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https://github.com/gradio-app/gradio.git
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latest pypi version
This commit is contained in:
Abubakar Abid
parent
b8c22d2d66
commit
c1d3fbf567
@ -24,15 +24,17 @@
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"metadata": {
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"scrolled": false
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},
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"outputs": [],
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"source": [
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"model = tf.keras.applications.inception_v3.InceptionV3()"
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"model = tf.keras.applications.MobileNet()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -47,7 +49,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 4,
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"metadata": {
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"scrolled": false
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},
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@ -56,10 +58,9 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Closing existing server...\n",
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"NOTE: Gradio is in beta stage, please report all bugs to: contact.gradio@gmail.com\n",
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"Model is running locally at: http://localhost:7862/\n",
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"Model available publicly at: https://53920.gradio.app -- may take up to a minute to setup.\n"
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"NOTE: Gradio is in beta stage, please report all bugs to: gradio.app@gmail.com\n",
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"Model is running locally at: http://localhost:7864/\n",
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"To create a public link, set `share=True` in the argument to `launch()`.\n"
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]
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},
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{
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@ -69,14 +70,14 @@
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" <iframe\n",
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" width=\"1000\"\n",
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" height=\"500\"\n",
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" src=\"http://localhost:7862/\"\n",
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" src=\"http://localhost:7864/\"\n",
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" frameborder=\"0\"\n",
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" allowfullscreen\n",
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" ></iframe>\n",
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" "
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],
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"text/plain": [
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"<IPython.lib.display.IFrame at 0x1f66392cd68>"
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"<IPython.lib.display.IFrame at 0x274adb64a90>"
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]
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},
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"metadata": {},
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@ -84,7 +85,7 @@
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}
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],
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"source": [
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"io.launch(inline=True, inbrowser=False, share=True, validate=False);"
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"io.launch(inline=True, share=False, validate=False);"
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]
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}
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],
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121
Test Keras.ipynb
Normal file
121
Test Keras.ipynb
Normal file
@ -0,0 +1,121 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Load the Model"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The autoreload extension is already loaded. To reload it, use:\n",
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" %reload_ext autoreload\n"
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]
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}
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],
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"source": [
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"%load_ext autoreload\n",
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"%autoreload 2\n",
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"\n",
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"import numpy as np\n",
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"import tensorflow as tf\n",
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"import gradio"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"model = tf.keras.applications.MobileNet()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"inp = gradio.inputs.ImageUpload()\n",
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"out = gradio.outputs.Label(label_names='imagenet1000', max_label_length=8)\n",
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"\n",
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"io = gradio.Interface(inputs=inp, \n",
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" outputs=out,\n",
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" model=model, \n",
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" model_type='keras')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {
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"scrolled": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Closing existing server...\n",
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"NOTE: Gradio is in beta stage, please report all bugs to: gradio.app@gmail.com\n",
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"Model is running locally at: http://localhost:7863/\n",
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"Model available publicly at: https://25024.gradio.app -- may take up to a minute to setup.\n"
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]
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},
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{
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"data": {
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"text/html": [
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"\n",
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" <iframe\n",
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" width=\"1000\"\n",
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" height=\"500\"\n",
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" src=\"http://localhost:7863/\"\n",
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" frameborder=\"0\"\n",
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" allowfullscreen\n",
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" ></iframe>\n",
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" "
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],
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"text/plain": [
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"<IPython.lib.display.IFrame at 0x266c18d8940>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"io.launch(inline=True, validate=False);"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.6 (tensorflow)",
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"language": "python",
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"name": "tensorflow"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.7"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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@ -89,6 +89,7 @@ class Interface:
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if self.model_type == "keras":
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import tensorflow as tf
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self.graph = tf.get_default_graph()
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self.sess = tf.keras.backend.get_session()
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self.verbose = verbose
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self.status = self.STATUS_TYPES["OFF"]
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self.validate_flag = False
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@ -135,8 +136,10 @@ class Interface:
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if self.model_type == "sklearn":
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return self.model_obj.predict(preprocessed_input)
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elif self.model_type == "keras":
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import tensorflow as tf
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with self.graph.as_default():
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return self.model_obj.predict(preprocessed_input)
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with self.sess.as_default():
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return self.model_obj.predict(preprocessed_input)
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elif self.model_type == "pyfunc":
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return self.model_obj(preprocessed_input)
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elif self.model_type == "pytorch":
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@ -200,7 +203,7 @@ class Interface:
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return
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raise RuntimeError("Validation did not pass")
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def launch(self, inline=None, inbrowser=None, share=False, validate=True):
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def launch(self, inline=None, inbrowser=None, share=True, validate=True):
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"""
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Standard method shared by interfaces that creates the interface and sets up a websocket to communicate with it.
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:param inline: boolean. If True, then a gradio interface is created inline (e.g. in jupyter or colab notebook)
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@ -1,5 +1,5 @@
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en = {
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"BETA_MESSAGE": "NOTE: Gradio is in beta stage, please report all bugs to: contact.gradio@gmail.com",
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"BETA_MESSAGE": "NOTE: Gradio is in beta stage, please report all bugs to: gradio.app@gmail.com",
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"RUNNING_LOCALLY": "Model is running locally at: {}",
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"NGROK_NO_INTERNET": "Unable to create public link for interface, please check internet connection or try "
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"restarting python interpreter.",
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Binary file not shown.
@ -1,6 +1,6 @@
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Metadata-Version: 1.0
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Name: gradio
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Version: 0.7.1
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Version: 0.7.2
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Summary: Python library for easily interacting with trained machine learning models
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Home-page: https://github.com/abidlabs/gradio
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Author: Abubakar Abid
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@ -89,6 +89,7 @@ class Interface:
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if self.model_type == "keras":
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import tensorflow as tf
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self.graph = tf.get_default_graph()
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self.sess = tf.keras.backend.get_session()
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self.verbose = verbose
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self.status = self.STATUS_TYPES["OFF"]
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self.validate_flag = False
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@ -135,8 +136,10 @@ class Interface:
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if self.model_type == "sklearn":
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return self.model_obj.predict(preprocessed_input)
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elif self.model_type == "keras":
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import tensorflow as tf
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with self.graph.as_default():
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return self.model_obj.predict(preprocessed_input)
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with self.sess.as_default():
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return self.model_obj.predict(preprocessed_input)
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elif self.model_type == "pyfunc":
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return self.model_obj(preprocessed_input)
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elif self.model_type == "pytorch":
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@ -200,7 +203,7 @@ class Interface:
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return
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raise RuntimeError("Validation did not pass")
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def launch(self, inline=None, inbrowser=None, share=False, validate=True):
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def launch(self, inline=None, inbrowser=None, share=True, validate=True):
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"""
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Standard method shared by interfaces that creates the interface and sets up a websocket to communicate with it.
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:param inline: boolean. If True, then a gradio interface is created inline (e.g. in jupyter or colab notebook)
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@ -1,5 +1,5 @@
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en = {
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"BETA_MESSAGE": "NOTE: Gradio is in beta stage, please report all bugs to: contact.gradio@gmail.com",
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"BETA_MESSAGE": "NOTE: Gradio is in beta stage, please report all bugs to: gradio.app@gmail.com",
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"RUNNING_LOCALLY": "Model is running locally at: {}",
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"NGROK_NO_INTERNET": "Unable to create public link for interface, please check internet connection or try "
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"restarting python interpreter.",
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