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Solves ValueError (using same graph) #6

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Solves ValueError (using same graph) #6

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10 changes: 8 additions & 2 deletions run_keras_server.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@
from keras.applications import ResNet50
from keras.preprocessing.image import img_to_array
from keras.applications import imagenet_utils
import tensorflow as tf
from PIL import Image
import numpy as np
import flask
Expand All @@ -25,6 +26,9 @@ def load_model():
# substitute in your own networks just as easily)
global model
model = ResNet50(weights="imagenet")
global graph
# save graph after loading ResNet50 weights
graph = tf.get_default_graph()

def prepare_image(image, target):
# if the image mode is not RGB, convert it
Expand Down Expand Up @@ -58,7 +62,9 @@ def predict():

# classify the input image and then initialize the list
# of predictions to return to the client
preds = model.predict(image)
# use the same graph saved after loading the model
with graph.as_default():
preds = model.predict(image)
results = imagenet_utils.decode_predictions(preds)
data["predictions"] = []

Expand All @@ -80,4 +86,4 @@ def predict():
print(("* Loading Keras model and Flask starting server..."
"please wait until server has fully started"))
load_model()
app.run()
app.run()