latest pypi version

Demo Gradio.ipynb

@@ -24,15 +24,17 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {},
+   "metadata": {
+    "scrolled": false
+   },
    "outputs": [],
    "source": [
-    "model = tf.keras.applications.inception_v3.InceptionV3()"
+    "model = tf.keras.applications.MobileNet()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -47,7 +49,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 4,
    "metadata": {
     "scrolled": false
    },
@@ -56,10 +58,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Closing existing server...\n",
+      "NOTE: Gradio is in beta stage, please report all bugs to: gradio.app@gmail.com\n",
-      "NOTE: Gradio is in beta stage, please report all bugs to: contact.gradio@gmail.com\n",
+      "Model is running locally at: http://localhost:7864/\n",
-      "Model is running locally at: http://localhost:7862/\n",
+      "To create a public link, set `share=True` in the argument to `launch()`.\n"
-      "Model available publicly at: https://53920.gradio.app -- may take up to a minute to setup.\n"
      ]
     },
     {
@@ -69,14 +70,14 @@
        "        <iframe\n",
        "            width=\"1000\"\n",
        "            height=\"500\"\n",
-       "            src=\"http://localhost:7862/\"\n",
+       "            src=\"http://localhost:7864/\"\n",
        "            frameborder=\"0\"\n",
        "            allowfullscreen\n",
        "        ></iframe>\n",
        "        "
       ],
       "text/plain": [
-       "<IPython.lib.display.IFrame at 0x1f66392cd68>"
+       "<IPython.lib.display.IFrame at 0x274adb64a90>"
       ]
      },
      "metadata": {},
@@ -84,7 +85,7 @@
     }
    ],
    "source": [
-    "io.launch(inline=True, inbrowser=False, share=True, validate=False);"
+    "io.launch(inline=True, share=False, validate=False);"
    ]
   }
  ],

Test Keras.ipynb

@@ -0,0 +1,121 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Load the Model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n"
+     ]
+    }
+   ],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "\n",
+    "import numpy as np\n",
+    "import tensorflow as tf\n",
+    "import gradio"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = tf.keras.applications.MobileNet()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "inp = gradio.inputs.ImageUpload()\n",
+    "out = gradio.outputs.Label(label_names='imagenet1000', max_label_length=8)\n",
+    "\n",
+    "io = gradio.Interface(inputs=inp, \n",
+    "                      outputs=out,\n",
+    "                      model=model, \n",
+    "                      model_type='keras')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Closing existing server...\n",
+      "NOTE: Gradio is in beta stage, please report all bugs to: gradio.app@gmail.com\n",
+      "Model is running locally at: http://localhost:7863/\n",
+      "Model available publicly at: https://25024.gradio.app -- may take up to a minute to setup.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <iframe\n",
+       "            width=\"1000\"\n",
+       "            height=\"500\"\n",
+       "            src=\"http://localhost:7863/\"\n",
+       "            frameborder=\"0\"\n",
+       "            allowfullscreen\n",
+       "        ></iframe>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.IFrame at 0x266c18d8940>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "io.launch(inline=True, validate=False);"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.6 (tensorflow)",
+   "language": "python",
+   "name": "tensorflow"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

build/lib/gradio/interface.py

@@ -89,6 +89,7 @@ class Interface:
         if self.model_type == "keras":
             import tensorflow as tf
             self.graph = tf.get_default_graph()
+            self.sess = tf.keras.backend.get_session()
         self.verbose = verbose
         self.status = self.STATUS_TYPES["OFF"]
         self.validate_flag = False
@@ -135,8 +136,10 @@ class Interface:
         if self.model_type == "sklearn":
             return self.model_obj.predict(preprocessed_input)
         elif self.model_type == "keras":
+            import tensorflow as tf
             with self.graph.as_default():
-                return self.model_obj.predict(preprocessed_input)
+                with self.sess.as_default():
+                    return self.model_obj.predict(preprocessed_input)
         elif self.model_type == "pyfunc":
             return self.model_obj(preprocessed_input)
         elif self.model_type == "pytorch":
@@ -200,7 +203,7 @@ class Interface:
             return
         raise RuntimeError("Validation did not pass")
 
-    def launch(self, inline=None, inbrowser=None, share=False, validate=True):
+    def launch(self, inline=None, inbrowser=None, share=True, validate=True):
         """
         Standard method shared by interfaces that creates the interface and sets up a websocket to communicate with it.
         :param inline: boolean. If True, then a gradio interface is created inline (e.g. in jupyter or colab notebook)

build/lib/gradio/strings.py

@@ -1,5 +1,5 @@
 en = {
-    "BETA_MESSAGE": "NOTE: Gradio is in beta stage, please report all bugs to: contact.gradio@gmail.com",
+    "BETA_MESSAGE": "NOTE: Gradio is in beta stage, please report all bugs to: gradio.app@gmail.com",
     "RUNNING_LOCALLY": "Model is running locally at: {}",
     "NGROK_NO_INTERNET": "Unable to create public link for interface, please check internet connection or try "
                          "restarting python interpreter.",

gradio.egg-info/PKG-INFO

@@ -1,6 +1,6 @@
 Metadata-Version: 1.0
 Name: gradio
-Version: 0.7.1
+Version: 0.7.2
 Summary: Python library for easily interacting with trained machine learning models
 Home-page: https://github.com/abidlabs/gradio
 Author: Abubakar Abid

gradio/interface.py

@@ -89,6 +89,7 @@ class Interface:
         if self.model_type == "keras":
             import tensorflow as tf
             self.graph = tf.get_default_graph()
+            self.sess = tf.keras.backend.get_session()
         self.verbose = verbose
         self.status = self.STATUS_TYPES["OFF"]
         self.validate_flag = False
@@ -135,8 +136,10 @@ class Interface:
         if self.model_type == "sklearn":
             return self.model_obj.predict(preprocessed_input)
         elif self.model_type == "keras":
+            import tensorflow as tf
             with self.graph.as_default():
-                return self.model_obj.predict(preprocessed_input)
+                with self.sess.as_default():
+                    return self.model_obj.predict(preprocessed_input)
         elif self.model_type == "pyfunc":
             return self.model_obj(preprocessed_input)
         elif self.model_type == "pytorch":
@@ -200,7 +203,7 @@ class Interface:
             return
         raise RuntimeError("Validation did not pass")
 
-    def launch(self, inline=None, inbrowser=None, share=False, validate=True):
+    def launch(self, inline=None, inbrowser=None, share=True, validate=True):
         """
         Standard method shared by interfaces that creates the interface and sets up a websocket to communicate with it.
         :param inline: boolean. If True, then a gradio interface is created inline (e.g. in jupyter or colab notebook)

gradio/strings.py

@@ -1,5 +1,5 @@
 en = {
-    "BETA_MESSAGE": "NOTE: Gradio is in beta stage, please report all bugs to: contact.gradio@gmail.com",
+    "BETA_MESSAGE": "NOTE: Gradio is in beta stage, please report all bugs to: gradio.app@gmail.com",
     "RUNNING_LOCALLY": "Model is running locally at: {}",
     "NGROK_NO_INTERNET": "Unable to create public link for interface, please check internet connection or try "
                          "restarting python interpreter.",

setup.py

@@ -5,7 +5,7 @@ except ImportError:
 
 setup(
     name='gradio',
-    version='0.7.1',
+    version='0.7.2',
     include_package_data=True,
     description='Python library for easily interacting with trained machine learning models',
     author='Abubakar Abid',