Keras Version Error - python-3.x

Question

I am working on Udacity Self-driving Car project which teaches a car to run autonomously(Behavior Clonning).
I am getting a weird Unicode error.
The Error Stated is as follows:
(dl) Vidits-MacBook-Pro-2:BehavioralClonning-master ViditShah$ python drive.py model.h5
Using TensorFlow backend.
You are using Keras version b'2.1.2' , but the model was built using b'1.2.1'
Traceback (most recent call last):
File "drive.py", line 122, in
model = load_model(args.model)
File "/Users/ViditShah/anaconda/envs/dl/lib/python3.6/site-packages/keras/models.py", line 240, in load_model
model = model_from_config(model_config, custom_objects=custom_objects)
File "/Users/ViditShah/anaconda/envs/dl/lib/python3.6/site-packages/keras/models.py", line 314, in model_from_config
return layer_module.deserialize(config, custom_objects=custom_objects)
File "/Users/ViditShah/anaconda/envs/dl/lib/python3.6/site-packages/keras/layers/init.py", line 55, in deserialize
printable_module_name='layer')
File "/Users/ViditShah/anaconda/envs/dl/lib/python3.6/site-packages/keras/utils/generic_utils.py", line 140, in deserialize_keras_object
list(custom_objects.items())))
File "/Users/ViditShah/anaconda/envs/dl/lib/python3.6/site-packages/keras/models.py", line 1323, in from_config
layer = layer_module.deserialize(conf, custom_objects=custom_objects)
File "/Users/ViditShah/anaconda/envs/dl/lib/python3.6/site-packages/keras/layers/init.py", line 55, in deserialize
printable_module_name='layer')
File "/Users/ViditShah/anaconda/envs/dl/lib/python3.6/site-packages/keras/utils/generic_utils.py", line 140, in deserialize_keras_object
list(custom_objects.items())))
File "/Users/ViditShah/anaconda/envs/dl/lib/python3.6/site-packages/keras/layers/core.py", line 699, in from_config
function = func_load(config['function'], globs=globs)
File "/Users/ViditShah/anaconda/envs/dl/lib/python3.6/site-packages/keras/utils/generic_utils.py", line 224, in func_load
raw_code = codecs.decode(code.encode('ascii'), 'base64')
UnicodeEncodeError: 'ascii' codec can't encode character '\xe3' in position 0: ordinal not in range(128)
I'm in my anaconda Environment dl.
The file drive.py is as follows.(This file was given during assignment and no edits has been suggested).
import argparse
import base64
from datetime import datetime
import os
import shutil
import numpy as np
import socketio
import eventlet
import eventlet.wsgi
from PIL import Image
from flask import Flask
from io import BytesIO
from keras.models import load_model
import h5py
from keras import __version__ as keras_version
sio = socketio.Server()
app = Flask(__name__)
model = None
prev_image_array = None
class SimplePIController:
def __init__(self, Kp, Ki):
self.Kp = Kp
self.Ki = Ki
self.set_point = 0.
self.error = 0.
self.integral = 0.
def set_desired(self, desired):
self.set_point = desired
def update(self, measurement):
# proportional error
self.error = self.set_point - measurement
# integral error
self.integral += self.error
return self.Kp * self.error + self.Ki * self.integral
controller = SimplePIController(0.1, 0.002)
set_speed = 9
controller.set_desired(set_speed)
#sio.on('telemetry')
def telemetry(sid, data):
if data:
# The current steering angle of the car
steering_angle = data["steering_angle"]
# The current throttle of the car
throttle = data["throttle"]
# The current speed of the car
speed = data["speed"]
# The current image from the center camera of the car
imgString = data["image"]
image = Image.open(BytesIO(base64.b64decode(imgString)))
image_array = np.asarray(image)
steering_angle = float(model.predict(image_array[None, :, :, :], batch_size=1))
throttle = controller.update(float(speed))
print(steering_angle, throttle)
send_control(steering_angle, throttle)
# save frame
if args.image_folder != '':
timestamp = datetime.utcnow().strftime('%Y_%m_%d_%H_%M_%S_%f')[:-3]
image_filename = os.path.join(args.image_folder, timestamp)
image.save('{}.jpg'.format(image_filename))
else:
# NOTE: DON'T EDIT THIS.
sio.emit('manual', data={}, skip_sid=True)
#sio.on('connect')
def connect(sid, environ):
print("connect ", sid)
send_control(0, 0)
def send_control(steering_angle, throttle):
sio.emit(
"steer",
data={
'steering_angle': steering_angle.__str__(),
'throttle': throttle.__str__()
},
skip_sid=True)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Remote Driving')
parser.add_argument(
'model',
type=str,
help='Path to model h5 file. Model should be on the same path.'
)
parser.add_argument(
'image_folder',
type=str,
nargs='?',
default='',
help='Path to image folder. This is where the images from the run will be saved.'
)
args = parser.parse_args()
# check that model Keras version is same as local Keras version
f = h5py.File(args.model, mode='r')
model_version = f.attrs.get('keras_version')
keras_version = str(keras_version).encode('utf8')
if model_version != keras_version:
print('You are using Keras version ', keras_version,
', but the model was built using ', model_version)
model = load_model(args.model)
if args.image_folder != '':
print("Creating image folder at {}".format(args.image_folder))
if not os.path.exists(args.image_folder):
os.makedirs(args.image_folder)
else:
shutil.rmtree(args.image_folder)
os.makedirs(args.image_folder)
print("RECORDING THIS RUN ...")
else:
print("NOT RECORDING THIS RUN ...")
# wrap Flask application with engineio's middleware
app = socketio.Middleware(sio, app)
# deploy as an eventlet WSGI server
eventlet.wsgi.server(eventlet.listen(('', 4567)), app)

Answer 1

You are getting this error because it seems that the model you are attempting to load was trained and saved in a previous version of Keras than the one you are using, as suggested by:
You are using Keras version b'2.1.2' , but the model was built using b'1.2.1' Traceback (most recent call last): File "drive.py", line 122, in model = load_model(args.model)
Seems that a solution to this may be to train your model with the same version you plan on using it, so you can load it smoothly. The other option would be to use version 1.2.1 to load that model and work with it.
This is probably due to differences between the way Keras saves models between versions, as some mayor changes should have taken place between v.1.2.1 and v.2.1.2.