fix keras_vggface comaptibility with keras 2.2.0

goodday-g1 · Nov 8, 2018 · 1f2df8f · 1f2df8f
1 parent aa4fb3f
commit 1f2df8f
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Showing 2 changed files with 533 additions and 3 deletions.
diff --git a/colab_demo/faceswap-GAN_colab_demo.ipynb b/colab_demo/faceswap-GAN_colab_demo.ipynb
@@ -551,6 +551,16 @@
     "model = FaceswapGANModel(**arch_config)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "!wget https://github.com/rcmalli/keras-vggface/releases/download/v2.0/rcmalli_vggface_tf_notop_resnet50.h5"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 57,
@@ -574,10 +584,17 @@
     }
    ],
    "source": [
-    "from keras_vggface.vggface import VGGFace\n",
+    "#from keras_vggface.vggface import VGGFace\n",
     "\n",
     "# VGGFace ResNet50\n",
-    "vggface = VGGFace(include_top=False, model='resnet50', input_shape=(224, 224, 3))\n",
+    "#vggface = VGGFace(include_top=False, model='resnet50', input_shape=(224, 224, 3))'\n",
+    "\n",
+    "from .vggface_models import RESNET50\n",
+    "vggface = RESNET50(include_top=False, weights=None, input_shape=(224, 224, 3))\n",
+    "vggface.load_weights(\"rcmalli_vggface_tf_notop_resnet50.h5\")\n",
+    "\n",
+    "#from keras.applications.resnet50 import ResNet50\n",
+    "#vggface = ResNet50(include_top=False, input_shape=(224, 224, 3))\n",
     "\n",
     "#vggface.summary()\n",
     "\n",
@@ -667,7 +684,9 @@
     "    K.clear_session()\n",
     "    model = FaceswapGANModel(**arch_config)\n",
     "    model.load_weights(path=save_path)\n",
-    "    vggface = VGGFace(include_top=False, model='resnet50', input_shape=(224, 224, 3))\n",
+    "    #vggface = VGGFace(include_top=False, model='resnet50', input_shape=(224, 224, 3))\n",
+    "    vggface = RESNET50(include_top=False, weights=None, input_shape=(224, 224, 3))\n",
+    "    vggface.load_weights(\"rcmalli_vggface_tf_notop_resnet50.h5\")\n",
     "    model.build_pl_model(vggface_model=vggface, before_activ=loss_config[\"PL_before_activ\"])\n",
     "    train_batchA = DataLoader(train_A, train_AnB, batchSize, img_dirA_bm_eyes,\n",
     "                              RESOLUTION, num_cpus, K.get_session(), **da_config)\n",