drive.py

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
import cv2
import json

from keras.models import load_model
from keras.models import model_from_json
import tensorflow as tf

sio = socketio.Server()
app = Flask(__name__)
model = None
prev_image_array = None

config = tf.ConfigProto()
config.gpu_options.allow_growth = True
sess = tf.Session(config=config)



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)
        # Crop and resize image to preserve same shape as training
        image_array = image_array[40:-20,:]
        image_array = cv2.resize(image_array, (200, 66), interpolation=cv2.INTER_AREA)
        steering_angle = float(model.predict(image_array[None, :, :, :], batch_size=1))
        # Increase throttle when speed falls below 20mph (esp useful for track 2)
        throttle = 0.12 if float(speed) > 20 else 0.5
        
        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()

    with open(args.model, 'r') as jfile:
        model = model_from_json(json.loads(jfile.read()))

    model.compile("adam", "mse")
    weights_file = args.model.replace('json', 'h5')
    model.load_weights(weights_file)

    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)