Francesco Gatti
88 lines
2.7 KiB
Python
88 lines
2.7 KiB
Python
import keras
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from keras.models import load_model
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import keras.backend.tensorflow_backend as KTF
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import numpy as np
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import argparse
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import tensorflow as tf
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import os
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import random
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import struct
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from keras.models import Sequential, Model
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import pickle
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def bin_write(f, data):
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data = data.flatten()
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fmt = 'f'*len(data)
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bin = struct.pack(fmt, *data)
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f.write(bin)
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# USE weight_exporter to generare wgs bins
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if __name__ == '__main__':
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print("DATA FORMAT: ", keras.backend.image_data_format())
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print("Load model: ", "ferrariSEP.hdf5")
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model = load_model("ferrariSEP.hdf5")
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model.summary()
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weights = model.get_weights()
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indata = pickle.load(open("input.pk", 'rb'))
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outdata = pickle.load(open("output.pk", 'rb'))
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x_angle = indata[0]
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x_gyro = indata[1]
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x_acc = indata[2]
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[yhat_delta_p, yhat_delta_q] = model.predict(indata, batch_size=1, verbose=1)
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predictdata = [yhat_delta_p, yhat_delta_q]
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error = outdata[0] - predictdata[0]
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print("error delta_p: ", error.sum())
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error = outdata[1] - predictdata[1]
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print("error delta_q: ", error.sum())
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#layer_name = 'dense_4'
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#intermediate_layer_model = Model(inputs=model.input,
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# outputs=model.get_layer(layer_name).output)
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#intermediate_output = intermediate_layer_model.predict([x_angle, x_gyro, x_acc])
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x_angle = np.array([x_angle])
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x_gyro = np.array([x_gyro])
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x_acc = np.array([x_acc])
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#intermediate_output = np.array([intermediate_output])
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x_angle = x_angle.transpose(1, 3, 0, 2)
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x_gyro = x_gyro.transpose(1, 3, 0, 2)
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x_acc = x_acc.transpose(1, 3, 0, 2)
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#intermediate_output = intermediate_output.transpose(0, 3, 1, 2)
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#print("Aggregate:")
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#print(intermediate_output.tolist())
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print("x0: ", np.shape(x_angle))
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#print("out: ",np.shape(intermediate_output))
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x_angle = np.array(x_angle.flatten(), dtype=np.float32)
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x_gyro = np.array(x_gyro.flatten(), dtype=np.float32)
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x_acc = np.array(x_acc.flatten(), dtype=np.float32)
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yhat_delta_p = np.array(yhat_delta_p.flatten(), dtype=np.float32)
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yhat_delta_q = np.array(yhat_delta_q.flatten(), dtype=np.float32)
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#intermediate_output = np.array(intermediate_output.flatten(), dtype=np.float32)
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f = open("layers/input0.bin", mode='wb')
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bin_write(f, x_angle)
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f = open("layers/input1.bin", mode='wb')
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bin_write(f, x_gyro)
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f = open("layers/input2.bin", mode='wb')
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bin_write(f, x_acc)
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f = open("layers/output0.bin", mode='wb')
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bin_write(f, yhat_delta_p)
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f = open("layers/output1.bin", mode='wb')
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bin_write(f, yhat_delta_q)
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#f = open("layers/output.bin", mode='wb')
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#bin_write(f, intermediate_output)
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