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I suspect this is my fault -- I'm having trouble getting good predictions from either the NYU or KITTI pre-trained models. I load the models the same way they are loaded in test.py:
Hi there,
I suspect this is my fault -- I'm having trouble getting good predictions from either the NYU or KITTI pre-trained models. I load the models the same way they are loaded in test.py:
model2 = keras.models.load_model("C:\\Users\\meyer\\Dropbox\\nga\\python\\github\\DenseDepth\\nyu amazon.h5", custom_objects = {"BilinearUpSampling2D": BilinearUpSampling2D}, compile = False)
and then make my predictions this way, where rgbA is a 480x640 RGB image represented as an array:
z = model2.predict(rgbA)
but my predictions are clearly wrong, as I show in the attached image.
So... does anyone have any idea how I can get accurate predictions out of the network?
Thanks!
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