diff --git a/all_positions.pickle b/all_positions.pickle
new file mode 100644
index 0000000..6f8fee3
Binary files /dev/null and b/all_positions.pickle differ
diff --git a/manual_control.py b/manual_control.py
new file mode 100644
index 0000000..384accd
--- /dev/null
+++ b/manual_control.py
@@ -0,0 +1,156 @@
+import sys
+import operator
+from os import listdir, system
+from random import randrange
+from ale_py import ALEInterface, SDL_SUPPORT, Action
+from colors import *
+from PIL import Image
+from matplotlib import pyplot as plt
+import cv2
+import pickle
+import queue
+from dataclasses import dataclass, field
+
+from enum import Enum
+
+from copy import deepcopy
+
+import numpy as np
+
+import readchar
+
+from sample_factory.algo.utils.tensor_dict import TensorDict
+from query_sample_factory_checkpoint import SampleFactoryNNQueryWrapper
+
+import time
+
+tempest_binary = "/home/spranger/projects/tempest-devel/ranking_release/bin/storm"
+rom_file = "/home/spranger/research/Skiing/env/lib/python3.8/site-packages/AutoROM/roms/skiing.bin"
+
+
+def input_to_action(char):
+ if char == "0":
+ return Action.NOOP
+ if char == "1":
+ return Action.RIGHT
+ if char == "2":
+ return Action.LEFT
+ if char == "3":
+ return "reset"
+ if char == "4":
+ return "set_x"
+ if char == "5":
+ return "set_vel"
+ if char in ["w", "a", "s", "d"]:
+ return char
+
+
+ale = ALEInterface()
+
+
+if SDL_SUPPORT:
+ ale.setBool("sound", True)
+ ale.setBool("display_screen", True)
+
+# Load the ROM file
+ale.loadROM(rom_file)
+
+with open('all_positions_v2.pickle', 'rb') as handle:
+ ramDICT = pickle.load(handle)
+y_ram_setting = 60
+x = 70
+
+oldram = deepcopy(ale.getRAM())
+velocity_set = False
+for episode in range(10):
+ total_reward = 0
+ j = 0
+ while not ale.game_over():
+ if not velocity_set: ale.setRAM(14,0)
+ j += 1
+ a = input_to_action(repr(readchar.readchar())[1])
+ #a = Action.NOOP
+
+ if a == "w":
+ y_ram_setting -= 1
+ if y_ram_setting <= 61:
+ y_ram_setting = 61
+ for i, r in enumerate(ramDICT[y_ram_setting]):
+ ale.setRAM(i,r)
+ ale.setRAM(25,x)
+ ale.act(Action.NOOP)
+ elif a == "s":
+ y_ram_setting += 1
+ if y_ram_setting >= 1950:
+ y_ram_setting = 1945
+ for i, r in enumerate(ramDICT[y_ram_setting]):
+ ale.setRAM(i,r)
+ ale.setRAM(25,x)
+ ale.act(Action.NOOP)
+ elif a == "a":
+ x -= 1
+ if x <= 0:
+ x = 0
+ ale.setRAM(25,x)
+ ale.act(Action.NOOP)
+ elif a == "d":
+ x += 1
+ if x >= 144:
+ x = 144
+ ale.setRAM(25,x)
+ ale.act(Action.NOOP)
+
+
+ elif a == "reset":
+ ram_pos = input("Ram Position:")
+ for i, r in enumerate(ramDICT[int(ram_pos)]):
+ ale.setRAM(i,r)
+ ale.act(Action.NOOP)
+ # Apply an action and get the resulting reward
+ elif a == "set_x":
+ x = int(input("X:"))
+ ale.setRAM(25, x)
+ ale.act(Action.NOOP)
+ elif a == "set_vel":
+ vel = input("Velocity:")
+ ale.setRAM(14, int(vel))
+ ale.act(Action.NOOP)
+ velocity_set = True
+ else:
+ reward = ale.act(a)
+ ram = ale.getRAM()
+ #if j % 2 == 0:
+ # y_pixel = int(j*1/2) + 55
+ # ramDICT[y_pixel] = ram
+ # print(f"saving to {y_pixel:04}")
+ # if y_pixel == 126 or y_pixel == 235:
+ # input("")
+
+ int_old_ram = list(map(int, oldram))
+ int_ram = list(map(int, ram))
+ difference = list()
+ for o, r in zip(int_old_ram, int_ram):
+ difference.append(r-o)
+
+ oldram = deepcopy(ram)
+ #print(f"player_x: {ram[25]},\tclock_m: {ram[104]},\tclock_s: {ram[105]},\tclock_ms: {ram[106]},\tscore: {ram[107]}")
+ print(f"player_x: {ram[25]},\tplayer_y: {y_ram_setting}")
+ #print(f"y_0: {ram[86]}, y_1: {ram[87]}, y_2: {ram[88]}, y_3: {ram[89]}, y_4: {ram[90]}, y_5: {ram[91]}, y_6: {ram[92]}, y_7: {ram[93]}, y_8: {ram[94]}")
+
+ #for i, r in enumerate(ram):
+ # print('{:03}:{:02x} '.format(i,r), end="")
+ # if i % 16 == 15: print("")
+ #print("")
+ #for i, r in enumerate(difference):
+ # string = '{:02}:{:03} '.format(i%100,r)
+ # if r != 0:
+ # print(color(string, fg='red'), end="")
+ # else:
+ # print(string, end="")
+ # if i % 16 == 15: print("")
+ print("Episode %d ended with score: %d" % (episode, total_reward))
+ input("")
+
+ with open('all_positions_v2.pickle', 'wb') as handle:
+ pickle.dump(ramDICT, handle, protocol=pickle.HIGHEST_PROTOCOL)
+ ale.reset_game()
diff --git a/test.py b/test.py
index 6401f41..e1c236b 100644
--- a/test.py
+++ b/test.py
@@ -6,9 +6,6 @@ import numpy as np
from matplotlib import pyplot as plt
import readchar
-import queue
-
-ski_position_queue = queue.Queue()
env = gym.make("ALE/Skiing-v5", render_mode="human")
@@ -70,9 +67,4 @@ for _ in range(1000000):
observation, reward, terminated, truncated, info = env.step(0)
observation, reward, terminated, truncated, info = env.step(0)
- #plt.imshow(observation)
- #plt.show()
- #im = Image.fromarray(observation)
- #im.save("init.png")
-
env.close()
diff --git a/train.py b/train.py
new file mode 100644
index 0000000..8021c12
--- /dev/null
+++ b/train.py
@@ -0,0 +1,14 @@
+from stable_baselines3 import PPO, DQN
+from stable_baselines3.common.monitor import Monitor
+from stable_baselines3.common.logger import configure, Image
+from stable_baselines3.common.callbacks import BaseCallback, EvalCallback, CheckpointCallback
+from gym_minigrid.wrappers import RGBImgObsWrapper, ImgObsWrapper, MiniWrapper
+
+import os
+from subprocess import call
+import time
+import argparse
+import gym
+
+env = gym.make("ALE/Skiing-v5", render_mode="human")
+observation, info = env.reset()