Merge branch 'master' of https://gitlab.cvh-server.de/mlappe/open_ai_gym_autobahn_auffahren

Gym_new.py

 import asyncio
 import random
 import json
-from socket import socket
 
 import websockets
-
-#from ActionSpace import ActionSpace
 import logging
 
 
@@ -13,143 +10,75 @@ 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
+    # 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 = []
-        #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])
+        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
-        # 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)
+        message = []
+        if action.find("accelerate")!=-1:
+            message.append( "accelerate")
         if action.find("left")!= -1:
-            test_message.append( "steer_left")
+            message.append( "steer_left")
         if action.find("right")!= -1:
-            test_message.append("steer_right")
+            message.append("steer_right")
         if action.find("brake")!= -1:
-            test_message.append("brake")
+            message.append("brake")
         if action.find("reverse")!= -1:
-            test_message.append("reverse")
+            message.append("reverse")
         if action.find("screen_on")!= -1:
-            test_message.append("screen_on")
+            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.append("screen_off")
         
-        message = json.dumps([test_message,delta], sort_keys=True, indent=4)
-        #message = json.dumps([action], sort_keys=True, indent=4)
+        message = json.dumps([message,delta], 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])
+        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
 
-        
-    """ 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):
     
+    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()

README.md

+# 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

main_test.py

+# -*- 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())