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# -*- coding: utf-8 -*-
from detectron2.config import LazyCall as L
from detectron2.layers import ShapeSpec
from detectron2.modeling.meta_arch import RetinaNet
from detectron2.modeling.anchor_generator import DefaultAnchorGenerator
from detectron2.modeling.backbone.fpn import LastLevelP6P7
from detectron2.modeling.backbone import BasicStem, FPN, ResNet
from detectron2.modeling.box_regression import Box2BoxTransform
from detectron2.modeling.matcher import Matcher
from detectron2.modeling.meta_arch.retinanet import RetinaNetHead
model = L(RetinaNet)(
backbone=L(FPN)(
bottom_up=L(ResNet)(
stem=L(BasicStem)(in_channels=3, out_channels=64, norm="FrozenBN"),
stages=L(ResNet.make_default_stages)(
depth=50,
stride_in_1x1=True,
norm="FrozenBN",
),
out_features=["res3", "res4", "res5"],
),
in_features=["res3", "res4", "res5"],
out_channels=256,
top_block=L(LastLevelP6P7)(in_channels=2048, out_channels="${..out_channels}"),
),
head=L(RetinaNetHead)(
input_shape=[ShapeSpec(channels=256)],
num_classes="${..num_classes}",
conv_dims=[256, 256, 256, 256],
prior_prob=0.01,
num_anchors=9,
),
anchor_generator=L(DefaultAnchorGenerator)(
sizes=[[x, x * 2 ** (1.0 / 3), x * 2 ** (2.0 / 3)] for x in [32, 64, 128, 256, 512]],
aspect_ratios=[0.5, 1.0, 2.0],
strides=[8, 16, 32, 64, 128],
offset=0.0,
),
box2box_transform=L(Box2BoxTransform)(weights=[1.0, 1.0, 1.0, 1.0]),
anchor_matcher=L(Matcher)(
thresholds=[0.4, 0.5], labels=[0, -1, 1], allow_low_quality_matches=True
),
num_classes=80,
head_in_features=["p3", "p4", "p5", "p6", "p7"],
focal_loss_alpha=0.25,
focal_loss_gamma=2.0,
pixel_mean=[103.530, 116.280, 123.675],
pixel_std=[1.0, 1.0, 1.0],
input_format="BGR",
)
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