diff --git a/Test Notebook.ipynb b/Test Notebook.ipynb index 4c24633201..3225651420 100644 --- a/Test Notebook.ipynb +++ b/Test Notebook.ipynb @@ -1,5 +1,12 @@ { "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Load the Model" + ] + }, { "cell_type": "code", "execution_count": 1, @@ -23,11 +30,317 @@ "model = tf.keras.applications.inception_v3.InceptionV3()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feed An Image Into the Model Manually" + ] + }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], + "source": [ + "from PIL import Image\n", + "import requests\n", + "from io import BytesIO\n", + "\n", + "url = 'https://nationalzoo.si.edu/sites/default/files/animals/cheetah-004.jpg'\n", + "\n", + "response = requests.get(url)\n", + "img = Image.open(BytesIO(response.content))\n", + "\n", + "# resize the image into an array that the model can accept\n", + "img = np.array(img.resize((299, 299))).reshape((1, 299, 299, 3))\n", + "\n", + "# scale the image and do other preprocessing\n", + "img = img/255" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[2.87348394e-05, 3.31625670e-05, 2.48761153e-05, 2.91672295e-05,\n", + " 1.58476214e-05, 2.04349963e-05, 2.29794769e-05, 2.98258401e-05,\n", + " 7.79210823e-05, 1.14480768e-04, 4.18152449e-05, 5.98102342e-05,\n", + " 8.04319134e-05, 1.35788669e-05, 3.69409063e-05, 2.70363416e-05,\n", + " 4.31931585e-05, 2.60745201e-05, 5.94786252e-05, 4.99271664e-05,\n", + " 2.43047725e-05, 1.30793895e-04, 4.14417882e-05, 2.70148976e-05,\n", + " 4.10587854e-05, 6.58849458e-05, 3.18542261e-05, 2.28214885e-05,\n", + " 4.62773096e-05, 2.48329743e-05, 2.42654005e-05, 2.44440125e-05,\n", + " 4.15933137e-05, 2.09003556e-05, 1.59764550e-05, 1.34925976e-05,\n", + " 5.11476246e-05, 3.04547921e-05, 5.38403292e-05, 2.52995142e-05,\n", + " 2.60678062e-05, 1.34934933e-04, 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4.69786464e-05, 7.30282045e-05,\n", + " 3.32598356e-05, 3.93198643e-05, 2.98816431e-05, 4.68274120e-05,\n", + " 3.85413005e-05, 2.63213096e-05, 7.29164458e-05, 1.51059212e-05,\n", + " 1.73022017e-05, 2.24817995e-05, 2.50870999e-05, 2.70464498e-05,\n", + " 6.94527189e-05, 7.03223559e-05, 1.13023976e-04, 1.81350424e-05,\n", + " 1.61756379e-05, 2.27133587e-05, 1.73909539e-05, 3.29188697e-05,\n", + " 3.83688603e-05, 4.63621691e-05, 4.20097022e-05, 2.44141211e-05,\n", + " 2.36812193e-05, 5.37081723e-05, 3.25651235e-05, 6.26961337e-05,\n", + " 4.40348194e-05, 6.08678674e-05, 1.51382401e-05, 4.85360542e-05,\n", + " 2.52648915e-05, 2.13416624e-05, 3.66176173e-05, 2.14315878e-05,\n", + " 2.53550206e-05, 2.49690220e-05, 1.72549426e-05, 1.23161544e-05,\n", + " 4.05697538e-05, 2.80514014e-05, 4.10169851e-05, 1.82738422e-05,\n", + " 2.12066843e-05, 1.92876123e-05, 1.40940101e-05, 2.85765000e-05,\n", + " 1.49180614e-05, 2.17154247e-05, 1.15241521e-04, 6.20267747e-05,\n", + " 3.51752824e-05, 1.84352139e-05, 2.34445524e-05, 6.70253139e-05,\n", + " 3.65042324e-05, 3.79433368e-05, 4.84678712e-05, 3.16102814e-05,\n", + " 4.14562965e-05, 3.48020985e-05, 5.51545527e-05, 1.20085324e-05,\n", + " 4.02397964e-05, 3.69577174e-05, 1.16221108e-05, 1.73307726e-05,\n", + " 2.36364995e-05, 3.68570509e-05, 2.28376211e-05, 1.44234800e-05,\n", + " 4.29613319e-05, 2.90063417e-05, 3.12782940e-05, 3.48059839e-05,\n", + " 3.07464470e-05, 4.45889127e-05, 2.77584841e-05, 2.82693636e-05,\n", + " 3.06526708e-05, 2.07262001e-05, 2.39080709e-05, 3.90869063e-05,\n", + " 1.63033437e-05, 3.13781420e-05, 1.09535986e-05, 2.71046247e-05,\n", + " 1.11349189e-04, 5.54282742e-05, 1.40334141e-05, 4.46840531e-05,\n", + " 3.27371636e-05, 2.36247342e-05, 4.71842868e-05, 2.51329329e-05,\n", + " 1.72788041e-05, 4.25959151e-05, 3.08176059e-05, 2.34919771e-05,\n", + " 5.41002009e-05, 3.36215126e-05, 1.79904982e-05, 2.53810031e-05,\n", + " 2.60098714e-05, 3.03672950e-05, 3.66435743e-05, 1.58947860e-05,\n", + " 1.63827226e-05, 1.00799487e-04, 7.84313306e-05, 3.44231594e-05,\n", + " 2.11487786e-05, 2.59042172e-05, 2.38122284e-05, 4.10612520e-05,\n", + " 7.02113830e-05, 5.71030141e-05, 3.37046913e-05, 5.70804186e-05,\n", + " 4.23736856e-05, 5.22688570e-05, 1.19306824e-05, 5.73656653e-05,\n", + " 7.22504701e-05, 3.07254595e-05, 1.82885069e-05, 3.95821407e-05,\n", + " 3.25709625e-05, 3.28924471e-05, 9.97101160e-05, 2.37495660e-05,\n", + " 4.08896231e-05, 5.16752771e-05, 2.26338507e-05, 3.62301726e-05,\n", + " 3.16428268e-05, 3.80293750e-05, 2.15715372e-05, 4.88352052e-05,\n", + " 5.38927270e-05, 1.52157181e-05, 3.10339638e-05, 7.30824031e-05,\n", + " 5.28455093e-05, 7.30705578e-05, 5.31096957e-05, 2.09516438e-05,\n", + " 2.92397508e-05, 1.90421888e-05, 2.24708656e-05, 5.41521295e-05,\n", + " 4.26290353e-05, 2.68298045e-05, 1.68493905e-04, 7.92833162e-05,\n", + " 2.62088943e-05, 3.02322060e-05, 4.04044986e-05, 3.22642190e-05,\n", + " 3.49984402e-05, 6.04081906e-05, 3.70786656e-05, 3.49358452e-05,\n", + " 5.57010717e-05, 6.00058593e-05, 2.44417952e-05, 5.71263263e-05,\n", + " 3.27215894e-05, 3.40137776e-05, 1.18062126e-05, 6.24499153e-05,\n", + " 6.80528974e-05, 5.41649897e-05, 2.79301566e-05, 6.44374522e-05,\n", + " 2.42756778e-05, 1.69049254e-05, 3.07581759e-05, 3.14246172e-05,\n", + " 4.06918080e-05, 1.29262517e-05, 3.18938037e-05, 2.57563679e-05,\n", + " 4.66018973e-05, 5.63653448e-05, 3.38337704e-05, 2.77759864e-05,\n", + " 2.10913349e-05, 2.39067704e-05, 5.60720728e-05, 3.24895882e-05,\n", + " 3.95797579e-05, 8.02239229e-05, 1.01568221e-05, 2.71663976e-05,\n", + " 4.02033183e-05, 3.46393863e-05, 1.89300026e-05, 6.62385719e-05,\n", + " 2.61362366e-05, 1.68800689e-05, 4.81760289e-05, 2.70115488e-05,\n", + " 6.33779127e-05, 9.80817131e-05, 1.00358353e-04, 1.55335729e-05,\n", + " 6.72744281e-05, 2.67282903e-05, 5.28051060e-05, 2.69585871e-05,\n", + " 4.51873238e-05, 1.50139886e-05, 4.31409971e-05, 2.19486756e-05,\n", + " 2.87472831e-05, 2.18212153e-05, 5.95341808e-05, 4.36046794e-05,\n", + " 2.39972505e-05, 2.03701456e-05, 2.67976375e-05, 1.95541270e-05,\n", + " 4.66474739e-05, 3.60696904e-05, 1.68149654e-05, 2.32476013e-05,\n", + " 2.53057151e-05, 3.79400080e-05, 4.50154475e-05, 4.20643009e-05,\n", + " 2.56692183e-05, 3.46892048e-05, 3.57301287e-05, 3.69169247e-05,\n", + " 3.51629387e-05, 3.76432145e-05, 2.19416434e-05, 2.46851632e-05,\n", + " 6.47292763e-05, 4.90587045e-05, 9.84386497e-05, 4.41858792e-05,\n", + " 1.67457674e-05, 7.27501538e-05, 1.29627551e-05, 4.09351560e-05,\n", + " 4.05014071e-05, 5.26341646e-05, 3.61480306e-05, 4.60584415e-05,\n", + " 6.60331425e-05, 2.30091900e-05, 4.62839744e-05, 2.25598706e-05,\n", + " 3.43657230e-05, 4.64396071e-05, 4.21469849e-05, 4.19451717e-05,\n", + " 1.95988596e-05, 2.81598495e-05, 2.10212929e-05, 2.90198714e-05,\n", + " 3.15838552e-05, 1.42506296e-05, 1.96369892e-05, 1.41922828e-05,\n", + " 2.51494548e-05, 5.29627650e-05, 2.34803319e-05, 2.45093706e-05,\n", + " 5.32276354e-05, 3.60567574e-05, 3.34151773e-05, 4.46611339e-05,\n", + " 1.84819692e-05, 3.09412899e-05, 4.80864292e-05, 4.70178165e-05,\n", + " 7.63339776e-05, 4.71588719e-05, 4.23062920e-05, 4.86267672e-05,\n", + " 2.40010959e-05, 1.92821499e-05, 1.88615959e-05, 5.05874268e-05,\n", + " 4.82907526e-05, 3.97411168e-05, 5.72696772e-05, 2.60267680e-05,\n", + " 5.70021366e-05, 1.14346831e-05, 5.19260393e-05, 6.01843822e-05]],\n", + " dtype=float32)" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.predict(img)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Use Gradio Instead" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], "source": [ "inp = gradio.inputs.ImageUpload(image_width=299, image_height=299, num_channels=3, aspect_ratio=False)\n", "out = gradio.outputs.Label(label_names='imagenet1000', max_label_length=8, num_top_classes=5)\n", @@ -40,7 +353,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": { "scrolled": false }, @@ -50,13 +363,33 @@ "output_type": "stream", "text": [ "NOTE: Gradio is in beta stage, please report all bugs to: a12d@stanford.edu\n", - "Model is running locally at: http://localhost:7860/interface.html\n", - "To create a public link, set `share=True` in the argument to `launch()`\n" + "Model is running locally at: http://localhost:7861/interface.html\n", + "Model available publicly for 8 hours at: http://018d2844.ngrok.io/interface.html\n" ] + }, + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "io.launch(inline=False, inbrowser=True, share=False, validate=False);" + "io.launch(inline=True, inbrowser=True, share=True, validate=False);" ] } ], diff --git a/web/getting_started.html b/web/getting_started.html index 9cf7ab23b5..b27665b539 100644 --- a/web/getting_started.html +++ b/web/getting_started.html @@ -14,6 +14,12 @@ Sharing
+

Installation

+

Gradio requires Python 3. You can download the latest version of gradio using pip, like this:

+ +
+
+

Or you may want to do

Getting Started

GradIO is a python library that allows you to place input and output interfaces over trained models to make it easy for you to "play around" @@ -22,14 +28,14 @@ page. Setting up GradIO is as easy as pip install gradio or pip3 install gradio for Python3.

Running a GradIO interface requires calling Interface(input : str, - output : str, model_type + class="func">Interface(inputs : str, + outputs : str, model_type : str, model : Any) function, which takes as input arguments:
- input – the string representing - the input interface to be used.
- output – the string representing + inputs – the string representing + the input interface to be used, or a subclass of gradio.AbstractInput (see below).
+ outputs – the string representing the output interface to be used.
model_type – the string representing type of model being passed in. Supported types include @@ -46,26 +52,27 @@ define and train the model as you would normally
io = gradio.Interface(input=“sketchpad”, output=“label”, inputs=“sketchpad”, outputs=“label”, model_type=“keras”, model=mdl)
io.launch()

+

Supported Interfaces

This is the list of currently supported interfaces in GradIO. All input interfaces can be paired with any output interface.

-

input=“text”

+

inputs=“text”

Use this interface to enter text as your input.

Input
-

input=“image_file”

+

inputs=“image_file”

Use this interface to upload images to your model.

Input
@@ -73,7 +80,7 @@ Drop Image Here
- or -
Click to Upload
-

input=“snapshot”

+

inputs=“snapshot”

Use this interface to take snapshots from the user's webcam.

Input
@@ -84,12 +91,12 @@
-

input=“sketchpad”

+

inputs=“sketchpad”

Use this interface to take simple monochrome cketches as input.

Input
-

input=“microphone”

+

inputs=“microphone”

Use this interface to audio input from the microphone.

Input
@@ -100,7 +107,7 @@
-

input=“audio_file”

+

inputs=“audio_file”

Use this interface to upload audio to your model.

Input
@@ -110,7 +117,7 @@
-

output=“classifier”

+

outputs=“classifier”

Use this interface for classification. Responds with confidence intervals.

@@ -123,14 +130,14 @@
angry
 
-

output=“text”

+

outputs=“text”

Use this interface to display the text of your output.

Output
-

output=“image”

+

outputs=“image”

Use this interface to display the text of your output.

Output