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0.1.6

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This commit is contained in:
Abubakar Abid 2019-02-19 11:49:13 -08:00
parent 64f5bb8453
commit 613db90028
13 changed files with 262 additions and 189 deletions
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245
.idea/workspace.xml
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@ -2,7 +2,13 @@
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@ -63,10 +69,11 @@
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@ -95,17 +102,17 @@
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@ -121,14 +128,22 @@
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@ -284,11 +300,10 @@
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@ -311,10 +325,17 @@
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@ -354,10 +375,10 @@
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@ -419,23 +440,11 @@
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45
Emotional Detector.ipynb → Emotional Detector (Upload).ipynb
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@ -24,33 +24,24 @@
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{
"name": "stdout",
"output_type": "stream",
"text": [
"WARNING:tensorflow:From C:\\Users\\ALI\\Anaconda3\\lib\\site-packages\\tensorflow\\python\\framework\\op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
"Instructions for updating:\n",
"Colocations handled automatically by placer.\n",
"WARNING:tensorflow:From C:\\Users\\ALI\\Anaconda3\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:3445: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n",
"Instructions for updating:\n",
"Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n",
"WARNING:tensorflow:From C:\\Users\\ALI\\Anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
"Instructions for updating:\n",
"Use tf.cast instead.\n"
]
}
],
"source": [ "source": [
"model = load_model('models/emotion.h5')" "# Load an Facial Emotion Detector Model"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"model = load_model('.models/emotion.h5')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
@ -61,7 +52,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": 6,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -69,8 +60,8 @@
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"NOTE: Gradio is in beta stage, please report all bugs to: a12d@stanford.edu\n", "NOTE: Gradio is in beta stage, please report all bugs to: a12d@stanford.edu\n",
"Model available locally at: http://localhost:7879/interface.html\n", "Model available locally at: http://localhost:7861/interface.html\n",
"Model available publicly for 8 hours at: http://31f97c1d.ngrok.io/interface.html\n" "Model available publicly for 8 hours at: https://fe2a5e78.ngrok.io/interface.html\n"
] ]
} }
], ],
@ -82,9 +73,9 @@
], ],
"metadata": { "metadata": {
"kernelspec": { "kernelspec": {
"display_name": "Python 3", "display_name": "Python 3.6 (tensorflow)",
"language": "python", "language": "python",
"name": "python3" "name": "tensorflow"
}, },
"language_info": { "language_info": {
"codemirror_mode": { "codemirror_mode": {
@ -96,7 +87,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.7.1" "version": "3.6.7"
} }
}, },
"nbformat": 4, "nbformat": 4,

95
Emotional Detector (Webcam).ipynb Normal file
View File

@ -0,0 +1,95 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using TensorFlow backend.\n"
]
}
],
"source": [
"import numpy as np\n",
"import sklearn\n",
"import gradio\n",
"from keras.models import load_model\n",
"\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Load an Facial Emotion Detector Model"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"model = load_model('.models/emotion.h5')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"def post_p(prediction): \n",
" emotional_dict = {0: \"Angry\", 1: \"Disgusted\", 2: \"Fearful\", 3: \"Happy\", 4: \"Neutral\", 5: \"Sad\", 6: \"Surprised\"}\n",
" return emotional_dict[prediction.squeeze().argmax()]"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"NOTE: Gradio is in beta stage, please report all bugs to: a12d@stanford.edu\n",
"Model available locally at: http://localhost:7861/interface.html\n",
"Model available publicly for 8 hours at: https://fe2a5e78.ngrok.io/interface.html\n"
]
}
],
"source": [
"iface = gradio.Interface(input='webcam', output='class', model=model, model_type='keras',postprocessing_fn=post_p)\n",
"iface.launch()"
]
}
],
"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
}

20
Test Notebook.ipynb → MNIST Handwritten Digits.ipynb
View File

@ -28,6 +28,13 @@
"%autoreload 2" "%autoreload 2"
] ]
}, },
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Load MNIST Model"
]
},
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": 2,
@ -39,9 +46,16 @@
"model = load_model('.models/mnist-cnn.h5')" "model = load_model('.models/mnist-cnn.h5')"
] ]
}, },
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Run Interface"
]
},
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": 3,
"metadata": { "metadata": {
"scrolled": true "scrolled": true
}, },
@ -51,8 +65,8 @@
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"NOTE: Gradio is in beta stage, please report all bugs to: a12d@stanford.edu\n", "NOTE: Gradio is in beta stage, please report all bugs to: a12d@stanford.edu\n",
"Model available locally at: http://localhost:7874/interface.html\n", "Model available locally at: http://localhost:7865/interface.html\n",
"Model available publicly for 8 hours at: http://bb18a5c1.ngrok.io/interface.html\n" "Model available publicly for 8 hours at: http://a0c2eba1.ngrok.io/interface.html\n"
] ]
} }
], ],

24
build/lib/gradio/css/draw-a-digit.css
View File

@ -23,6 +23,30 @@ body {
} }
h1, h2, h3, h4, h5, h6,
.h1, .h2, .h3, .h4, .h5, .h6 {
margin-bottom: 0.5rem;
font-family: inherit;
font-weight: 500;
line-height: 1.2;
color: inherit;
width: 400px;
}
.btn-group > .btn:first-child {
margin-left: 75;
}
.btn-group,
.btn-group-vertical {
position: relative;
display: -ms-inline-flexbox;
display: inline-flex;
vertical-align: middle;
width:400px;
align-items: center;
}
.uploader {position:relative; overflow:hidden; width:400px; height:400px; background:#f3f3f3; border:2px dashed #e8e8e8; font-family: "Arial"; font-size: 40px; color: darkolivegreen;} .uploader {position:relative; overflow:hidden; width:400px; height:400px; background:#f3f3f3; border:2px dashed #e8e8e8; font-family: "Arial"; font-size: 40px; color: darkolivegreen;}
#filePhoto{ #filePhoto{

4
build/lib/gradio/js/all-io.js
View File

@ -1,4 +1,4 @@
var NGROK_URL = "ws://b09c2edb.ngrok.io" var NGROK_URL = "ws://0076f141.ngrok.io"
var SOCKET_PORT = 9200 var SOCKET_PORT = 9200
try { try {
@ -6,7 +6,7 @@ try {
if (origin.includes("ngrok")){ if (origin.includes("ngrok")){
var ws = new WebSocket(NGROK_URL) var ws = new WebSocket(NGROK_URL)
} else { } else {
var ws = new WebSocket("ws://127.0.0.1:9200/") var ws = new WebSocket("ws://127.0.0.1:" + SOCKET_PORT + "/")
} }
ws.onerror = function(evt) { ws.onerror = function(evt) {
console.log(evt) console.log(evt)

2
build/lib/gradio/templates/class_output.html
View File

@ -1,5 +1,5 @@
<div class="col-6"> <div class="col-6">
<h5></h5><br> <h5>Class Output:</h5>
<div id="predict_div" style="background-color:grey"> <div id="predict_div" style="background-color:grey">
</div> </div>

2
build/lib/gradio/templates/image_upload_input.html
View File

@ -14,7 +14,7 @@
--> -->
<div class="col-6"> <div class="col-6">
<h5 style="text-align: center">Image Upload Input:</h5> <div> <h5>Image Upload Input:</h5> </div>
<div class="uploader" style="text-align: center; vertical-align: middle" onclick="$('#filePhoto').click()"> <div class="uploader" style="text-align: center; vertical-align: middle" onclick="$('#filePhoto').click()">
<br>Click here <br> or <br> drag and drop <br>an image <br>Click here <br> or <br> drag and drop <br>an image

BIN
dist/gradio-0.1.5-py3-none-any.whl → dist/gradio-0.1.6-py3-none-any.whl vendored
View File

Binary file not shown.

2
gradio.egg-info/PKG-INFO
View File

@ -1,6 +1,6 @@
Metadata-Version: 1.0 Metadata-Version: 1.0
Name: gradio Name: gradio
Version: 0.1.5 Version: 0.1.6
Summary: Python library for easily interacting with trained machine learning models Summary: Python library for easily interacting with trained machine learning models
Home-page: https://github.com/abidlabs/gradio Home-page: https://github.com/abidlabs/gradio
Author: Abubakar Abid Author: Abubakar Abid

4
gradio/js/all-io.js
View File

@ -1,4 +1,4 @@
var NGROK_URL = "wss://ac0577fa.ngrok.io" var NGROK_URL = "ws://0076f141.ngrok.io"
var SOCKET_PORT = 9200 var SOCKET_PORT = 9200
try { try {
@ -6,7 +6,7 @@ try {
if (origin.includes("ngrok")){ if (origin.includes("ngrok")){
var ws = new WebSocket(NGROK_URL) var ws = new WebSocket(NGROK_URL)
} else { } else {
var ws = new WebSocket("ws://127.0.0.1:9200/") var ws = new WebSocket("ws://127.0.0.1:" + SOCKET_PORT + "/")
} }
ws.onerror = function(evt) { ws.onerror = function(evt) {
console.log(evt) console.log(evt)

4
js/all-io.js
View File

@ -1,5 +1,5 @@
var NGROK_URL = "ws://225e0da0.ngrok.io" var NGROK_URL = "ws://9828e92a.ngrok.io"
var SOCKET_PORT = 9201 var SOCKET_PORT = 9200
try { try {
var origin = window.location.origin; var origin = window.location.origin;

2
setup.py
View File

@ -5,7 +5,7 @@ except ImportError:
setup( setup(
name='gradio', name='gradio',
version='0.1.5', version='0.1.6',
include_package_data=True, include_package_data=True,
description='Python library for easily interacting with trained machine learning models', description='Python library for easily interacting with trained machine learning models',
author='Abubakar Abid', author='Abubakar Abid',