ROIAlignV2
sampling_ratio: 0
scales: [0.25, 0.125, 0.0625, 0.03125]
num_classes: 80
positive_fraction: 0.25
proposal_matcher:
_target_: detectron2.modeling.matcher.Matcher
allow_low_quality_matches: false
labels: [0, 1]
thresholds: [0.5]
optimizer:
_target_: torch.optim.SGD
lr: 0.1
momentum: 0.9
params: {_target_: detectron2.solver.get_default_optimizer_params, weight_decay_norm: 0.0}
weight_decay: 4.0e-05
train:
amp: {enabled: true}
checkpointer: {max_to_keep: 100, period: 5000}
cudnn_benchmark: true
ddp: {broadcast_buffers: false, find_unused_parameters: false, fp16_compression: true}
device: cuda
eval_period: 5000
init_checkpoint: ''
log_period: 20
max_iter: 184375
output_dir: ./output