mirror of
https://github.com/gradio-app/gradio.git
synced 2025-01-30 11:00:11 +08:00
merged
This commit is contained in:
Abubakar Abid
commit
f8f31fb5d4
1
.gitignore
vendored
1
.gitignore
vendored
@ -6,4 +6,3 @@ staticfiles
|
||||
.idea/*
|
||||
.ipynb_checkpoints/*
|
||||
.models/*
|
||||
|
||||
|
||||
@ -2,10 +2,14 @@
|
||||
<project version="4">
|
||||
<component name="ChangeListManager">
|
||||
<list default="true" id="fd73cd66-e80f-470e-a2ec-e220d3b6b864" name="Default Changelist" comment="">
|
||||
<change afterPath="$PROJECT_DIR$/Usage.ipynb" afterDir="false" />
|
||||
<change beforePath="$PROJECT_DIR$/.gitignore" beforeDir="false" afterPath="$PROJECT_DIR$/.gitignore" afterDir="false" />
|
||||
<change beforePath="$PROJECT_DIR$/.idea/workspace.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/workspace.xml" afterDir="false" />
|
||||
<change beforePath="$PROJECT_DIR$/.ipynb_checkpoints/Emotion Detector-checkpoint.ipynb" beforeDir="false" afterPath="$PROJECT_DIR$/.ipynb_checkpoints/Emotion Detector-checkpoint.ipynb" afterDir="false" />
|
||||
<change beforePath="$PROJECT_DIR$/Emotion Detector.ipynb" beforeDir="false" />
|
||||
<change beforePath="$PROJECT_DIR$/Test Notebook.ipynb" beforeDir="false" afterPath="$PROJECT_DIR$/Test Notebook.ipynb" afterDir="false" />
|
||||
<change beforePath="$PROJECT_DIR$/gradio.py" beforeDir="false" afterPath="$PROJECT_DIR$/gradio.py" afterDir="false" />
|
||||
<change beforePath="$PROJECT_DIR$/networking.py" beforeDir="false" afterPath="$PROJECT_DIR$/networking.py" afterDir="false" />
|
||||
<change beforePath="$PROJECT_DIR$/js/class-output.js" beforeDir="false" afterPath="$PROJECT_DIR$/js/class-output.js" afterDir="false" />
|
||||
</list>
|
||||
<option name="EXCLUDED_CONVERTED_TO_IGNORED" value="true" />
|
||||
<option name="SHOW_DIALOG" value="false" />
|
||||
@ -73,6 +77,7 @@
|
||||
</usages-collector>
|
||||
<usages-collector id="statistics.file.extensions.open">
|
||||
<counts>
|
||||
<entry key="gitignore" value="1" />
|
||||
<entry key="ipynb" value="1" />
|
||||
<entry key="py" value="5" />
|
||||
</counts>
|
||||
@ -80,34 +85,27 @@
|
||||
<usages-collector id="statistics.file.types.open">
|
||||
<counts>
|
||||
<entry key="IPNB" value="1" />
|
||||
<entry key="PLAIN_TEXT" value="1" />
|
||||
<entry key="Python" value="5" />
|
||||
</counts>
|
||||
</usages-collector>
|
||||
<usages-collector id="statistics.file.extensions.edit">
|
||||
<counts>
|
||||
<entry key="dummy" value="10" />
|
||||
<entry key="py" value="1788" />
|
||||
<entry key="gitignore" value="2" />
|
||||
<entry key="py" value="1804" />
|
||||
</counts>
|
||||
</usages-collector>
|
||||
<usages-collector id="statistics.file.types.edit">
|
||||
<counts>
|
||||
<entry key="PLAIN_TEXT" value="10" />
|
||||
<entry key="Python" value="1788" />
|
||||
<entry key="PLAIN_TEXT" value="12" />
|
||||
<entry key="Python" value="1804" />
|
||||
</counts>
|
||||
</usages-collector>
|
||||
</session>
|
||||
</component>
|
||||
<component name="FileEditorManager">
|
||||
<leaf SIDE_TABS_SIZE_LIMIT_KEY="300">
|
||||
<file pinned="false" current-in-tab="false">
|
||||
<entry file="file://$PROJECT_DIR$/templates/draw_a_digit.html">
|
||||
<provider selected="true" editor-type-id="text-editor">
|
||||
<state relative-caret-position="375">
|
||||
<caret line="15" column="9" selection-start-line="15" selection-start-column="9" selection-end-line="15" selection-end-column="9" />
|
||||
</state>
|
||||
</provider>
|
||||
</entry>
|
||||
</file>
|
||||
<file pinned="false" current-in-tab="false">
|
||||
<entry file="file://$PROJECT_DIR$/index.html">
|
||||
<provider selected="true" editor-type-id="text-editor">
|
||||
@ -165,8 +163,8 @@
|
||||
<file pinned="false" current-in-tab="true">
|
||||
<entry file="file://$PROJECT_DIR$/gradio.py">
|
||||
<provider selected="true" editor-type-id="text-editor">
|
||||
<state relative-caret-position="466">
|
||||
<caret line="192" column="41" selection-start-line="192" selection-start-column="41" selection-end-line="192" selection-end-column="41" />
|
||||
<state relative-caret-position="366">
|
||||
<caret line="200" column="36" lean-forward="true" selection-start-line="200" selection-start-column="36" selection-end-line="200" selection-end-column="36" />
|
||||
<folding>
|
||||
<element signature="e#0#35#0" expanded="true" />
|
||||
</folding>
|
||||
@ -174,6 +172,15 @@
|
||||
</provider>
|
||||
</entry>
|
||||
</file>
|
||||
<file pinned="false" current-in-tab="false">
|
||||
<entry file="file://$PROJECT_DIR$/.gitignore">
|
||||
<provider selected="true" editor-type-id="text-editor">
|
||||
<state relative-caret-position="175">
|
||||
<caret line="7" selection-start-line="7" selection-end-line="7" />
|
||||
</state>
|
||||
</provider>
|
||||
</entry>
|
||||
</file>
|
||||
<file pinned="false" current-in-tab="false">
|
||||
<entry file="file://$PROJECT_DIR$/networking.py">
|
||||
<provider selected="true" editor-type-id="text-editor">
|
||||
@ -282,6 +289,7 @@
|
||||
<option value="$PROJECT_DIR$/preprocessing_utils.py" />
|
||||
<option value="$PROJECT_DIR$/inputs.py" />
|
||||
<option value="$PROJECT_DIR$/networking.py" />
|
||||
<option value="$PROJECT_DIR$/.gitignore" />
|
||||
<option value="$PROJECT_DIR$/gradio.py" />
|
||||
</list>
|
||||
</option>
|
||||
@ -516,10 +524,17 @@
|
||||
</state>
|
||||
</provider>
|
||||
</entry>
|
||||
<entry file="file://$PROJECT_DIR$/.gitignore">
|
||||
<provider selected="true" editor-type-id="text-editor">
|
||||
<state relative-caret-position="175">
|
||||
<caret line="7" selection-start-line="7" selection-end-line="7" />
|
||||
</state>
|
||||
</provider>
|
||||
</entry>
|
||||
<entry file="file://$PROJECT_DIR$/gradio.py">
|
||||
<provider selected="true" editor-type-id="text-editor">
|
||||
<state relative-caret-position="466">
|
||||
<caret line="192" column="41" selection-start-line="192" selection-start-column="41" selection-end-line="192" selection-end-column="41" />
|
||||
<state relative-caret-position="366">
|
||||
<caret line="200" column="36" lean-forward="true" selection-start-line="200" selection-start-column="36" selection-end-line="200" selection-end-column="36" />
|
||||
<folding>
|
||||
<element signature="e#0#35#0" expanded="true" />
|
||||
</folding>
|
||||
|
||||
@ -2,6 +2,7 @@
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
<<<<<<< HEAD
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -99,20 +100,41 @@
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
=======
|
||||
"execution_count": 14,
|
||||
>>>>>>> 6aaa97e586a26410e46fa4cc80907293e1f079f9
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stderr",
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Using TensorFlow backend.\n"
|
||||
"The autoreload extension is already loaded. To reload it, use:\n",
|
||||
" %reload_ext autoreload\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
<<<<<<< HEAD
|
||||
"import sklearn\n",
|
||||
"import gradio\n",
|
||||
=======
|
||||
"import base64\n",
|
||||
"from PIL import Image\n",
|
||||
"import tensorflow as tf\n",
|
||||
"import sklearn\n",
|
||||
"import gradio\n",
|
||||
"from io import BytesIO\n",
|
||||
"\n",
|
||||
"from keras.models import Sequential\n",
|
||||
"from keras.layers import Dense, Dropout, Activation, Flatten\n",
|
||||
"from keras.layers import Conv2D, MaxPooling2D, BatchNormalization\n",
|
||||
"from keras.losses import categorical_crossentropy\n",
|
||||
"from keras.optimizers import Adam\n",
|
||||
"from keras.regularizers import l2\n",
|
||||
"from keras.callbacks import ReduceLROnPlateau, TensorBoard, EarlyStopping, ModelCheckpoint\n",
|
||||
>>>>>>> 6aaa97e586a26410e46fa4cc80907293e1f079f9
|
||||
"from keras.models import load_model\n",
|
||||
"\n",
|
||||
"%load_ext autoreload\n",
|
||||
@ -121,7 +143,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
@ -130,20 +152,127 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def postprocessing(prediction):\n",
|
||||
" \"\"\"\n",
|
||||
" \"\"\"\n",
|
||||
" emotion_dict = {0: \"DANGEROUS\", 1: \"DANGEROUS\", 2: \"DANGEROUS\", 3: \"DANGEROUS\", 4: \"DANGEROUS\", 5: \"DANGEROUS\", 6: \"DANGEROUS\"}\n",
|
||||
" return emotion_dict[prediction] "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 16,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"\n",
|
||||
"def resize_and_crop(img, size, crop_type='top'):\n",
|
||||
" \"\"\"\n",
|
||||
" Resize and crop an image to fit the specified size.\n",
|
||||
" args:\n",
|
||||
" img_path: path for the image to resize.\n",
|
||||
" modified_path: path to store the modified image.\n",
|
||||
" size: `(width, height)` tuple.\n",
|
||||
" crop_type: can be 'top', 'middle' or 'bottom', depending on this\n",
|
||||
" value, the image will cropped getting the 'top/left', 'midle' or\n",
|
||||
" 'bottom/rigth' of the image to fit the size.\n",
|
||||
" raises:\n",
|
||||
" Exception: if can not open the file in img_path of there is problems\n",
|
||||
" to save the image.\n",
|
||||
" ValueError: if an invalid `crop_type` is provided.\n",
|
||||
" \"\"\"\n",
|
||||
" # Get current and desired ratio for the images\n",
|
||||
" img_ratio = img.size[0] / float(img.size[1])\n",
|
||||
" ratio = size[0] / float(size[1])\n",
|
||||
" # The image is scaled/cropped vertically or horizontally depending on the ratio\n",
|
||||
" if ratio > img_ratio:\n",
|
||||
" img = img.resize((size[0], size[0] * img.size[1] / img.size[0]),\n",
|
||||
" Image.ANTIALIAS)\n",
|
||||
" # Crop in the top, middle or bottom\n",
|
||||
" if crop_type == 'top':\n",
|
||||
" box = (0, 0, img.size[0], size[1])\n",
|
||||
" elif crop_type == 'middle':\n",
|
||||
" box = (0, (img.size[1] - size[1]) / 2, img.size[0], (img.size[1] + size[1]) / 2)\n",
|
||||
" elif crop_type == 'bottom':\n",
|
||||
" box = (0, img.size[1] - size[1], img.size[0], img.size[1])\n",
|
||||
" else:\n",
|
||||
" raise ValueError('ERROR: invalid value for crop_type')\n",
|
||||
" img = img.crop(box)\n",
|
||||
" elif ratio < img_ratio:\n",
|
||||
" img = img.resize((size[1] * img.size[0] / img.size[1], size[1]),\n",
|
||||
" Image.ANTIALIAS)\n",
|
||||
" # Crop in the top, middle or bottom\n",
|
||||
" if crop_type == 'top':\n",
|
||||
" box = (0, 0, size[0], img.size[1])\n",
|
||||
" elif crop_type == 'middle':\n",
|
||||
" box = ((img.size[0] - size[0]) / 2, 0, (img.size[0] + size[0]) / 2, img.size[1])\n",
|
||||
" elif crop_type == 'bottom':\n",
|
||||
" box = (img.size[0] - size[0], 0, img.size[0], img.size[1])\n",
|
||||
" else:\n",
|
||||
" raise ValueError('ERROR: invalid value for crop_type')\n",
|
||||
" img = img.crop(box)\n",
|
||||
" else:\n",
|
||||
" img = img.resize((size[0], size[1]),\n",
|
||||
" Image.ANTIALIAS)\n",
|
||||
" # If the scale is the same, we do not need to crop\n",
|
||||
" return img\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 17,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def pre_p(imgstring): \n",
|
||||
" content = imgstring.split(';')[1]\n",
|
||||
" image_encoded = content.split(',')[1]\n",
|
||||
" body = base64.decodebytes(image_encoded.encode('utf-8'))\n",
|
||||
" im = Image.open(BytesIO(base64.b64decode(image_encoded))).convert('L')\n",
|
||||
" im = resize_and_crop(im, (28, 28))\n",
|
||||
" array = np.array(im).flatten().reshape(1, -1)\n",
|
||||
" return array \n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 19,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
<<<<<<< HEAD
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"http://localhost:6002/templates/tmp_html.html\n"
|
||||
=======
|
||||
"ename": "OSError",
|
||||
"evalue": "[Errno 10048] error while attempting to bind on address ('127.0.0.1', 5680): only one usage of each socket address (protocol/network address/port) is normally permitted",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[1;31mOSError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[1;32m<ipython-input-19-121213b76e06>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0miface\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgradio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mInterface\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'webcam'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0moutput\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'class'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mmodel_obj\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmodel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmodel_type\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'keras'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mpreprocessing_fn\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mpre_p\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mpostprocessing_fn\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mpostprocessing\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0miface\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlaunch\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[1;32m~\\Desktop\\gradiome\\gradio.py\u001b[0m in \u001b[0;36mlaunch\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 241\u001b[0m \u001b[0mwebbrowser\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'file://'\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrealpath\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_build_template\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 242\u001b[0m \u001b[0mstart_server\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mwebsockets\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mserve\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcommunicate\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mLOCALHOST_IP\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mSOCKET_PORT\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 243\u001b[1;33m \u001b[0masyncio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_event_loop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun_until_complete\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstart_server\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 244\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 245\u001b[0m \u001b[0masyncio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_event_loop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun_forever\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\nest_asyncio.py\u001b[0m in \u001b[0;36mrun_until_complete\u001b[1;34m(self, future)\u001b[0m\n\u001b[0;32m 59\u001b[0m \u001b[1;32mwhile\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdone\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 60\u001b[0m \u001b[0mrun_once\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 61\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 62\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 63\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_run_until_complete_orig\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfuture\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;32m~\\Anaconda3\\lib\\asyncio\\futures.py\u001b[0m in \u001b[0;36mresult\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 176\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__log_traceback\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 177\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_exception\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 178\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_exception\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 179\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_result\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 180\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;32m~\\Anaconda3\\lib\\asyncio\\tasks.py\u001b[0m in \u001b[0;36m__step\u001b[1;34m(***failed resolving arguments***)\u001b[0m\n\u001b[0;32m 221\u001b[0m \u001b[1;31m# We use the `send` method directly, because coroutines\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 222\u001b[0m \u001b[1;31m# don't have `__iter__` and `__next__` methods.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 223\u001b[1;33m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcoro\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 224\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 225\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcoro\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mthrow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mexc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;32m~\\Anaconda3\\lib\\asyncio\\tasks.py\u001b[0m in \u001b[0;36m_wrap_awaitable\u001b[1;34m(awaitable)\u001b[0m\n\u001b[0;32m 601\u001b[0m \u001b[0mthat\u001b[0m \u001b[0mwill\u001b[0m \u001b[0mlater\u001b[0m \u001b[0mbe\u001b[0m \u001b[0mwrapped\u001b[0m \u001b[1;32min\u001b[0m \u001b[0ma\u001b[0m \u001b[0mTask\u001b[0m \u001b[0mby\u001b[0m \u001b[0mensure_future\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 602\u001b[0m \"\"\"\n\u001b[1;32m--> 603\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;32myield\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mawaitable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__await__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 604\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 605\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\websockets\\py35\\server.py\u001b[0m in \u001b[0;36m__await_impl__\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 11\u001b[0m \u001b[1;31m# Duplicated with __iter__ because Python 3.7 requires an async function\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 12\u001b[0m \u001b[1;31m# (as explained in __await__ below) which Python 3.4 doesn't support.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 13\u001b[1;33m \u001b[0mserver\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mawait\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_creating_server\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 14\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mws_server\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mserver\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 15\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mws_server\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;32m~\\Anaconda3\\lib\\asyncio\\base_events.py\u001b[0m in \u001b[0;36mcreate_server\u001b[1;34m(self, protocol_factory, host, port, family, flags, sock, backlog, ssl, reuse_address, reuse_port, ssl_handshake_timeout, start_serving)\u001b[0m\n\u001b[0;32m 1365\u001b[0m raise OSError(err.errno, 'error while attempting '\n\u001b[0;32m 1366\u001b[0m \u001b[1;34m'to bind on address %r: %s'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1367\u001b[1;33m % (sa, err.strerror.lower())) from None\n\u001b[0m\u001b[0;32m 1368\u001b[0m \u001b[0mcompleted\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1369\u001b[0m \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;31mOSError\u001b[0m: [Errno 10048] error while attempting to bind on address ('127.0.0.1', 5680): only one usage of each socket address (protocol/network address/port) is normally permitted"
|
||||
>>>>>>> 6aaa97e586a26410e46fa4cc80907293e1f079f9
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
<<<<<<< HEAD
|
||||
"C:\\Users\\islam\\Repos\\gradio\\gradio.py:194: UserWarning: No parser was explicitly specified, so I'm using the best available HTML parser for this system (\"html.parser\"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently.\n",
|
||||
"\n",
|
||||
"The code that caused this warning is on line 194 of the file C:\\Users\\islam\\Repos\\gradio\\gradio.py. To get rid of this warning, pass the additional argument 'features=\"html.parser\"' to the BeautifulSoup constructor.\n",
|
||||
@ -170,11 +299,32 @@
|
||||
" File \"C:\\Users\\islam\\Anaconda3\\envs\\tensorflow\\lib\\site-packages\\websockets\\protocol.py\", line 646, in ensure_open\n",
|
||||
" ) from self.transfer_data_exc\n",
|
||||
"websockets.exceptions.ConnectionClosed: WebSocket connection is closed: code = 1001 (going away), no reason\n"
|
||||
=======
|
||||
"Error in connection handler\n",
|
||||
"Traceback (most recent call last):\n",
|
||||
" File \"C:\\Users\\ALI\\Anaconda3\\lib\\site-packages\\websockets\\server.py\", line 169, in handler\n",
|
||||
" yield from self.ws_handler(self, path)\n",
|
||||
" File \"C:\\Users\\ALI\\Desktop\\gradiome\\gradio.py\", line 228, in communicate\n",
|
||||
" prediction = self.predict(processed_input)\n",
|
||||
" File \"C:\\Users\\ALI\\Desktop\\gradiome\\gradio.py\", line 211, in predict\n",
|
||||
" return self.model_obj.predict(array)[0].argmax()\n",
|
||||
" File \"C:\\Users\\ALI\\Anaconda3\\lib\\site-packages\\keras\\engine\\training.py\", line 1149, in predict\n",
|
||||
" x, _, _ = self._standardize_user_data(x)\n",
|
||||
" File \"C:\\Users\\ALI\\Anaconda3\\lib\\site-packages\\keras\\engine\\training.py\", line 751, in _standardize_user_data\n",
|
||||
" exception_prefix='input')\n",
|
||||
" File \"C:\\Users\\ALI\\Anaconda3\\lib\\site-packages\\keras\\engine\\training_utils.py\", line 128, in standardize_input_data\n",
|
||||
" 'with shape ' + str(data_shape))\n",
|
||||
"ValueError: Error when checking input: expected conv2d_1_input to have 4 dimensions, but got array with shape (1, 784)\n"
|
||||
>>>>>>> 6aaa97e586a26410e46fa4cc80907293e1f079f9
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
<<<<<<< HEAD
|
||||
"iface = gradio.Interface(input='webcam',output='class',model_obj=model, model_type='keras')\n",
|
||||
=======
|
||||
"iface = gradio.Interface(input='webcam',output='class',model_obj=model, model_type='keras',postprocessing_fn=postprocessing)\n",
|
||||
>>>>>>> 6aaa97e586a26410e46fa4cc80907293e1f079f9
|
||||
"iface.launch()"
|
||||
]
|
||||
},
|
||||
|
||||
@ -1,237 +0,0 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
},
|
||||
{
|
||||
"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": "code",
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"model = load_model('model.h5') # found random emotion detector model on github ''(its not very accurate)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"http://localhost:6002/templates/tmp_html.html\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"C:\\Users\\islam\\Repos\\gradio\\gradio.py:194: UserWarning: No parser was explicitly specified, so I'm using the best available HTML parser for this system (\"html.parser\"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently.\n",
|
||||
"\n",
|
||||
"The code that caused this warning is on line 194 of the file C:\\Users\\islam\\Repos\\gradio\\gradio.py. To get rid of this warning, pass the additional argument 'features=\"html.parser\"' to the BeautifulSoup constructor.\n",
|
||||
"\n",
|
||||
" input_soup = BeautifulSoup(input_page.read())\n",
|
||||
"C:\\Users\\islam\\Repos\\gradio\\gradio.py:195: UserWarning: No parser was explicitly specified, so I'm using the best available HTML parser for this system (\"html.parser\"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently.\n",
|
||||
"\n",
|
||||
"The code that caused this warning is on line 195 of the file C:\\Users\\islam\\Repos\\gradio\\gradio.py. To get rid of this warning, pass the additional argument 'features=\"html.parser\"' to the BeautifulSoup constructor.\n",
|
||||
"\n",
|
||||
" output_soup = BeautifulSoup(output_page.read())\n",
|
||||
"C:\\Users\\islam\\Repos\\gradio\\gradio.py:199: UserWarning: No parser was explicitly specified, so I'm using the best available HTML parser for this system (\"html.parser\"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently.\n",
|
||||
"\n",
|
||||
"The code that caused this warning is on line 199 of the file C:\\Users\\islam\\Repos\\gradio\\gradio.py. To get rid of this warning, pass the additional argument 'features=\"html.parser\"' to the BeautifulSoup constructor.\n",
|
||||
"\n",
|
||||
" all_io_soup = BeautifulSoup(all_io_page.read())\n",
|
||||
"Error in connection handler\n",
|
||||
"Traceback (most recent call last):\n",
|
||||
" File \"C:\\Users\\islam\\Anaconda3\\envs\\tensorflow\\lib\\site-packages\\websockets\\server.py\", line 169, in handler\n",
|
||||
" yield from self.ws_handler(self, path)\n",
|
||||
" File \"C:\\Users\\islam\\Repos\\gradio\\gradio.py\", line 226, in communicate\n",
|
||||
" processed_input = self.input_interface._pre_process(await websocket.recv())\n",
|
||||
" File \"C:\\Users\\islam\\Anaconda3\\envs\\tensorflow\\lib\\site-packages\\websockets\\protocol.py\", line 434, in recv\n",
|
||||
" yield from self.ensure_open()\n",
|
||||
" File \"C:\\Users\\islam\\Anaconda3\\envs\\tensorflow\\lib\\site-packages\\websockets\\protocol.py\", line 646, in ensure_open\n",
|
||||
" ) from self.transfer_data_exc\n",
|
||||
"websockets.exceptions.ConnectionClosed: WebSocket connection is closed: code = 1001 (going away), no reason\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"iface = gradio.Interface(input='webcam',output='class',model_obj=model, model_type='keras')\n",
|
||||
"iface.launch()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"serving at port 7000\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Exception in thread Thread-6:\n",
|
||||
"Traceback (most recent call last):\n",
|
||||
" File \"C:\\Users\\islam\\Anaconda3\\envs\\tensorflow\\lib\\threading.py\", line 916, in _bootstrap_inner\n",
|
||||
" self.run()\n",
|
||||
" File \"C:\\Users\\islam\\Anaconda3\\envs\\tensorflow\\lib\\threading.py\", line 864, in run\n",
|
||||
" self._target(*self._args, **self._kwargs)\n",
|
||||
" File \"C:\\Users\\islam\\Anaconda3\\envs\\tensorflow\\lib\\socketserver.py\", line 236, in serve_forever\n",
|
||||
" ready = selector.select(poll_interval)\n",
|
||||
" File \"C:\\Users\\islam\\Anaconda3\\envs\\tensorflow\\lib\\selectors.py\", line 323, in select\n",
|
||||
" r, w, _ = self._select(self._readers, self._writers, [], timeout)\n",
|
||||
" File \"C:\\Users\\islam\\Anaconda3\\envs\\tensorflow\\lib\\selectors.py\", line 314, in _select\n",
|
||||
" r, w, x = select.select(r, w, w, timeout)\n",
|
||||
"OSError: [WinError 10038] An operation was attempted on something that is not a socket\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"import http.server\n",
|
||||
"import socketserver\n",
|
||||
"import os\n",
|
||||
"import threading\n",
|
||||
"\n",
|
||||
"TEMPLATE_DIRECTORY = 'templates'\n",
|
||||
"PORT = 7000\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"web_dir = os.path.realpath(TEMPLATE_DIRECTORY)\n",
|
||||
"os.chdir(web_dir)\n",
|
||||
"Handler = http.server.SimpleHTTPRequestHandler\n",
|
||||
"\n",
|
||||
"with socketserver.TCPServer((\"\", PORT), Handler) as httpd:\n",
|
||||
" print(\"serving at port\", PORT)\n",
|
||||
" t = threading.Thread(target=httpd.serve_forever)\n",
|
||||
" t.start()\n",
|
||||
"\n",
|
||||
"path_to_server = 'localhost:{}/'.format(PORT)\n",
|
||||
"os.chdir('..') # TODO(abidlabs): make this better\n",
|
||||
" "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"serving at port 7000\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"import http.server\n",
|
||||
"import socketserver\n",
|
||||
"import os\n",
|
||||
"import threading\n",
|
||||
"\n",
|
||||
"TEMPLATE_DIRECTORY = 'templates'\n",
|
||||
"PORT = 7000\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"web_dir = os.path.realpath(TEMPLATE_DIRECTORY)\n",
|
||||
"os.chdir(web_dir)\n",
|
||||
"Handler = http.server.SimpleHTTPRequestHandler\n",
|
||||
"\n",
|
||||
"with socketserver.TCPServer((\"\", PORT), Handler) as httpd:\n",
|
||||
" print(\"serving at port\", PORT)\n",
|
||||
" httpd.serve_forever()\n",
|
||||
"# t = threading.Thread(target=httpd.serve_forever)\n",
|
||||
"# t.start()\n",
|
||||
"\n",
|
||||
"path_to_server = 'localhost:{}/'.format(PORT)\n",
|
||||
"os.chdir('..') # TODO(abidlabs): make this better "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import subprocess"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<subprocess.Popen at 0x16a3f8aa390>"
|
||||
]
|
||||
},
|
||||
"execution_count": 8,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"subprocess.Popen(['python', '-m', 'http.server', '6001'])"
|
||||
]
|
||||
}
|
||||
],
|
||||
"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
|
||||
}
|
||||
@ -25,9 +25,18 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"C:\\Users\\islam\\Anaconda3\\envs\\tensorflow\\lib\\site-packages\\keras\\engine\\saving.py:327: UserWarning: Error in loading the saved optimizer state. As a result, your model is starting with a freshly initialized optimizer.\n",
|
||||
" warnings.warn('Error in loading the saved optimizer '\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"model = load_model('.models/mnist-cnn.h5')"
|
||||
]
|
||||
@ -41,7 +50,8 @@
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Model publicly available for 8 hours at: https://57d2bd20.ngrok.io/templates/tmp_html.html\n"
|
||||
"Model available locally at: http://localhost:6002/\n",
|
||||
"Model available publicly for 8 hours at: http://57d2bd20.ngrok.io/templates/tmp_html.html\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
||||
160
Usage.ipynb
Normal file
160
Usage.ipynb
Normal file
@ -0,0 +1,160 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Example Usage of Gradio"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Here is the code to define a model and train it. It may take a few minutes to train on a machine without GPUs"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
"import tensorflow as tf\n",
|
||||
"import sklearn\n",
|
||||
"import gradio\n",
|
||||
"\n",
|
||||
"%load_ext autoreload\n",
|
||||
"%autoreload 2"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"WARNING:tensorflow:From C:\\Users\\ALI\\Anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\resource_variable_ops.py:435: 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\\tensorflow\\python\\keras\\layers\\core.py:143: 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",
|
||||
"60000/60000 [==============================] - 17s 286us/sample - loss: 0.2190 - acc: 0.9358\n",
|
||||
"10000/10000 [==============================] - 0s 49us/sample - loss: 0.1067 - acc: 0.9665\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[0.1066632072519511, 0.9665]"
|
||||
]
|
||||
},
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"mnist = tf.keras.datasets.mnist\n",
|
||||
"\n",
|
||||
"(x_train, y_train),(x_test, y_test) = mnist.load_data()\n",
|
||||
"x_train, x_test = x_train.reshape(-1, 784) / 255.0, x_test.reshape(-1, 784) / 255.0\n",
|
||||
"\n",
|
||||
"model = tf.keras.models.Sequential([\n",
|
||||
" tf.keras.layers.Flatten(),\n",
|
||||
" tf.keras.layers.Dense(512, activation=tf.nn.relu),\n",
|
||||
" tf.keras.layers.Dropout(0.2),\n",
|
||||
" tf.keras.layers.Dense(10, activation=tf.nn.softmax)\n",
|
||||
"])\n",
|
||||
"model.compile(optimizer='adam',\n",
|
||||
" loss='sparse_categorical_crossentropy',\n",
|
||||
" metrics=['accuracy'])\n",
|
||||
"\n",
|
||||
"model.fit(x_train, y_train, epochs=1)\n",
|
||||
"model.evaluate(x_test, y_test)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Here, we simply take the trained model and pass it into **gradio**. When you run this, it should open up a new browser window and show allow you to interact with the model."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"C:\\Users\\ALI\\Desktop\\gradiome\\gradio.py:191: UserWarning: No parser was explicitly specified, so I'm using the best available HTML parser for this system (\"lxml\"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently.\n",
|
||||
"\n",
|
||||
"The code that caused this warning is on line 191 of the file C:\\Users\\ALI\\Desktop\\gradiome\\gradio.py. To get rid of this warning, pass the additional argument 'features=\"lxml\"' to the BeautifulSoup constructor.\n",
|
||||
"\n",
|
||||
" input_soup = BeautifulSoup(input_page.read())\n",
|
||||
"C:\\Users\\ALI\\Desktop\\gradiome\\gradio.py:192: UserWarning: No parser was explicitly specified, so I'm using the best available HTML parser for this system (\"lxml\"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently.\n",
|
||||
"\n",
|
||||
"The code that caused this warning is on line 192 of the file C:\\Users\\ALI\\Desktop\\gradiome\\gradio.py. To get rid of this warning, pass the additional argument 'features=\"lxml\"' to the BeautifulSoup constructor.\n",
|
||||
"\n",
|
||||
" output_soup = BeautifulSoup(output_page.read())\n",
|
||||
"C:\\Users\\ALI\\Desktop\\gradiome\\gradio.py:196: UserWarning: No parser was explicitly specified, so I'm using the best available HTML parser for this system (\"lxml\"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently.\n",
|
||||
"\n",
|
||||
"The code that caused this warning is on line 196 of the file C:\\Users\\ALI\\Desktop\\gradiome\\gradio.py. To get rid of this warning, pass the additional argument 'features=\"lxml\"' to the BeautifulSoup constructor.\n",
|
||||
"\n",
|
||||
" all_io_soup = BeautifulSoup(all_io_page.read())\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"ename": "OSError",
|
||||
"evalue": "[Errno 10048] error while attempting to bind on address ('127.0.0.1', 5680): only one usage of each socket address (protocol/network address/port) is normally permitted",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[1;31mOSError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[1;32m<ipython-input-4-0a9a4dc4acce>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mgradio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mInterface\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'sketchpad'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0moutput\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'class'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mmodel_obj\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmodel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmodel_type\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'keras'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlaunch\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[1;32m~\\Desktop\\gradiome\\gradio.py\u001b[0m in \u001b[0;36mlaunch\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 241\u001b[0m \u001b[0mwebbrowser\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'file://'\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrealpath\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_build_template\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 242\u001b[0m \u001b[0mstart_server\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mwebsockets\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mserve\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcommunicate\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mLOCALHOST_IP\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mSOCKET_PORT\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 243\u001b[1;33m \u001b[0masyncio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_event_loop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun_until_complete\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstart_server\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 244\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 245\u001b[0m \u001b[0masyncio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_event_loop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun_forever\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\nest_asyncio.py\u001b[0m in \u001b[0;36mrun_until_complete\u001b[1;34m(self, future)\u001b[0m\n\u001b[0;32m 59\u001b[0m \u001b[1;32mwhile\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdone\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 60\u001b[0m \u001b[0mrun_once\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 61\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 62\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 63\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_run_until_complete_orig\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfuture\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;32m~\\Anaconda3\\lib\\asyncio\\futures.py\u001b[0m in \u001b[0;36mresult\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 176\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__log_traceback\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 177\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_exception\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 178\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_exception\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 179\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_result\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 180\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;32m~\\Anaconda3\\lib\\asyncio\\tasks.py\u001b[0m in \u001b[0;36m__step\u001b[1;34m(***failed resolving arguments***)\u001b[0m\n\u001b[0;32m 221\u001b[0m \u001b[1;31m# We use the `send` method directly, because coroutines\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 222\u001b[0m \u001b[1;31m# don't have `__iter__` and `__next__` methods.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 223\u001b[1;33m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcoro\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 224\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 225\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcoro\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mthrow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mexc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;32m~\\Anaconda3\\lib\\asyncio\\tasks.py\u001b[0m in \u001b[0;36m_wrap_awaitable\u001b[1;34m(awaitable)\u001b[0m\n\u001b[0;32m 601\u001b[0m \u001b[0mthat\u001b[0m \u001b[0mwill\u001b[0m \u001b[0mlater\u001b[0m \u001b[0mbe\u001b[0m \u001b[0mwrapped\u001b[0m \u001b[1;32min\u001b[0m \u001b[0ma\u001b[0m \u001b[0mTask\u001b[0m \u001b[0mby\u001b[0m \u001b[0mensure_future\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 602\u001b[0m \"\"\"\n\u001b[1;32m--> 603\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;32myield\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mawaitable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__await__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 604\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 605\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\websockets\\py35\\server.py\u001b[0m in \u001b[0;36m__await_impl__\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 11\u001b[0m \u001b[1;31m# Duplicated with __iter__ because Python 3.7 requires an async function\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 12\u001b[0m \u001b[1;31m# (as explained in __await__ below) which Python 3.4 doesn't support.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 13\u001b[1;33m \u001b[0mserver\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mawait\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_creating_server\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 14\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mws_server\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mserver\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 15\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mws_server\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;32m~\\Anaconda3\\lib\\asyncio\\base_events.py\u001b[0m in \u001b[0;36mcreate_server\u001b[1;34m(self, protocol_factory, host, port, family, flags, sock, backlog, ssl, reuse_address, reuse_port, ssl_handshake_timeout, start_serving)\u001b[0m\n\u001b[0;32m 1365\u001b[0m raise OSError(err.errno, 'error while attempting '\n\u001b[0;32m 1366\u001b[0m \u001b[1;34m'to bind on address %r: %s'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1367\u001b[1;33m % (sa, err.strerror.lower())) from None\n\u001b[0m\u001b[0;32m 1368\u001b[0m \u001b[0mcompleted\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1369\u001b[0m \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[1;31mOSError\u001b[0m: [Errno 10048] error while attempting to bind on address ('127.0.0.1', 5680): only one usage of each socket address (protocol/network address/port) is normally permitted"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
" gradio.Interface(input='sketchpad',output='class',model_obj=model, model_type='keras').launch()"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
19
gradio.py
19
gradio.py
@ -122,7 +122,7 @@ class Interface():
|
||||
"""
|
||||
build_template_path = 'templates/tmp_html.html'
|
||||
|
||||
def __init__(self, input, output, model_obj, model_type, **model_params):
|
||||
def __init__(self, input, output, model_obj, model_type, preprocessing_fn=None, postprocessing_fn=None):
|
||||
"""
|
||||
:param model_type: what kind of trained model, can be 'keras' or 'sklearn'.
|
||||
:param model_obj: the model object, such as a sklearn classifier or keras model.
|
||||
@ -132,7 +132,8 @@ class Interface():
|
||||
self.output_interface = registry[output]()
|
||||
self.model_type = model_type
|
||||
self.model_obj = model_obj
|
||||
self.model_params = model_params
|
||||
self.preprocessing_fn = preprocessing_fn
|
||||
self.postprocessing_fn = postprocessing_fn
|
||||
|
||||
def _build_template(self):
|
||||
input_template_path = self.input_interface._get_template_path()
|
||||
@ -174,9 +175,19 @@ class Interface():
|
||||
while True:
|
||||
try:
|
||||
msg = await websocket.recv()
|
||||
processed_input = self.input_interface._pre_process(msg)
|
||||
|
||||
if self.preprocessing_fn is None:
|
||||
processed_input = self.input_interface._pre_process(await websocket.recv())
|
||||
else:
|
||||
processed_input = self.preprocessing_fn(await websocket.recv())
|
||||
|
||||
prediction = self.predict(processed_input)
|
||||
processed_output = self.output_interface._post_process(prediction)
|
||||
|
||||
if self.postprocessing_fn is None:
|
||||
processed_output = self.output_interface._post_process(prediction)
|
||||
else:
|
||||
processed_output = self.postprocessing_fn(prediction)
|
||||
|
||||
await websocket.send(str(processed_output))
|
||||
except websockets.exceptions.ConnectionClosed:
|
||||
pass
|
||||
|
||||
@ -30,10 +30,11 @@ try {
|
||||
ws.onmessage = function (event) {
|
||||
console.log(event.data);
|
||||
predict_ctx.clearRect(0, 0, 400, 400); // Clears the canvas
|
||||
predict_ctx.font = "60px Arial";
|
||||
predict_ctx.font = String(400/(event.data.length*1.1)) + "px Arial";
|
||||
console.log(predict_ctx.font);
|
||||
predict_ctx.fillStyle = "white";
|
||||
sleep(300).then(() => {
|
||||
predict_ctx.textAlign = "center";
|
||||
predict_ctx.textAlign = "center";
|
||||
predict_ctx.fillText(event.data, 200, 200);
|
||||
})
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user