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hubconf.py
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# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from models.detr import DETR
from models.backbone import Backbone, Joiner
from models.transformer import Transformer
from models.position_encoding import PositionEmbeddingSine
dependencies = ['torch', 'torchvision']
def _make_detr(backbone_name: str, dilation=False, num_classes=91):
hidden_dim = 256
backbone = Backbone(backbone_name, train_backbone=True,
return_interm_layers=False, dilation=dilation)
pos_enc = PositionEmbeddingSine(hidden_dim // 2, normalize=True)
backbone_with_pos_enc = Joiner(backbone, pos_enc)
backbone_with_pos_enc.num_channels = backbone.num_channels
transformer = Transformer(d_model=hidden_dim, return_intermediate_dec=True)
return DETR(backbone_with_pos_enc, transformer, num_classes=num_classes, num_queries=100)
def detr_resnet50(pretrained=False, num_classes=91):
"""
DETR R50 with 6 encoder and 6 decoder layers.
Achieves 42/62.4 AP/AP50 on COCO val5k.
"""
model = _make_detr('resnet50', dilation=False, num_classes=num_classes)
if pretrained:
checkpoint = torch.hub.load_state_dict_from_url(
url='https://dl.fbaipublicfiles.com/detr/detr-r50-e632da11.pth',
map_location='cpu',
check_hash=True)
model.load_state_dict(checkpoint['model'])
return model
def detr_resnet50_dc5(pretrained=False, num_classes=91):
"""
DETR-DC5 R50 with 6 encoder and 6 decoder layers.
The last block of ResNet-50 has dilation to increase
output resolution.
Achieves 43.3/63.1 AP/AP50 on COCO val5k.
"""
model = _make_detr('resnet50', dilation=True, num_classes=num_classes)
if pretrained:
checkpoint = torch.hub.load_state_dict_from_url(
url='https://dl.fbaipublicfiles.com/detr/detr-r50-dc5-f0fb7ef5.pth',
map_location='cpu',
check_hash=True)
model.load_state_dict(checkpoint['model'])
return model
def detr_resnet101(pretrained=False, num_classes=91):
"""
DETR-DC5 R101 with 6 encoder and 6 decoder layers.
Achieves 43.5/63.8 AP/AP50 on COCO val5k.
"""
model = _make_detr('resnet101', dilation=False, num_classes=num_classes)
if pretrained:
checkpoint = torch.hub.load_state_dict_from_url(
url='https://dl.fbaipublicfiles.com/detr/detr-r101-2c7b67e5.pth',
map_location='cpu',
check_hash=True)
model.load_state_dict(checkpoint['model'])
return model
def detr_resnet101_dc5(pretrained=False, num_classes=91):
"""
DETR-DC5 R101 with 6 encoder and 6 decoder layers.
The last block of ResNet-101 has dilation to increase
output resolution.
Achieves 44.9/64.7 AP/AP50 on COCO val5k.
"""
model = _make_detr('resnet101', dilation=True, num_classes=num_classes)
if pretrained:
checkpoint = torch.hub.load_state_dict_from_url(
url='https://dl.fbaipublicfiles.com/detr/detr-r101-dc5-a2e86def.pth',
map_location='cpu',
check_hash=True)
model.load_state_dict(checkpoint['model'])
return model