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fix unit test, remove h5 files

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This commit is contained in:
dawoodkhan82 2019-07-24 01:34:10 -07:00
parent 5f24b6cb54
commit afa1944570
3 changed files with 15 additions and 27 deletions
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2
gradio/preprocessing_utils.py
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@ -22,9 +22,7 @@ def encode_array_to_base64(image_array):
PIL_image = Image.fromarray(skimage.img_as_ubyte(image_array))
PIL_image.save(output_bytes, 'PNG')
bytes_data = output_bytes.getvalue()
base64_str = str(base64.b64encode(bytes_data), 'utf-8')
return "data:image/png;base64," + base64_str

38
gradio/test.py
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@ -2,30 +2,20 @@ import tensorflow as tf
import gradio
#CREATE INTERFACE USING 'GOOD' MNIST MODEL
(x_train, y_train),(x_test, y_test) = tf.keras.datasets.mnist.load_data()
model = tf.keras.models.load_model('MNIST_9344.h5')
input = gradio.inputs.Sketchpad(sample_inputs=x_train[:10])
iface = gradio.Interface(inputs=input, outputs="label", model=model, model_type='keras')
iface.launch(inline=False, share=False, inbrowser=True);
x_train, x_test = x_train / 255.0, x_test / 255.0
model = tf.keras.models.Sequential([
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(512, activation=tf.nn.relu),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Dense(10, activation=tf.nn.softmax)
])
#CREATE INTERFACE BY TRAINING MSNIST MODEL
# (x_train, y_train),(x_test, y_test) = tf.keras.datasets.mnist.load_data()
# x_train, x_test = x_train / 255.0, x_test / 255.0
#
# model = tf.keras.models.Sequential([
# tf.keras.layers.Flatten(),
# tf.keras.layers.Dense(512, activation=tf.nn.relu),
# tf.keras.layers.Dropout(0.2),
# tf.keras.layers.Dense(10, activation=tf.nn.softmax)
# ])
#
# model.compile(optimizer='adam',
# loss='sparse_categorical_crossentropy',
# metrics=['accuracy'])
# model.fit(x_train, y_train, epochs=1)
# inp = gradio.inputs.Sketchpad(sample_inputs=x_train[:10])
# iface = gradio.Interface(inputs=inp, outputs="label", model=model, model_type='keras')
# iface.launch(inline=False, share=False, inbrowser=True);
model.compile(optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
model.fit(x_train, y_train, epochs=1)
inp = gradio.inputs.Sketchpad(sample_inputs=x_train[:10])
iface = gradio.Interface(inputs=inp, outputs="label", model=model, model_type='keras')
iface.launch(inline=False, share=False, inbrowser=True);

2
test/test_networking.py
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@ -41,7 +41,7 @@ class TestSetSampleData(unittest.TestCase):
config_file = os.path.join(temp_dir, 'static/config.json')
with open(config_file) as json_file:
data = json.load(json_file)
self.assertFalse(test_array == data["sample_inputs"])
self.assertTrue(test_array == data["sample_inputs"])
# class TestCopyFiles(unittest.TestCase):
# def test_copy_files(self):