diff --git a/Gym_new.py b/Gym_new.py
index 9015dfa2ed992ecc6a37e81f8e6ad8401e12e423..c67dc38c70db3d62e41fee106ab8f3a6b0a9a4ba 100644
--- a/Gym_new.py
+++ b/Gym_new.py
@@ -1,155 +1,84 @@
-import asyncio
-import random
-import json
-from socket import socket
-
-import websockets
-
-#from ActionSpace import ActionSpace
-import logging
-
-
-class Gym:
- host = None
- port = None
- player = None
- families = None
- types = None
- protocols = None
- logger = None
- # Create a TCP/IP socket
- sock = None
- last_recieved_JSON = None
- loop = None
- maxaction = 5
- #websocket = None
-
- def __init__(self, host ='localhost', port =9080, player ="player1"):
- self.host = host
- self.port = port
- self.player = player
- #self.loop = loop
- random.seed()
-
- # self.families = self.get_constants('AF_')
- # self.types = self.get_constants('SOCK_')
- # self.protocols = self.get_constants('IPPROTO_')
-
- self.logger = logging.getLogger('websockets')
- self.logger.setLevel(logging.INFO)
- self.logger.addHandler(logging.StreamHandler())
- print('New gym instance IP:', host, 'Port:', port, 'Playername:', player)
-
- # Call reset function of environment and returns observation
- # Send data to reset enviroment
- async def reset(self, delta):
- message = json.dumps([['reset'], delta], sort_keys=True, indent=4)
- data = []
- #print('send_action:',message)
- await self.send_websocket(message, data)
- test = json.loads(data[0])
- # print(test)
- # print(test[0])
- # print(test[1])
- reward = test[3]
- observation = test[0:3]
- done = test[4]
- info = 0
- # print(data)
- # print(data[0][0])
- return observation, reward, done, info
-
- # send action to env returns observation, reward, done, info
- # creates JSON object
- async def step(self, action, delta):
- global maxaction
- # Test ob die Action im richtigen Bereich ist!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
- test_message = []
- if action.find("accelerate")!=-1:#(action>=0) and (action < maxaction):
- test_message.append( "accelerate")
- #message = json.dumps({'action': action, 'delta': delta}, sort_keys=True, indent=4)
- #message = json.dumps([action], sort_keys=True, indent=4)
- #message2 = str(action)
-
-
- #hier data aufteilen!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
- #test = json.loads(data)
- #print(test)
- #x = data.split(',')
- #print(x)
- if action.find("left")!= -1:
- test_message.append( "steer_left")
- if action.find("right")!= -1:
- test_message.append("steer_right")
- if action.find("brake")!= -1:
- test_message.append("brake")
- if action.find("reverse")!= -1:
- test_message.append("reverse")
- if action.find("screen_on")!= -1:
- test_message.append("screen_on")
- if action.find("screen_off")!= -1:
- test_message.append("screen_off")
-
-
- else:
- pass
- #print("Action is not a valid Step")
-
- message = json.dumps([test_message,delta], sort_keys=True, indent=4)
- #message = json.dumps([action], sort_keys=True, indent=4)
- data = []
- #print('send_action:', message)
-
- await self.send_websocket(message, data)
- #print("awaited send_action")
- test = json.loads(data[0])
- # print(test)
- # print(test[0])
- # print(test[1])
- reward = test[3]
- observation = test[0:3]
- done = test[4]
- info = test[5]
- # print(data)
- # print(data[0][0])
- return observation, reward, done, info
-
-
- """ Returns a random action of action space
- """
- # Gibt jetzt eine Action zurück als Zahlenwert
- def get_sample_action(self):
- global maxaction
- action = random.randrange(0, maxaction)
- return action
-
- # socket_echo_client_easy.py
-
-
- # Wird jetzt nicht mehr benutzt !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
- # async def send_action(self, next_action):
- # message = '["' + next_action.name + '"]'
- # data = []
- # print('send_action:',message)
- # await self.send_websocket(message, data)
- # print("awaited send_action")
- # print(data)
- # return data
- async def connect_websocket(self):
- print("creating Websocket ")
- uri = "ws://localhost:9080"
- self.websocket = await websockets.connect(uri)
- # async with websockets.connect(uri) as websocket:
- # print("Websocket created ")
- # self.websocket = websocket
-
- async def send_websocket(self, message, data):
-
- await self.websocket.send(message)
- # print(f"> {name}")
- data.append(await self.websocket.recv())
- #print(f"< {data}")
- #print(data)
-
- async def close_websocket(self):
- await self.websocket.close()
\ No newline at end of file
+import asyncio
+import random
+import json
+
+import websockets
+import logging
+
+
+class Gym:
+ host = None
+ port = None
+ player = None
+ logger = None
+
+
+ def __init__(self, host ='localhost', port =9080, player ="player1"):
+ self.host = host
+ self.port = port
+ self.player = player
+ random.seed()
+
+ self.logger = logging.getLogger('websockets')
+ self.logger.setLevel(logging.INFO)
+ self.logger.addHandler(logging.StreamHandler())
+ print('New gym instance IP:', host, 'Port:', port, 'Playername:', player)
+
+ # Call reset function of environment and returns observation, reward, done, info
+ # Send data to reset enviroment
+ async def reset(self, delta):
+ message = json.dumps([['reset'], delta], sort_keys=True, indent=4)
+ data = []
+ await self.send_websocket(message, data)
+ all_information = json.loads(data[0])
+ reward = all_information[3]
+ observation = all_information[0:3]
+ done = all_information[4]
+ info = all_information[5]
+ return observation, reward, done, info
+
+ # send action to env returns observation, reward, done, info
+ # Obeservation is an array with the following information:
+ # [speed, steering-angle, [length of all sensors (starting straight and then clockwise around the car)]]
+ # creates JSON object
+ async def step(self, action, delta):
+ global maxaction
+ message = []
+ if action.find("accelerate")!=-1:
+ message.append( "accelerate")
+ if action.find("left")!= -1:
+ message.append( "steer_left")
+ if action.find("right")!= -1:
+ message.append("steer_right")
+ if action.find("brake")!= -1:
+ message.append("brake")
+ if action.find("reverse")!= -1:
+ message.append("reverse")
+ if action.find("screen_on")!= -1:
+ message.append("screen_on")
+ if action.find("screen_off")!= -1:
+ message.append("screen_off")
+
+ message = json.dumps([message,delta], sort_keys=True, indent=4)
+ data = []
+
+ await self.send_websocket(message, data)
+ all_information = json.loads(data[0])
+ reward = all_information[3]
+ observation = all_information[0:3]
+ done = all_information[4]
+ info = all_information[5]
+ return observation, reward, done, info
+
+ async def connect_websocket(self):
+ print("creating Websocket ")
+ uri = "ws://localhost:9080"
+ self.websocket = await websockets.connect(uri)
+
+
+ async def send_websocket(self, message, data):
+ await self.websocket.send(message)
+ data.append(await self.websocket.recv())
+
+ async def close_websocket(self):
+ await self.websocket.close()
diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..35c19910e18cedd18f10046236edb51e0388b575
--- /dev/null
+++ b/README.md
@@ -0,0 +1,45 @@
+# Summary of the Project
+Open_Ai_Gym_Autobahn_Auffahren is a project that makes it possible for a python-agent to play a godot game.\
+This project shows an example for that with a car trying to enter a highway.\
+It has a complete Godot-Enviroment with an example bot in python.\
+
+# Installation Tutorial
+
+## Godot
+First you need to install Godot on your Computer.\
+You can find the Link [here](https://godotengine.org/download).
+
+## Python
+[Here](https://www.python.org/downloads/) is one way to install Python on your PC.\
+You also need the following packages: [websockets](https://pypi.org/project/websocket-client/), [Pillow](https://pypi.org/project/Pillow/).\
+Please notice that the websockets package is not supportet in Spyder Enviroment.
+
+## Repository
+Download all the files to convinient folder.
+
+
+# Setup
+There are a few variables you can change in Godot
+## World
+1. human_player: If set to true, you can drive with wasd and brake with space. Otherwise it waits for a client to connect.
+2. learn_with_images: Also returns a 60x80 screenshot of the game in every step, if set to true.
+3. show_game: If set to false, it won't render the game, but still sends all the information to the client.
+
+## Car
+1. brake_str: Can be used to reduce the brake-strength of the car.
+2. NUMBER_OF_SENSORS: Determines the number of sensors around the car (Always start at the front and goes clockwise).
+3. max_range_sensor: Range of the sensors in pixels (~31 m)
+4. range_per_step_sensor: Accuracy of the sensors in pixels (~0.31 m)
+
+# Running the Project
+
+## Godot
+1. Start Godot
+2. Click Scan to a a new project and select the folder with the downloaded files
+3. Now doubleclick the project
+4. Run the Project by pressing F5
+
+## Python
+1. After starting the Project in Godot you can run your own Python programm or the example progamm (main_test) from the files
+___
+Created by Midras Lappe and Theo Brockmann
diff --git a/main_test.py b/main_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..0f6a6f4dd244abd1227e4d1ffbf90a823182a0b7
--- /dev/null
+++ b/main_test.py
@@ -0,0 +1,46 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Jan 12 17:17:49 2021
+
+@author: theob
+"""
+
+import asyncio
+import Gym_new
+import time
+import nest_asyncio
+import show_image as si
+
+
+
+async def main():
+ image_mode = 'L'
+
+
+ env = Gym_new.Gym()
+ await env.connect_websocket()
+
+ # Resets the enviroment
+ observation, reward, done, info = await env.reset("",0.01)
+ print(observation)
+ print(reward)
+ print(done)
+
+ # Makes 1 step only driving straight
+ observation, reward, done, info = await env.step("accelerate,screen_on", 0.17)
+ print(observation)
+ # Obeservation is an array with the following information:
+ # [speed, steering-angle, [length of all sensors (starting straight and then clockwise around the car)]]
+ print(reward)
+ print(done)
+
+ try:
+ # Test show Image
+ si.show_image(image_mode,info['thumbnail']['width'],info['thumbnail']['height'],info['thumbnail']['image'])
+ except Exception as e:
+ print("failed showing image: " + str(e))
+
+if __name__ == "__main__":
+ nest_asyncio.apply()
+ loop = asyncio.get_event_loop()
+ loop.run_until_complete(main())