Update info for DPN models

osmr · Aug 28, 2018 · 02d5e00 · 02d5e00
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commit 02d5e00
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Showing 5 changed files with 19 additions and 6 deletions.
diff --git a/README.md b/README.md
@@ -28,6 +28,7 @@ torchvision >= 0.2.1
 - SENet/SE-ResNet/SE-PreResNet/SE-ResNeXt (['Squeeze-and-Excitation Networks'](https://arxiv.org/abs/1709.01507))
 - DenseNet (['Densely Connected Convolutional Networks'](https://arxiv.org/abs/1608.06993))
 - CondenseNet (['CondenseNet: An Efficient DenseNet using Learned Group Convolutions'](https://arxiv.org/abs/1711.09224))
+- DPN (['Dual Path Networks'](https://arxiv.org/abs/1707.01629))
 - DarkNet (['Darknet: Open source neural networks in c'](https://github.com/pjreddie/darknet)) 
 - SqueezeNet (['SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size'](https://arxiv.org/abs/1602.07360))
 - SqueezeNext (['SqueezeNext: Hardware-Aware Neural Network Design'](https://arxiv.org/abs/1803.10615))
@@ -90,6 +91,9 @@ bottleneck block. Respectively a network without b-suffix has the stride in the
 | DenseNet-201 | 22.71 | 6.36 | 20,013,928 | 4,318.75M | Converted from Gluon Model Zoo ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.3/densenet201-0636-65b5d389.params.log)) |
 | CondenseNet-74 (C=G=4) | 26.82 | 8.64 | 4,773,944 | 533.64M | From [ShichenLiu/CondenseNet] ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.4/condensenett74_c4_g4-0864-cde68fa2.params.log)) |
 | CondenseNet-74 (C=G=8) | 29.76 | 10.49 | 2,935,416 | 278.55M | From [ShichenLiu/CondenseNet] ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.4/condensenett74_c8_g8-1049-4cf4a08e.params.log)) |
+| DPN-68 | 23.57 | 7.00 | 12,611,602 | 2,338.71M | From [Cadene/pretrained...pytorch] ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.17/dpn68-0700-3114719d.params.log)) |
+| DPN-98 | 20.23 | 5.28 | 61,570,728 | 11,702.80M | From [Cadene/pretrained...pytorch] ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.17/dpn98-0528-fa5d6fca.params.log)) |
+| DPN-131 | 20.03 | 5.22 | 79,254,504 | 16,056.22M | From [Cadene/pretrained...pytorch] ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.17/dpn131-0522-35ac2f82.params.log)) |
 | SqueezeNet v1.0 | 42.81 | 19.98 | 1,248,424 | 828.30M | Converted from Gluon Model Zoo ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.5/squeezenet_v1_0-1998-1b771149.params.log)) |
 | SqueezeNet v1.1 | 41.37 | 19.20 | 1,235,496 | 354.88M | Training ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.15/squeezenet_v1_1-1920-6d01104e.params.log)) |
 | 108-MENet-8x1 (g=3) | 46.11 | 22.37 | 654,516 | 40.64M | From [clavichord93/MENet] ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.6/menet108_8x1_g3-2237-d3bb5a4f.params.log)) |
@@ -152,6 +156,9 @@ bottleneck block. Respectively a network without b-suffix has the stride in the
 | DenseNet-201 | 23,10 | 6.63 | 20,013,928 | 4,318.75M | Converted from Gluon Model Zoo ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.3/densenet201-0663-71ece4ad.pth.log)) |
 | CondenseNet-74 (C=G=4) | 26.25 | 8.28 | 4,773,944 | 533.64M | From [ShichenLiu/CondenseNet] ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.4/condensenett74_c4_g4-0828-5ba55049.pth.log)) |
 | CondenseNet-74 (C=G=8) | 28.93 | 10.06 | 2,935,416 | 278.55M | From [ShichenLiu/CondenseNet] ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.4/condensenett74_c8_g8-1006-3574d874.pth.log)) |
+| DPN-68 | 24.17 | 7.27 | 12,611,602 | 2,338.71M | From [Cadene/pretrained...pytorch] ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.17/dpn68-0727-43849233.pth.log)) |
+| DPN-98 | 20.81 | 5.53 | 61,570,728 | 11,702.80M | From [Cadene/pretrained...pytorch] ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.17/dpn98-0553-52c55969.pth.log)) |
+| DPN-131 | 20.54 | 5.48 | 79,254,504 | 16,056.22M | From [Cadene/pretrained...pytorch] ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.17/dpn131-0548-0c53e5b3.pth.log)) |
 | SqueezeNet v1.0 | 41.91 | 19.58 | 1,248,424 | 828.30M | Converted from TorchVision ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.5/squeezenet_v1_0-1958-d6d59f9c.pth.log)) |
 | SqueezeNet v1.1 | 41.82 | 19.38 | 1,235,496 | 354.88M | Converted from TorchVision ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.5/squeezenet_v1_1-1938-8dcd1cc5.pth.log)) |
 | 108-MENet-8x1 (g=3) | 43.92 | 20.76 | 654,516 | 40.64M | From [clavichord93/MENet] ([log](https://github.com/osmr/imgclsmob/releases/download/v0.0.6/menet108_8x1_g3-2076-7f47b37e.pth.log)) |

diff --git a/gluon/models/dpn.py b/gluon/models/dpn.py
@@ -628,14 +628,14 @@ def _test():
     import numpy as np
     import mxnet as mx
 
-    pretrained = False
+    pretrained = True
     for_training = False
 
     models = [
         dpn68,
-        dpn68b,
+        # dpn68b,
         dpn98,
-        dpn107,
+        # dpn107,
         dpn131,
     ]
 

diff --git a/gluon/models/model_store.py b/gluon/models/model_store.py
@@ -46,6 +46,9 @@
     ('densenet201', '0636', '65b5d389b1f2a18c62dc39f74960266c601fec76', 'v0.0.3'),
     ('condensenet74_c4_g4', '0864', 'cde68fa2fcc9197e336717a17753a15a6efd7596', 'v0.0.4'),
     ('condensenet74_c8_g8', '1049', '4cf4a08e7fb46f5821049dcae97ae442b0ceb546', 'v0.0.4'),
+    ('dpn68', '0700', '3114719dccf3d9fa30bb7ab5a8c845815328e495', 'v0.0.17'),
+    ('dpn98', '0528', 'fa5d6fca985afde21f6374e4a4d4df788d1b4c3a', 'v0.0.17'),
+    ('dpn131', '0522', '35ac2f82e69264e0712dcb979da4d99675e2f2aa', 'v0.0.17'),
     ('squeezenet_v1_0', '1998', '1b771149cafb1631f70814bd40d6ee8642f30148', 'v0.0.5'),
     ('squeezenet_v1_1', '1920', '6d01104eaf6f03ee18589896b2c0d5a6d7c5b164', 'v0.0.15'),
     ('menet108_8x1_g3', '2237', 'd3bb5a4fa19a5e1dad2d036ffe64cc2a376defcc', 'v0.0.6'),

diff --git a/pytorch/models/dpn.py b/pytorch/models/dpn.py
@@ -613,14 +613,14 @@ def _test():
     import torch
     from torch.autograd import Variable
 
-    pretrained = False
+    pretrained = True
     for_training = False
 
     models = [
         dpn68,
-        dpn68b,
+        # dpn68b,
         dpn98,
-        dpn107,
+        # dpn107,
         dpn131,
     ]
 

diff --git a/pytorch/models/model_store.py b/pytorch/models/model_store.py
@@ -47,6 +47,9 @@
     ('densenet201', '0663', '71ece4ad7be5d1e2aa4bbf6f1a6b32ac2562d847', 'v0.0.3'),
     ('condensenet74_c4_g4', '0828', '5ba550494cae7081d12c14b02b2a02365539d377', 'v0.0.4'),
     ('condensenet74_c8_g8', '1006', '3574d874fefc3307f241690bad51f20e61be1542', 'v0.0.4'),
+    ('dpn68', '0727', '438492331840612ff1700e7b7d52dd6c0c683b47', 'v0.0.17'),
+    ('dpn98', '0553', '52c55969835d56185afa497c43f09df07f58f0d3', 'v0.0.17'),
+    ('dpn131', '0548', '0c53e5b380137ccb789e932775e8bd8a811eeb3e', 'v0.0.17'),
     ('squeezenet_v1_0', '1958', 'd6d59f9cc04c147d1f2eeeead9ac315391c3f028', 'v0.0.5'),
     ('squeezenet_v1_1', '1938', '8dcd1cc5d955f3d154bfa5be20cd278f3e77f21b', 'v0.0.5'),
     ('menet108_8x1_g3', '2076', '7f47b37e10912a55ea85fefa616f822fc6b32859', 'v0.0.6'),