Update info about ResNet-18 x0.5 model

README.md

@@ -13,7 +13,7 @@ To use only Gluon models in your project, simply install the `gluoncv2` package
 ```
 pip install gluoncv2 mxnet>=1.2.1
 ```
-To enable different hardware supports such as GPUs, check out [mxnet variants](https://pypi.org/project/mxnet/).
+To enable different hardware supports such as GPUs, check out [MXNet variants](https://pypi.org/project/mxnet/).
 For example, you can install with cuda-9.2 supported mxnet:
 ```
 pip install gluoncv2 mxnet-cu92>=1.2.1
@@ -121,7 +121,7 @@ bottleneck block. Respectively a network without b-suffix has the stride in the
 | ResNet-14 | 32.85 | 12.41 | 5,788,200 | 1,355.64M | Training ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.40/resnet14-1241-a8955ff3.params.log)) |
 | ResNet-16 | 30.68 | 11.10 | 6,968,872 | 1,586.95M | Training ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.41/resnet16-1110-1be996d1.params.log)) |
 | ResNet-18 x0.25 | 53.13 | 27.77 | 831,096 | 136.64M | 1-stage training ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.1/resnet18_wd4-2777-42c5a34c.params.log)) |
-| ResNet-18 x0.5 | 38.94 | 16.46 | 3,055,880 | 485.22M | 1-stage training ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.1/resnet18_wd2-1646-99006438.params.log)) |
+| ResNet-18 x0.5 | 36.54 | 14.96 | 3,055,880 | 485.22M | Training ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.46/resnet18_wd2-1496-d839c509.params.log)) |
 | ResNet-18 x0.75 | 33.25 | 12.54 | 6,675,352 | 1,045.75M | Training ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.18/resnet18_w3d4-1254-d6548612.params.log)) |
 | ResNet-18 | 29.13 | 9.94 | 11,689,512 | 1,818.21M | Training ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.1/resnet18-0994-ae25f2b2.params.log)) |
 | ResNet-34 | 25.34 | 7.92 | 21,797,672 | 3,669.16M | Converted from Gluon Model Zoo ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.1/resnet34-0792-5b875f49.params.log)) |
@@ -191,7 +191,7 @@ bottleneck block. Respectively a network without b-suffix has the stride in the
 | ResNet-14 | 33.17 | 12.71 | 5,788,200 | 1,355.64M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.40/resnet14-1271-568c392e.pth.log)) |
 | ResNet-16 | 30.90 | 11.38 | 6,968,872 | 1,586.95M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.41/resnet16-1138-3a5aa7c0.pth.log)) |
 | ResNet-18 x0.25 | 53.37 | 28.06 | 831,096 | 136.64M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.1/resnet18_wd4-2806-d0cda855.pth.log)) |
-| ResNet-18 x0.5 | 39.31 | 16.79 | 3,055,880 | 485.22M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.1/resnet18_wd2-1679-12f81d73.pth.log)) |
+| ResNet-18 x0.5 | 37.04 | 15.38 | 3,055,880 | 485.22M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.46/resnet18_wd2-1538-671466b5.pth.log)) |
 | ResNet-18 x0.75 | 33.61 | 12.85 | 6,675,352 | 1,045.75M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.18/resnet18_w3d4-1285-94713e0e.pth.log)) |
 | ResNet-18 | 29.52 | 10.21 | 11,689,512 | 1,818.21M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.1/resnet18-1021-b0d7daea.pth.log)) |
 | ResNet-34 | 25.66 | 8.18 | 21,797,672 | 3,669.16M | Converted from Gluon Model Zoo ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.1/resnet34-0818-6f947d40.pth.log)) |
@@ -261,7 +261,7 @@ bottleneck block. Respectively a network without b-suffix has the stride in the
 | ResNet-14 | 32.84 | 12.42 | 5,788,200 | 1,355.64M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.40/resnet14-1242-4e65746b.npz.log)) |
 | ResNet-16 | 30.66 | 11.07 | 6,968,872 | 1,586.95M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.41/resnet16-1107-b1d7fb7d.npz.log)) |
 | ResNet-18 x0.25 | 53.17 | 27.70 | 831,096 | 136.64M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.22/resnet18_wd4-2770-72465bfe.npz.log)) |
-| ResNet-18 x0.5 | 38.95 | 16.46 | 3,055,880 | 485.22M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.22/resnet18_wd2-1646-58261fc5.npz.log)) |
+| ResNet-18 x0.5 | 36.55 | 14.99 | 3,055,880 | 485.22M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.46/resnet18_wd2-1499-542ed773.npz.log)) |
 | ResNet-18 x0.75 | 33.27 | 12.56 | 6,675,352 | 1,045.75M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.22/resnet18_w3d4-1256-ce2011df.npz.log)) |
 | ResNet-18 | 29.08 | 9.97 | 11,689,512 | 1,818.21M | Converted from GL model ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.22/resnet18-0997-9862a84f.npz.log)) |
 | ResNet-34 | 25.35 | 7.95 | 21,797,672 | 3,669.16M | Converted from Gluon Model Zoo ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.22/resnet34-0795-0b392267.npz.log)) |

chainer_/chainercv2/models/model_store.py

@@ -15,7 +15,7 @@
     ('resnet14', '1242', '4e65746b8a327f2fde5740669f5cd44dc7327e24', 'v0.0.40'),
     ('resnet16', '1107', 'b1d7fb7df91145155f6b1c45133c47ecb26996e9', 'v0.0.41'),
     ('resnet18_wd4', '2770', '72465bfeef07399a54c03d6531aaadaf7e54a94c', 'v0.0.22'),
-    ('resnet18_wd2', '1646', '58261fc55698d1f5fccba964a39de30e9cf4f658', 'v0.0.22'),
+    ('resnet18_wd2', '1499', '542ed773551add89346117be2430c9f818faeeb1', 'v0.0.46'),
     ('resnet18_w3d4', '1256', 'ce2011dfcddf9cac229d7e3a63b3764e15bcbc47', 'v0.0.22'),
     ('resnet18', '0997', '9862a84fbb34789888ffb631d64534294b312e20', 'v0.0.22'),
     ('resnet34', '0795', '0b392267b08907dc14023b24fd84df0268087002', 'v0.0.22'),

convert_models.py

@@ -474,6 +474,9 @@ def main():
     if (args.src_fwk == "chainer") or (args.dst_fwk == "chainer"):
         packages += ['chainer', 'chainercv']
         pip_packages += ['cupy-cuda92', 'chainer', 'chainercv']
+    if (args.src_fwk == "keras") or (args.dst_fwk == "keras"):
+        packages += ['keras']
+        pip_packages += ['keras', 'keras-mxnet', 'keras-applications', 'keras-preprocessing']
 
     _, log_file_exist = initialize_logging(
         logging_dir_path=args.save_dir,

gluon/gluoncv2/models/model_store.py

@@ -15,7 +15,7 @@
     ('resnet14', '1241', 'a8955ff3d4facd8e38e776fc72f1945806def16a', 'v0.0.40'),
     ('resnet16', '1110', '1be996d1d18da94d9e8dc0cd35d5135ef4da6bc9', 'v0.0.41'),
     ('resnet18_wd4', '2777', '42c5a34cb9380f89377bb2122664ebbe087dd49d', 'v0.0.1'),
-    ('resnet18_wd2', '1646', '99006438e7f89c0e46cfd5535ced5e173b6417a5', 'v0.0.1'),
+    ('resnet18_wd2', '1496', 'd839c509bcb8c9c156478f2b91f23e96fc17df15', 'v0.0.46'),
     ('resnet18_w3d4', '1254', 'd654861258936f678b928a92d88fd205a20777af', 'v0.0.18'),
     ('resnet18', '0994', 'ae25f2b27603955a3888f15286692a45d7396045', 'v0.0.1'),
     ('resnet34', '0792', '5b875f4934da8d83d44afc30d8e91362d3103115', 'v0.0.1'),

keras_/model_provider.py

@@ -1,5 +1,6 @@
 from .models.resnet import *
 from .models.preresnet import *
+from .models.resnext import *
 from .models.darknet import *
 from .models.mobilenet import *
 
@@ -67,6 +68,13 @@
     'sepreresnet200': sepreresnet200,
     'sepreresnet200b': sepreresnet200b,
 
+    'resnext50_32x4d': resnext50_32x4d,
+    'resnext101_32x4d': resnext101_32x4d,
+    'resnext101_64x4d': resnext101_64x4d,
+    'seresnext50_32x4d': seresnext50_32x4d,
+    'seresnext101_32x4d': seresnext101_32x4d,
+    'seresnext101_64x4d': seresnext101_64x4d,
+
     'darknet_ref': darknet_ref,
     'darknet_tiny': darknet_tiny,
     'darknet19': darknet19,

pytorch/pytorchcv/models/model_store.py

@@ -15,7 +15,7 @@
     ('resnet14', '1271', '568c392e3e94041dd589d1b8164e337f90440d06', 'v0.0.40'),
     ('resnet16', '1138', '3a5aa7c0164af3b66faf5b9974352a86d6a02974', 'v0.0.41'),
     ('resnet18_wd4', '2806', 'd0cda855f8772dddf3efef5cbd6ac5874d166ab4', 'v0.0.1'),
-    ('resnet18_wd2', '1679', '12f81d7315e798ec944bb52bd492bdfed667fca4', 'v0.0.1'),
+    ('resnet18_wd2', '1538', '671466b5e3b952eac4e8c60f57380d11bc1d3a05', 'v0.0.46'),
     ('resnet18_w3d4', '1285', '94713e0e1780a9f19b2a5f4575eb254f8a67b556', 'v0.0.18'),
     ('resnet18', '1021', 'b0d7daeaab950f2a7106c8062c7435627b3fe3da', 'v0.0.1'),
     ('resnet34', '0818', '6f947d409313c862a1ef22c46e29b09c85eb9abf', 'v0.0.1'),