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drive.py
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drive.py
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import socketio
import eventlet
import numpy as np
from flask import Flask
from keras.models import load_model
#from tensorflow.keras.models import load_model
import base64
from io import BytesIO
from PIL import Image
import cv2
from datetime import datetime
import os
import shutil
import argparse
sio = socketio.Server()
app = Flask(__name__) #'__main__'
speed_limit = 10
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)
def img_preprocess(img):
img = img[60:135,:,:]
img = cv2.cvtColor(img, cv2.COLOR_RGB2YUV)
img = cv2.GaussianBlur(img, (3, 3), 0)
img = cv2.resize(img, (200, 66))
img = img/255
return img
@sio.on('telemetry')
def telemetry(sid, data):
if data:
speed = float(data['speed'])
image = Image.open(BytesIO(base64.b64decode(data['image'])))
image_array = np.asarray(image)
image_array = img_preprocess(image_array)
image_array = np.array([image_array])
steering_angle = float(model.predict(image_array))
throttle = controller.update(float(speed))
print('{} | {} | {}'.format(steering_angle, throttle, speed))
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('Connected')
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()
print(args)
print("--------")
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)