Comments (2)
I am not sure if I understand your question. But since nobody replied I will try... :)
Save your result (for later reuse):
model_json = model.to_json()
with open("./model.json", "w") as json_file:
json_file.write(model_json)
model.save_weights("./weights.h5")
Load your result:
json_file = open("./model.json", "r")
loaded_model_json = json_file.read()
json_file.close()
model = model_from_json(loaded_model_json)
model.load_weights("./model.h5")
model.compile(loss='mean_squared_error', optimizer="RMSprop")
Predict images:
# images = arrary of images
predicts = model.predict(images)
print(predicts[0])
from keras-resnet.
@Tassfighter Thank you!!
from keras-resnet.
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from keras-resnet.