/dports/misc/py-gluoncv/gluon-cv-0.9.0/gluoncv/model_zoo/ssd/ |
H A D | presets.py | 57 pretrained_base=pretrained_base, **kwargs) 83 pretrained_base=pretrained_base, **kwargs) 120 pretrained_base=pretrained_base, **kwargs) 150 pretrained_base=pretrained_base, **kwargs) 176 pretrained_base=pretrained_base, **kwargs) 250 pretrained_base=pretrained_base, **kwargs) 283 pretrained_base=pretrained_base, **kwargs) 365 pretrained_base=pretrained_base, **kwargs) 398 pretrained_base=pretrained_base, **kwargs) 480 pretrained_base=pretrained_base, **kwargs) [all …]
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H A D | ssd.py | 355 dataset, pretrained=False, pretrained_base=True, ctx=mx.cpu(), argument 413 pretrained_base = False if pretrained else pretrained_base 416 pretrained=pretrained_base, classes=classes, ctx=ctx, root=root, 425 classes, dataset, pretrained_base, **kwargs): argument 458 pretrained_base=pretrained_base,
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/dports/misc/py-gluoncv/gluon-cv-0.9.0/gluoncv/model_zoo/center_net/ |
H A D | center_net.py | 348 pretrained_base = False if pretrained else pretrained_base 378 pretrained_base = False if pretrained else pretrained_base 408 pretrained_base = False if pretrained else pretrained_base 438 pretrained_base = False if pretrained else pretrained_base 468 pretrained_base = False if pretrained else pretrained_base 498 pretrained_base = False if pretrained else pretrained_base 528 pretrained_base = False if pretrained else pretrained_base 558 pretrained_base = False if pretrained else pretrained_base 588 pretrained_base = False if pretrained else pretrained_base 618 pretrained_base = False if pretrained else pretrained_base [all …]
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H A D | duc_mobilenet.py | 37 pretrained_base=True, norm_layer=nn.BatchNorm, norm_kwargs=None, **kwargs): argument 42 net = get_model(base_network, pretrained=pretrained_base) 75 net = DUCMobilenet(base_network=base_network, pretrained_base=pretrained, **kwargs)
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H A D | deconv_resnet.py | 74 pretrained_base=True, norm_layer=nn.BatchNorm, norm_kwargs=None, argument 78 net = get_model(base_network, pretrained=pretrained_base) 188 net = DeconvResnet(base_network=base_network, pretrained_base=pretrained,
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/dports/misc/py-gluoncv/gluon-cv-0.9.0/gluoncv/model_zoo/rcnn/faster_rcnn/ |
H A D | predefined_models.py | 54 pretrained_base = False if pretrained else pretrained_base 104 pretrained_base = False if pretrained else pretrained_base 156 pretrained_base = False if pretrained else pretrained_base 216 pretrained_base = False if pretrained else pretrained_base 277 pretrained_base = False if pretrained else pretrained_base 393 pretrained_base = False if pretrained else pretrained_base 442 pretrained_base = False if pretrained else pretrained_base 494 pretrained_base = False if pretrained else pretrained_base 554 pretrained_base = False if pretrained else pretrained_base 616 pretrained_base = False if pretrained else pretrained_base [all …]
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/dports/misc/py-gluoncv/gluon-cv-0.9.0/gluoncv/model_zoo/rcnn/mask_rcnn/ |
H A D | predefined_models.py | 21 def mask_rcnn_resnet50_v1b_coco(pretrained=False, pretrained_base=True, **kwargs): argument 46 pretrained_base = False if pretrained else pretrained_base 71 def mask_rcnn_fpn_resnet50_v1b_coco(pretrained=False, pretrained_base=True, **kwargs): argument 96 pretrained_base = False if pretrained else pretrained_base 126 def mask_rcnn_resnet101_v1d_coco(pretrained=False, pretrained_base=True, **kwargs): argument 151 pretrained_base = False if pretrained else pretrained_base 201 pretrained_base = False if pretrained else pretrained_base 263 pretrained_base = False if pretrained else pretrained_base 321 pretrained_base = False if pretrained else pretrained_base 386 pretrained_base = False if pretrained else pretrained_base [all …]
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/dports/misc/py-gluoncv/gluon-cv-0.9.0/gluoncv/model_zoo/action_recognition/ |
H A D | actionrec_vgg16.py | 39 def __init__(self, nclass, pretrained_base=True, argument 49 pretrained_model = vgg16(pretrained=pretrained_base, **kwargs) 69 def vgg16_ucf101(nclass=101, pretrained=False, pretrained_base=True, argument 94 pretrained_base=pretrained_base, 110 def vgg16_hmdb51(nclass=51, pretrained=False, pretrained_base=True, argument 135 pretrained_base=pretrained_base, 151 def vgg16_kinetics400(nclass=400, pretrained=False, pretrained_base=True, argument 176 pretrained_base=pretrained_base, 192 def vgg16_sthsthv2(nclass=174, pretrained=False, pretrained_base=True, argument 217 pretrained_base=pretrained_base,
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H A D | actionrec_inceptionv3.py | 42 def __init__(self, nclass, pretrained_base=True, argument 52 pretrained_model = inception_v3(pretrained=pretrained_base, partial_bn=partial_bn, **kwargs) 72 def inceptionv3_ucf101(nclass=101, pretrained=False, pretrained_base=True, argument 100 pretrained_base=pretrained_base, 116 def inceptionv3_hmdb51(nclass=51, pretrained=False, pretrained_base=True, argument 144 pretrained_base=pretrained_base, 160 def inceptionv3_kinetics400(nclass=400, pretrained=False, pretrained_base=True, argument 188 pretrained_base=pretrained_base, 204 def inceptionv3_sthsthv2(nclass=174, pretrained=False, pretrained_base=True, argument 232 pretrained_base=pretrained_base,
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H A D | actionrec_inceptionv1.py | 42 def __init__(self, nclass, pretrained_base=True, argument 52 pretrained_model = googlenet(pretrained=pretrained_base, partial_bn=partial_bn, **kwargs) 113 def inceptionv1_ucf101(nclass=101, pretrained=False, pretrained_base=True, argument 141 pretrained_base=pretrained_base, 157 def inceptionv1_hmdb51(nclass=51, pretrained=False, pretrained_base=True, argument 185 pretrained_base=pretrained_base, 201 def inceptionv1_kinetics400(nclass=400, pretrained=False, pretrained_base=True, argument 229 pretrained_base=pretrained_base, 245 def inceptionv1_sthsthv2(nclass=174, pretrained=False, pretrained_base=True, argument 273 pretrained_base=pretrained_base,
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H A D | actionrec_resnetv1b.py | 43 def __init__(self, depth, nclass, pretrained_base=True, argument 50 pretrained_model = resnet18_v1b(pretrained=pretrained_base, **kwargs) 53 pretrained_model = resnet34_v1b(pretrained=pretrained_base, **kwargs) 56 pretrained_model = resnet50_v1b(pretrained=pretrained_base, **kwargs) 111 def resnet18_v1b_sthsthv2(nclass=174, pretrained=False, pretrained_base=True, argument 156 def resnet34_v1b_sthsthv2(nclass=174, pretrained=False, pretrained_base=True, argument 201 def resnet50_v1b_sthsthv2(nclass=174, pretrained=False, pretrained_base=True, argument 561 def resnet50_v1b_ucf101(nclass=101, pretrained=False, pretrained_base=True, argument 606 def resnet50_v1b_hmdb51(nclass=51, pretrained=False, pretrained_base=True, argument 651 def resnet50_v1b_custom(nclass=400, pretrained=False, pretrained_base=True, argument [all …]
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H A D | i3d_resnet.py | 450 self.pretrained_base = pretrained_base 663 pretrained_base=pretrained_base, 721 pretrained_base=pretrained_base, 779 pretrained_base=pretrained_base, 840 pretrained_base=pretrained_base, 901 pretrained_base=pretrained_base, 962 pretrained_base=pretrained_base, 1022 pretrained_base=pretrained_base, 1079 pretrained_base=pretrained_base, 1155 pretrained_base=pretrained_base, [all …]
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H A D | slowfast.py | 172 pretrained_base=False, argument 535 def slowfast_4x16_resnet50_kinetics400(nclass=400, pretrained=False, pretrained_base=True, argument 569 pretrained_base=pretrained_base, 598 def slowfast_8x8_resnet50_kinetics400(nclass=400, pretrained=False, pretrained_base=True, argument 632 pretrained_base=pretrained_base, 695 pretrained_base=pretrained_base, 758 pretrained_base=pretrained_base, 821 pretrained_base=pretrained_base, 887 pretrained_base=pretrained_base, 916 def slowfast_4x16_resnet50_custom(nclass=400, pretrained=False, pretrained_base=True, argument [all …]
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/dports/misc/py-gluoncv/gluon-cv-0.9.0/tests/model_zoo/ |
H A D | test_model_zoo.py | 428 _test_model_list(models, ctx, x, pretrained=True, pretrained_base=True) 472 _test_model_list(models, ctx, x, pretrained=True, pretrained_base=True) 483 _test_model_list(models, ctx, x, pretrained=True, pretrained_base=True) 494 _test_model_list(models, ctx, x, pretrained=True, pretrained_base=True) 507 _test_model_list(models, ctx, x, pretrained=True, pretrained_base=True) 518 _test_model_list(models, ctx, x, pretrained=True, pretrained_base=True) 529 _test_model_list(models, ctx, x, pretrained=True, pretrained_base=True) 541 _test_model_list(models, ctx, x, pretrained=True, pretrained_base=True) 555 _test_model_list(models, ctx, x, pretrained=True, pretrained_base=True) 565 _test_model_list(models, ctx, x, pretrained=True, pretrained_base=True) [all …]
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/dports/misc/py-gluoncv/gluon-cv-0.9.0/gluoncv/model_zoo/yolo/ |
H A D | yolo3.py | 581 pretrained_base = False if pretrained else pretrained_base 650 pretrained_base = False if pretrained else pretrained_base 683 pretrained_base = False if pretrained else pretrained_base 762 pretrained_base = False if pretrained else pretrained_base 765 pretrained=pretrained_base, 857 pretrained_base = False if pretrained else pretrained_base 860 pretrained=pretrained_base, 900 pretrained_base = False if pretrained else pretrained_base 903 pretrained=pretrained_base, 995 pretrained_base = False if pretrained else pretrained_base [all …]
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/dports/misc/py-gluoncv/gluon-cv-0.9.0/gluoncv/torch/model_zoo/action_recognition/ |
H A D | actionrec_resnetv1b.py | 45 def __init__(self, depth, num_classes, pretrained_base=True, argument 53 self.pretrained_base = pretrained_base 57 C2D = torchvision.models.resnet18(pretrained=self.pretrained_base, progress=True) 60 C2D = torchvision.models.resnet34(pretrained=self.pretrained_base, progress=True) 128 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 146 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 164 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 182 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 200 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 218 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, [all …]
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H A D | i3d_slow.py | 275 pretrained_base=True, argument 308 self.pretrained_base = pretrained_base 410 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 427 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 444 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 461 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 478 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 495 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 512 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 529 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE,
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H A D | i3d_resnet.py | 292 pretrained_base=True, argument 329 self.pretrained_base = pretrained_base 420 if not self.pretrained_base: 423 if self.pretrained_base and not self.pretrained: 519 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 540 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 564 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 588 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 612 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, 642 pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE, [all …]
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/dports/misc/py-gluoncv/gluon-cv-0.9.0/gluoncv/model_zoo/monodepthv2/ |
H A D | monodepth2.py | 44 def __init__(self, backbone, pretrained_base, num_input_images=1, scales=range(4), argument 49 self.encoder = ResnetEncoder(backbone, pretrained_base, 51 if not pretrained_base: 74 def get_monodepth2(backbone='resnet18', pretrained_base=True, argument 107 model = MonoDepth2(backbone=backbone, pretrained_base=pretrained_base,
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H A D | monodepth2_posenet.py | 45 def __init__(self, backbone, pretrained_base, num_input_images=2, num_input_features=1, argument 50 self.encoder = ResnetEncoder(backbone, pretrained_base, 52 if not pretrained_base: 77 def get_monodepth2posenet(backbone='resnet18', pretrained_base=True, num_input_images=2, argument 115 backbone=backbone, pretrained_base=pretrained_base,
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/dports/misc/py-gluoncv/gluon-cv-0.9.0/gluoncv/model_zoo/ |
H A D | fcn.py | 43 def __init__(self, nclass, backbone='resnet50', aux=True, ctx=cpu(), pretrained_base=True, argument 46 crop_size=crop_size, pretrained_base=pretrained_base, **kwargs) 94 root='~/.mxnet/models', ctx=cpu(0), pretrained_base=True, **kwargs): argument 125 model = FCN(datasets[dataset].NUM_CLASS, backbone=backbone, pretrained_base=pretrained_base,
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H A D | pspnet.py | 36 def __init__(self, nclass, backbone='resnet50', aux=True, ctx=cpu(), pretrained_base=True, argument 39 crop_size=crop_size, pretrained_base=pretrained_base, **kwargs) 149 root='~/.mxnet/models', ctx=cpu(0), pretrained_base=True, **kwargs): argument 180 pretrained_base=pretrained_base, ctx=ctx, **kwargs)
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H A D | icnet.py | 47 def __init__(self, nclass, backbone='resnet50', aux=False, ctx=cpu(), pretrained_base=True, argument 51 pretrained_base=pretrained_base, **kwargs) 321 root='~/.mxnet/models', pretrained_base=True, ctx=cpu(0), **kwargs): argument 353 pretrained_base=pretrained_base, ctx=ctx, **kwargs)
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/dports/misc/py-gluoncv/gluon-cv-0.9.0/gluoncv/model_zoo/rcnn/ |
H A D | rcnn.py | 250 def custom_rcnn_fpn(pretrained_base=True, base_network_name='resnet18_v1b', norm_layer=nn.BatchNorm, argument 295 base_network = resnet18_v1b(pretrained=pretrained_base, dilated=False, 302 base_network = resnet50_v1b(pretrained=pretrained_base, dilated=False, 309 base_network = resnet101_v1d(pretrained=pretrained_base, dilated=False, 316 base_network = resnest50(pretrained=pretrained_base, dilated=False, 323 base_network = resnest101(pretrained=pretrained_base, dilated=False, 334 pretrained=pretrained_base, norm_layer=sym_norm_layer, norm_kwargs=sym_norm_kwargs)
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/dports/misc/py-gluoncv/gluon-cv-0.9.0/gluoncv/model_zoo/simple_pose/ |
H A D | mobile_pose.py | 34 pretrained_base=False, pretrained_ctx=cpu(), **kwargs): argument 39 base_model = get_model(base_name, pretrained=pretrained_base,
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