Spaces:
Sleeping
Sleeping
File size: 7,376 Bytes
c64c726 f1594be c64c726 f1594be c64c726 f1594be c64c726 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 |
"""
Credits: some parts are taken and modified from the file `config.py` from https://github.com/TeaPearce/Counter-Strike_Behavioural_Cloning/
"""
from dataclasses import dataclass
from typing import Dict, List, Set, Tuple
import numpy as np
try:
import pygame # type: ignore
except Exception:
pygame = None # type: ignore
import torch
from .keymap import CSGO_FORBIDDEN_COMBINATIONS, CSGO_KEYMAP
@dataclass
class CSGOAction:
keys: List[int]
mouse_x: float
mouse_y: float
l_click: bool
r_click: bool
def __post_init__(self) -> None:
self.keys = filter_keys_pressed_forbidden(self.keys)
self.process_mouse()
@property
def key_names(self) -> List[str]:
# Use pygame to convert key codes when available; else assume keys already strings
names: List[str] = []
for key in self.keys:
if pygame is not None:
try:
names.append(pygame.key.name(key))
continue
except Exception:
pass
# Fallback for headless: keep as-is or cast to string
names.append(str(key))
return names
def process_mouse(self) -> None:
# Clip and match mouse to closest in list of possibles
x = np.clip(self.mouse_x, MOUSE_X_LIM[0], MOUSE_X_LIM[1])
y = np.clip(self.mouse_y, MOUSE_Y_LIM[0], MOUSE_Y_LIM[1])
self.mouse_x = min(MOUSE_X_POSSIBLES, key=lambda x_: abs(x_ - x))
self.mouse_y = min(MOUSE_Y_POSSIBLES, key=lambda x_: abs(x_ - y))
# Use arrows to override mouse movements
for key in self.key_names:
if key == "left":
self.mouse_x = -60
elif key == "right":
self.mouse_x = +60
elif key == "up":
self.mouse_y = -50
elif key == "down":
self.mouse_y = +50
def print_csgo_action(action: CSGOAction) -> Tuple[str]:
action_names = [CSGO_KEYMAP[k] for k in action.keys] if len(action.keys) > 0 else []
action_names = [x for x in action_names if not x.startswith("camera_")]
keys = " + ".join(action_names)
mouse = str((action.mouse_x, action.mouse_y)) * (action.mouse_x != 0 or action.mouse_y != 0)
clicks = "L" * action.l_click + " + " * (action.l_click and action.r_click) + "R" * action.r_click
return keys, mouse, clicks
MOUSE_X_POSSIBLES = [
-1000,
-500,
-300,
-200,
-100,
-60,
-30,
-20,
-10,
-4,
-2,
0,
2,
4,
10,
20,
30,
60,
100,
200,
300,
500,
1000,
]
MOUSE_Y_POSSIBLES = [
-200,
-100,
-50,
-20,
-10,
-4,
-2,
0,
2,
4,
10,
20,
50,
100,
200,
]
MOUSE_X_LIM = (MOUSE_X_POSSIBLES[0], MOUSE_X_POSSIBLES[-1])
MOUSE_Y_LIM = (MOUSE_Y_POSSIBLES[0], MOUSE_Y_POSSIBLES[-1])
N_KEYS = 11 # number of keyboard outputs, w,s,a,d,space,ctrl,shift,1,2,3,r
N_CLICKS = 2 # number of mouse buttons, left, right
N_MOUSE_X = len(MOUSE_X_POSSIBLES) # number of outputs on mouse x axis
N_MOUSE_Y = len(MOUSE_Y_POSSIBLES) # number of outputs on mouse y axis
def encode_csgo_action(csgo_action: CSGOAction, device: torch.device) -> torch.Tensor:
# mouse_x = csgo_action.mouse_x
# mouse_y = csgo_action.mouse_y
keys_pressed_onehot = np.zeros(N_KEYS)
mouse_x_onehot = np.zeros(N_MOUSE_X)
mouse_y_onehot = np.zeros(N_MOUSE_Y)
l_click_onehot = np.zeros(1)
r_click_onehot = np.zeros(1)
for key in csgo_action.key_names:
if key == "w":
keys_pressed_onehot[0] = 1
elif key == "a":
keys_pressed_onehot[1] = 1
elif key == "s":
keys_pressed_onehot[2] = 1
elif key == "d":
keys_pressed_onehot[3] = 1
elif key == "space":
keys_pressed_onehot[4] = 1
elif key == "left ctrl":
keys_pressed_onehot[5] = 1
elif key == "left shift":
keys_pressed_onehot[6] = 1
elif key == "1":
keys_pressed_onehot[7] = 1
elif key == "2":
keys_pressed_onehot[8] = 1
elif key == "3":
keys_pressed_onehot[9] = 1
elif key == "r":
keys_pressed_onehot[10] = 1
l_click_onehot[0] = int(csgo_action.l_click)
r_click_onehot[0] = int(csgo_action.r_click)
mouse_x_onehot[MOUSE_X_POSSIBLES.index(csgo_action.mouse_x)] = 1
mouse_y_onehot[MOUSE_Y_POSSIBLES.index(csgo_action.mouse_y)] = 1
assert mouse_x_onehot.sum() == 1
assert mouse_y_onehot.sum() == 1
return torch.tensor(
np.concatenate((
keys_pressed_onehot,
l_click_onehot,
r_click_onehot,
mouse_x_onehot,
mouse_y_onehot,
)),
device=device,
dtype=torch.float32,
)
def decode_csgo_action(y_preds: torch.Tensor) -> CSGOAction:
y_preds = y_preds.squeeze()
keys_pred = y_preds[0:N_KEYS]
l_click_pred = y_preds[N_KEYS : N_KEYS + 1]
r_click_pred = y_preds[N_KEYS + 1 : N_KEYS + N_CLICKS]
mouse_x_pred = y_preds[N_KEYS + N_CLICKS : N_KEYS + N_CLICKS + N_MOUSE_X]
mouse_y_pred = y_preds[
N_KEYS + N_CLICKS + N_MOUSE_X : N_KEYS + N_CLICKS + N_MOUSE_X + N_MOUSE_Y
]
keys_pressed = []
keys_pressed_onehot = np.round(keys_pred)
if keys_pressed_onehot[0] == 1:
keys_pressed.append("w")
if keys_pressed_onehot[1] == 1:
keys_pressed.append("a")
if keys_pressed_onehot[2] == 1:
keys_pressed.append("s")
if keys_pressed_onehot[3] == 1:
keys_pressed.append("d")
if keys_pressed_onehot[4] == 1:
keys_pressed.append("space")
if keys_pressed_onehot[5] == 1:
keys_pressed.append("left ctrl")
if keys_pressed_onehot[6] == 1:
keys_pressed.append("left shift")
if keys_pressed_onehot[7] == 1:
keys_pressed.append("1")
if keys_pressed_onehot[8] == 1:
keys_pressed.append("2")
if keys_pressed_onehot[9] == 1:
keys_pressed.append("3")
if keys_pressed_onehot[10] == 1:
keys_pressed.append("r")
l_click = int(np.round(l_click_pred))
r_click = int(np.round(r_click_pred))
id = np.argmax(mouse_x_pred)
mouse_x = MOUSE_X_POSSIBLES[id]
id = np.argmax(mouse_y_pred)
mouse_y = MOUSE_Y_POSSIBLES[id]
# Map string names back to pygame key codes when pygame is available; otherwise keep as strings
if pygame is not None:
try:
keys_pressed = [pygame.key.key_code(x) for x in keys_pressed]
except Exception:
pass
return CSGOAction(keys_pressed, mouse_x, mouse_y, bool(l_click), bool(r_click))
def filter_keys_pressed_forbidden(keys_pressed: List[int], keymap: Dict[int, str] = CSGO_KEYMAP, forbidden_combinations: List[Set[str]] = CSGO_FORBIDDEN_COMBINATIONS) -> List[int]:
keys = set()
names = set()
for key in keys_pressed:
if key not in keymap:
continue
name = keymap[key]
keys.add(key)
names.add(name)
for forbidden in forbidden_combinations:
if forbidden.issubset(names):
keys.remove(key)
names.remove(name)
break
return list(filter(lambda key: key in keys, keys_pressed))
|