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fix examples

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This commit is contained in:
Ali Abid 2020-07-02 08:30:06 -07:00
commit 3f359358d6
24 changed files with 99 additions and 48 deletions
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15
README.md
View File

@ -40,20 +40,15 @@ import gradio
import tensorflow as tf
from imagenetlabels import idx_to_labels
graph = tf.get_default_graph()
sess = tf.keras.backend.get_session()
def classify_image(inp):
with graph.as_default():
with sess.as_default():
inp = inp.reshape((1, 224, 224, 3))
prediction = mobile_net.predict(inp).flatten()
return {idx_to_labels[i].split(',')[0]: float(prediction[i]) for i in range(1000)}
inp = inp.reshape((1, 224, 224, 3))
prediction = mobile_net.predict(inp).flatten()
return {idx_to_labels[i].split(',')[0]: float(prediction[i]) for i in range(1000)}
imagein = gradio.inputs.ImageIn(shape=(224, 224, 3))
imagein = gradio.inputs.Image(shape=(224, 224, 3))
label = gradio.outputs.Label(num_top_classes=3)
gr.Interface(classify_image, imagein, label).launch();
gr.Interface(classify_image, imagein, label, capture_session=True).launch();
```
![alt text](https://i.ibb.co/nM97z2B/image-interface.png)

4
build/lib/gradio/inputs.py
View File

@ -209,15 +209,17 @@ class CheckboxGroup(AbstractInput):
class Slider(AbstractInput):
def __init__(self, minimum=0, maximum=100, label=None):
def __init__(self, minimum=0, maximum=100, default=None, label=None):
self.minimum = minimum
self.maximum = maximum
self.default = minimum if default is None else default
super().__init__(label)
def get_template_context(self):
return {
"minimum": self.minimum,
"maximum": self.maximum,
"default": self.default,
**super().get_template_context()
}

24
build/lib/gradio/interface.py
View File

@ -40,7 +40,7 @@ class Interface:
"""
def get_input_instance(iface):
if isinstance(iface, str):
return gradio.inputs.shortcuts[iface]
return gradio.inputs.shortcuts[iface.lower()]
elif isinstance(iface, gradio.inputs.AbstractInput):
return iface
else:
@ -49,7 +49,7 @@ class Interface:
def get_output_instance(iface):
if isinstance(iface, str):
return gradio.outputs.shortcuts[iface]
return gradio.outputs.shortcuts[iface.lower()]
elif isinstance(iface, gradio.outputs.AbstractOutput):
return iface
else:
@ -115,8 +115,10 @@ class Interface:
raw_input[i]) for i, input_interface in
enumerate(self.input_interfaces)]
predictions = []
durations = []
for predict_fn in self.predict:
if self.capture_session:
start = time.time()
if self.capture_session and not(self.session is None):
graph, sess = self.session
with graph.as_default():
with sess.as_default():
@ -135,14 +137,16 @@ class Interface:
"error.")
else:
raise exception
duration = time.time() - start
if len(self.output_interfaces) / \
len(self.predict) == 1:
prediction = [prediction]
durations.append(duration)
predictions.extend(prediction)
processed_output = [output_interface.postprocess(
predictions[i]) for i, output_interface in enumerate(self.output_interfaces)]
return processed_output
return processed_output, durations
def validate(self):
if self.validate_flag:
@ -208,9 +212,12 @@ class Interface:
# self.validate()
if self.capture_session:
import tensorflow as tf
self.session = tf.get_default_graph(), \
tf.keras.backend.get_session()
try:
import tensorflow as tf
self.session = tf.get_default_graph(), \
tf.keras.backend.get_session()
except (ImportError, AttributeError): # If they are using TF >= 2.0 or don't have TF, just ignore this.
pass
# If an existing interface is running with this instance, close it.
if self.status == "RUNNING":
@ -257,7 +264,7 @@ class Interface:
if share:
try:
share_url = networking.setup_tunnel(server_port)
print(share_url)
print("External URL:", share_url)
except RuntimeError:
share_url = None
if self.verbose:
@ -299,6 +306,7 @@ class Interface:
is_colab
): # Embed the remote interface page if on google colab;
# otherwise, embed the local page.
time.sleep(1)
display(IFrame(share_url, width=1000, height=500))
else:
display(IFrame(path_to_local_server, width=1000, height=500))

4
build/lib/gradio/networking.py
View File

@ -139,7 +139,9 @@ def serve_files_in_background(interface, port, directory_to_serve=None, server_n
int(self.headers["Content-Length"]))
msg = json.loads(data_string)
raw_input = msg["data"]
output = {"data": interface.process(raw_input)}
prediction, durations = interface.process(raw_input)
output = {"data": prediction, "durations": durations}
if interface.saliency is not None:
saliency = interface.saliency(raw_input, prediction)
output['saliency'] = saliency.tolist()

8
build/lib/gradio/static/css/style.css
View File

@ -13,6 +13,14 @@ button, input[type="submit"], input[type="reset"], input[type="text"], input[typ
-webkit-appearance: none;
border-radius: 0;
}
.loading_time {
font-size: large;
color: #EEA45D;
text-align: right;
padding-top: 5px;
}
nav {
text-align: center;
padding: 16px 0 4px;

6
build/lib/gradio/static/js/all_io.js
View File

@ -32,16 +32,18 @@ var io_master_template = {
this.target.find(".loading_failed").show();
})
},
output: function(data) {
output: function(data) {
this.last_output = data["data"];
for (let i = 0; i < this.output_interfaces.length; i++) {
this.output_interfaces[i].output(data["data"][i]);
this.output_interfaces[i].target.parent().find(`.loading_time[interface="${i}"]`).text("Latency: " + ((data["durations"][i])).toFixed(2) + "s");
}
if (this.config.live) {
this.gather();
} else {
this.target.find(".loading").addClass("invisible");
this.target.find(".output_interface").removeClass("invisible");
this.target.find(".output_interface").removeClass("invisible");
this.target.find(".output_interfaces .panel_header").removeClass("invisible");
}
},

4
build/lib/gradio/static/js/gradio.js
View File

@ -91,6 +91,9 @@ function gradio(config, fn, target) {
${output_interface.html}
</div>
`);
target.find(".output_interfaces").append(`
<div class="loading_time" interface="${i}"> </div>
`);
output_interface.target = target.find(`.output_interface[interface_id=${_id}]`);
set_interface_id(output_interface, _id);
output_interface.io_master = io_master;
@ -110,6 +113,7 @@ function gradio(config, fn, target) {
target.find(".flag").removeClass("flagged");
target.find(".flag_message").empty();
target.find(".loading").addClass("invisible");
target.find(".loading_time").text("");
target.find(".output_interface").removeClass("invisible");
io_master.last_input = null;
io_master.last_output = null;

4
build/lib/gradio/static/js/interfaces/input/slider.js
View File

@ -12,6 +12,7 @@ const slider = {
this.target.css("height", "auto");
this.target.find(".min").text(opts.minimum);
this.target.find(".max").text(opts.maximum);
this.target.find(".value").text(opts.default);
let difference = opts.maximum - opts.minimum;
if (difference <= 1) {
step = 0.01;
@ -23,6 +24,7 @@ const slider = {
this.target.find(".slider")
.attr("min", opts.minimum)
.attr("max", opts.maximum)
.attr("value", opts.default)
.attr("step", step)
.on("change", function() {
io.target.find(".value").text($(this).val());
@ -33,7 +35,7 @@ const slider = {
this.io_master.input(this.id, parseFloat(value));
},
clear: function() {
this.target.find("input").val(this.minimum);
this.target.find("input").val(this.default);
},
load_example: function(data) {
this.target.find("input").val(data);

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dist/gradio-0.9.4-py3-none-any.whl → dist/gradio-0.9.5-py3-none-any.whl vendored
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2
gradio.egg-info/PKG-INFO
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@ -1,6 +1,6 @@
Metadata-Version: 1.0
Name: gradio
Version: 0.9.4
Version: 0.9.5
Summary: Python library for easily interacting with trained machine learning models
Home-page: https://github.com/abidlabs/gradio
Author: Abubakar Abid

4
gradio/inputs.py
View File

@ -209,15 +209,17 @@ class CheckboxGroup(AbstractInput):
class Slider(AbstractInput):
def __init__(self, minimum=0, maximum=100, label=None):
def __init__(self, minimum=0, maximum=100, default=None, label=None):
self.minimum = minimum
self.maximum = maximum
self.default = minimum if default is None else default
super().__init__(label)
def get_template_context(self):
return {
"minimum": self.minimum,
"maximum": self.maximum,
"default": self.default,
**super().get_template_context()
}

24
gradio/interface.py
View File

@ -40,7 +40,7 @@ class Interface:
"""
def get_input_instance(iface):
if isinstance(iface, str):
return gradio.inputs.shortcuts[iface]
return gradio.inputs.shortcuts[iface.lower()]
elif isinstance(iface, gradio.inputs.AbstractInput):
return iface
else:
@ -49,7 +49,7 @@ class Interface:
def get_output_instance(iface):
if isinstance(iface, str):
return gradio.outputs.shortcuts[iface]
return gradio.outputs.shortcuts[iface.lower()]
elif isinstance(iface, gradio.outputs.AbstractOutput):
return iface
else:
@ -115,8 +115,10 @@ class Interface:
raw_input[i]) for i, input_interface in
enumerate(self.input_interfaces)]
predictions = []
durations = []
for predict_fn in self.predict:
if self.capture_session:
start = time.time()
if self.capture_session and not(self.session is None):
graph, sess = self.session
with graph.as_default():
with sess.as_default():
@ -135,14 +137,16 @@ class Interface:
"error.")
else:
raise exception
duration = time.time() - start
if len(self.output_interfaces) / \
len(self.predict) == 1:
prediction = [prediction]
durations.append(duration)
predictions.extend(prediction)
processed_output = [output_interface.postprocess(
predictions[i]) for i, output_interface in enumerate(self.output_interfaces)]
return processed_output
return processed_output, durations
def validate(self):
if self.validate_flag:
@ -208,9 +212,12 @@ class Interface:
# self.validate()
if self.capture_session:
import tensorflow as tf
self.session = tf.get_default_graph(), \
tf.keras.backend.get_session()
try:
import tensorflow as tf
self.session = tf.get_default_graph(), \
tf.keras.backend.get_session()
except (ImportError, AttributeError): # If they are using TF >= 2.0 or don't have TF, just ignore this.
pass
# If an existing interface is running with this instance, close it.
if self.status == "RUNNING":
@ -257,7 +264,7 @@ class Interface:
if share:
try:
share_url = networking.setup_tunnel(server_port)
print(share_url)
print("External URL:", share_url)
except RuntimeError:
share_url = None
if self.verbose:
@ -299,6 +306,7 @@ class Interface:
is_colab
): # Embed the remote interface page if on google colab;
# otherwise, embed the local page.
time.sleep(1)
display(IFrame(share_url, width=1000, height=500))
else:
display(IFrame(path_to_local_server, width=1000, height=500))

4
gradio/networking.py
View File

@ -139,7 +139,9 @@ def serve_files_in_background(interface, port, directory_to_serve=None, server_n
int(self.headers["Content-Length"]))
msg = json.loads(data_string)
raw_input = msg["data"]
output = {"data": interface.process(raw_input)}
prediction, durations = interface.process(raw_input)
output = {"data": prediction, "durations": durations}
if interface.saliency is not None:
saliency = interface.saliency(raw_input, prediction)
output['saliency'] = saliency.tolist()

8
gradio/static/css/style.css
View File

@ -13,6 +13,14 @@ button, input[type="submit"], input[type="reset"], input[type="text"], input[typ
-webkit-appearance: none;
border-radius: 0;
}
.loading_time {
font-size: large;
color: #EEA45D;
text-align: right;
padding-top: 5px;
}
nav {
text-align: center;
padding: 16px 0 4px;

6
gradio/static/js/all_io.js
View File

@ -32,16 +32,18 @@ var io_master_template = {
this.target.find(".loading_failed").show();
})
},
output: function(data) {
output: function(data) {
this.last_output = data["data"];
for (let i = 0; i < this.output_interfaces.length; i++) {
this.output_interfaces[i].output(data["data"][i]);
this.output_interfaces[i].target.parent().find(`.loading_time[interface="${i}"]`).text("Latency: " + ((data["durations"][i])).toFixed(2) + "s");
}
if (this.config.live) {
this.gather();
} else {
this.target.find(".loading").addClass("invisible");
this.target.find(".output_interface").removeClass("invisible");
this.target.find(".output_interface").removeClass("invisible");
this.target.find(".output_interfaces .panel_header").removeClass("invisible");
}
},

4
gradio/static/js/gradio.js
View File

@ -91,6 +91,9 @@ function gradio(config, fn, target) {
${output_interface.html}
</div>
`);
target.find(".output_interfaces").append(`
<div class="loading_time" interface="${i}"> </div>
`);
output_interface.target = target.find(`.output_interface[interface_id=${_id}]`);
set_interface_id(output_interface, _id);
output_interface.io_master = io_master;
@ -110,6 +113,7 @@ function gradio(config, fn, target) {
target.find(".flag").removeClass("flagged");
target.find(".flag_message").empty();
target.find(".loading").addClass("invisible");
target.find(".loading_time").text("");
target.find(".output_interface").removeClass("invisible");
io_master.last_input = null;
io_master.last_output = null;

4
gradio/static/js/interfaces/input/slider.js
View File

@ -12,6 +12,7 @@ const slider = {
this.target.css("height", "auto");
this.target.find(".min").text(opts.minimum);
this.target.find(".max").text(opts.maximum);
this.target.find(".value").text(opts.default);
let difference = opts.maximum - opts.minimum;
if (difference <= 1) {
step = 0.01;
@ -23,6 +24,7 @@ const slider = {
this.target.find(".slider")
.attr("min", opts.minimum)
.attr("max", opts.maximum)
.attr("value", opts.default)
.attr("step", step)
.on("change", function() {
io.target.find(".value").text($(this).val());
@ -33,7 +35,7 @@ const slider = {
this.io_master.input(this.id, parseFloat(value));
},
clear: function() {
this.target.find("input").val(this.minimum);
this.target.find("input").val(this.default);
},
load_example: function(data) {
this.target.find("input").val(data);

2
setup.py
View File

@ -5,7 +5,7 @@ except ImportError:
setup(
name='gradio',
version='0.9.4',
version='0.9.5',
include_package_data=True,
description='Python library for easily interacting with trained machine learning models',
author='Abubakar Abid',

9
test/test_inputs.py
View File

@ -11,7 +11,7 @@ PACKAGE_NAME = 'gradio'
class TestSketchpad(unittest.TestCase):
def test_path_exists(self):
inp = inputs.Sketchpad()
path = inputs.BASE_INPUT_INTERFACE_JS_PATH.format(inp.__class__.__name__)
path = inputs.BASE_INPUT_INTERFACE_JS_PATH.format(inp.__class__.__name__.lower())
self.assertTrue(os.path.exists(os.path.join(PACKAGE_NAME, path)))
def test_preprocessing(self):
@ -23,7 +23,7 @@ class TestSketchpad(unittest.TestCase):
class TestWebcam(unittest.TestCase):
def test_path_exists(self):
inp = inputs.Webcam()
path = inputs.BASE_INPUT_INTERFACE_JS_PATH.format(inp.__class__.__name__)
path = inputs.BASE_INPUT_INTERFACE_JS_PATH.format(inp.__class__.__name__.lower())
self.assertTrue(os.path.exists(os.path.join(PACKAGE_NAME, path)))
def test_preprocessing(self):
@ -35,7 +35,8 @@ class TestWebcam(unittest.TestCase):
class TestTextbox(unittest.TestCase):
def test_path_exists(self):
inp = inputs.Textbox()
path = inputs.BASE_INPUT_INTERFACE_JS_PATH.format(inp.__class__.__name__)
path = inputs.BASE_INPUT_INTERFACE_JS_PATH.format(
inp.__class__.__name__.lower())
self.assertTrue(os.path.exists(os.path.join(PACKAGE_NAME, path)))
def test_preprocessing(self):
@ -47,7 +48,7 @@ class TestTextbox(unittest.TestCase):
class TestImageUpload(unittest.TestCase):
def test_path_exists(self):
inp = inputs.Image()
path = inputs.BASE_INPUT_INTERFACE_JS_PATH.format(inp.__class__.__name__)
path = inputs.BASE_INPUT_INTERFACE_JS_PATH.format(inp.__class__.__name__.lower())
self.assertTrue(os.path.exists(os.path.join(PACKAGE_NAME, path)))
def test_preprocessing(self):

5
test/test_networking.py
View File

@ -6,7 +6,6 @@ import socket
import tempfile
import os
import json
LOCALHOST_NAME = 'localhost'
class TestGetAvailablePort(unittest.TestCase):
@ -17,7 +16,7 @@ class TestGetAvailablePort(unittest.TestCase):
for port in range(initial, final):
try:
s = socket.socket() # create a socket object
s.bind((LOCALHOST_NAME, port)) # Bind to the port
s.bind((networking.LOCALHOST_NAME, port)) # Bind to the port
s.close()
port_found = True
break
@ -25,7 +24,7 @@ class TestGetAvailablePort(unittest.TestCase):
pass
if port_found:
s = socket.socket() # create a socket object
s.bind((LOCALHOST_NAME, port)) # Bind to the port
s.bind((networking.LOCALHOST_NAME, port)) # Bind to the port
new_port = networking.get_first_available_port(initial, final)
s.close()
self.assertFalse(port==new_port)

6
test/test_outputs.py
View File

@ -11,7 +11,7 @@ BASE64_IMG = "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEASABIAAD/2wBDAAYEBQYFBAY
class TestLabel(unittest.TestCase):
def test_path_exists(self):
out = outputs.Label()
path = outputs.BASE_OUTPUT_INTERFACE_JS_PATH.format(out.__class__.__name__)
path = outputs.BASE_OUTPUT_INTERFACE_JS_PATH.format(out.__class__.__name__.lower())
self.assertTrue(os.path.exists(os.path.join(PACKAGE_NAME, path)))
# def test_postprocessing_string(self):
@ -50,7 +50,7 @@ class TestLabel(unittest.TestCase):
class TestTextbox(unittest.TestCase):
def test_path_exists(self):
out = outputs.Textbox()
path = outputs.BASE_OUTPUT_INTERFACE_JS_PATH.format(out.__class__.__name__)
path = outputs.BASE_OUTPUT_INTERFACE_JS_PATH.format(out.__class__.__name__.lower())
self.assertTrue(os.path.exists(os.path.join(PACKAGE_NAME, path)))
def test_postprocessing(self):
@ -63,7 +63,7 @@ class TestTextbox(unittest.TestCase):
class TestImage(unittest.TestCase):
def test_path_exists(self):
out = outputs.Image()
path = outputs.BASE_OUTPUT_INTERFACE_JS_PATH.format(out.__class__.__qualname__)
path = outputs.BASE_OUTPUT_INTERFACE_JS_PATH.format(out.__class__.__qualname__.lower())
self.assertTrue(os.path.exists(os.path.join(PACKAGE_NAME, path)))
def test_postprocessing(self):