Max Performance V 1.1 Press Z and it would add/upgrade: armor, engine, brakes, transmission, turbo, suspension and unburstable tires. And well, repair your car. The script's open source. Open it with Notepad to view the source code. Installation: Put maxperformance.cs into your 'scripts' folder.

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Explorations of Using Python to play Grand Theft Auto 5

RPG = 5 Stinger = 5 Grenades = 4 Stickybombs = 6 Smokegrenade = 4 BZGas = 4 Flares = 10 Molotov = 4 Tank = 50 Space Rocket = 10 How to Install - 1. First make a backup of update.rpf located in Grand Theft Auto V update 2. Extract the rar file. Open OpenIV and open update.rpf 4. Go into edit mode 5. Go to common / data / ai 6. Explorations of Using Python to play Grand Theft Auto 5 8 minute read Explorations of Using Python to play Grand Theft Auto 5. GTA 5 is a great environment to practice in for a variety of reasons; With GTA, we can use modes to control the time of day, weather,traffic,speeds, what happens. RPG = 5 Stinger = 5 Grenades = 4 Stickybombs = 6 Smokegrenade = 4 BZGas = 4 Flares = 10 Molotov = 4 Tank = 50 Space Rocket = 10 How to Install - 1. First make a backup of update.rpf located in Grand Theft Auto Vupdate 2. Extract the rar file. Open OpenIV and open update.rpf 4. Go into edit mode 5. Go to common / data / ai 6.

• GTA 5 is a great environment to practice in for a variety of reasons
• With GTA, we can use modes to control the time of day, weather,traffic,speeds, what happens when we crash, all kinds of things
• It is a just a completely customizable environment
• This method can be done on a variety of games
• This initial goal is to create a sort of self-driving car
• The method he will use to access the game should be do-able on almost any game
• Things like sun glare in GAT V will make computer vision much more challenging, but also more realistic
• We can teach an AI to play games by simply showing it how to play for a bit, using CNN on that information, and then letting the AI poke around
• Here are initial thoughts
  • We can access frames from the scree
  • We can mimic key-presses(sendkeys,pyautogui and probably many other options)
• This is enough for rudimentary tasks, but what about for deep learning?
• The only extra thing we might want is something that can also log various events from the game world
• Since most games are played almost completely visually, we can handle for that, and we can also track mouse position and key presses, allowing us to engage in deep learning
• Main concern is processing everything fast enough
• So this is quite a large project
• The initial goals are
  1. Access the game screen at a somewhat decent FPS Anything over 5 should be workable for us, unpleasant to watch, but workable,and we can always watch the actual live game, rather than the processing frames
  2. Send keyboard input to game screen.
  3. Try some form of joystick input if possible(especially considering throttle and turning)
  4. Simple self-driving car that stays in some lanes under simple conditions(High sun,clear day, no rain, no traffic…)

So step 1, how should we actually accesses our screen?

• refer to this implementation stackoverflow impl, it just appears to have a typo on the import, ImageGrab is part of PIL

• ImageGrab is only availeble for Windows or MacPython: Using Pyscreenshot image to get RGB values (Linux)
• This gives 12 ~ 13 FPS

The next thing we want to do is to run OpenCV on the captured screen data

• We’ll convert the image to grayscale to simplify things and edge detection to eventually be used for finding the lines that will be our lanes

• let’s add some grayscale and edges

pyautogui, Control the keyboard and mouse from a Python script

• But Some games want “Direct Input” instead of pyautogui sendkeys
• Window direct key input examples

We get a full list of direct x scan codes here: direct x scan codes

We’re interesting in W, A, S, and D for now:

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W = 0x11

A = 0x1E

S = 0x1F

D = 0x20

Region of Interest for finding lanes

• We’re back on the task of trying to do some self-driving
• In order to do this, a common goal is to be able to detect lanes

Hough Lines

• HoughlinesP algorithm

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• draw lines on the image

• use GausssinaBlur

Finding Lanes for self-driving car

• find the edges, selected a region of interest, and then finally have found lines

Self Driving Car control

Reference sites

So you’ve got your hands on Rockstar’s Grand Theft Auto 5 for the PC, but your rig at the moment isn’t capable of running the game at the higher settings, let alone in 4K, but is upgrading worth it? It’ll probably set you back a small fortune but here’s the good news, you might not have to because Rockstar has recently announced a contest in which they will be giving away a one-of-a-kind gaming PC.

As you can see in the image above, this is a GTA-themed PC thanks to the “V” design spotted on the side panel. It has been custom built for Rockstar by the folks at Digital Storm, who for those unfamiliar are famous for building some pretty insanely power gaming rigs. So what kind of specs are we looking at here? For starters it will come with a six-core Intel i7 5930K CPU, an Intel 750 series SSD although the size was not revealed, 32GB of DDR4 RAM, and two NVIDIA Titan X cards along with liquid cooling.

This will no doubt make the computer more than capable of running the game at the highest settings, and if you have a 4K monitor, you should be able to pull off 4K with no problem and at a buttery smooth 60 frames per second! Of course given that this is a contest it means that not everyone can win but if you’d like to try your luck, head on over to the Rockstar Social Club website where you can find out the official rules on how to take part in the contest.

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