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Let's Talk Let's Talk is an interactive discussion program about lifestyle issues. The UH Arts initiative strives to: The initiative encompasses music, visual arts, literary arts, dance, theater, and design programs in the Kathrine G. Hines College of Architecture. By Sara Tubbs — Fans of Carlos Cruz-Diez, one of the great figures of kinetic-optic art, will have a chance to learn about his iconic works during a special event on Tuesday, May 8 at the University of Houston M.
Anderson Library Elizabeth D. By Sara Tubbs — Students in the UH graphic design program along with students from creative writing are reconnecting Houstonians with the past through a public art project that looks towards the future. Meeting Points on Buffalo Bayou" is a self-guided tour of interactive, text-based installations at 1 p. Without a region specified, the entire screen is searched. These values are visualized in the following graphic:. These image files are included in the zip file download.
Note that running PyAutoGUI's image recongition takes a relatively long time to execute several hundred milliseconds. This can be mitigated by searching a smaller region instead of the entire screen. And since some objects will always appear in the same place in the game window, you can rely on using static integer coordinates instead of image recognition to find them.
Many of the buttons in the game's user interface will always be in the same location. The coordinates for these buttons can be pre-programmed ahead of time. You could take a screenshot, paste the image into a graphics program such as Photoshop or MS Paint, and find all of the XY coordinates yourself. But this tutorial has done this step for you.
The other coordinate global variables are populated in the setupCoordinates function. This is visualized in the following graphic:. This tutorial does the tedious coordinate-finding work for you, but if you ever need to do it yourself you can use the pyautogui. The coordinates update as you move the mouse, so you can move the mouse to the desired location on the screen, then view its current coordinates. You can also pass X and Y offsets to the function to set the 0, 0 origin somewhere besides the top-left corner of the screen.
When you are done, press Ctrl-C to return from the function. PyAutogui has a pyautogui. Often you can use the return value of pyautogui. The click is done immediately, but the optional duration keyword argument will specify the number of seconds PyAutoGUI spends moving to the x, y coordinate. A small delay makes it easier to visually follow along with the bot's clicking.
Since the SKIP button in the game is flashing, the pyautogui. This is why there is a while loop that keeps searching until it finds it. Remember, locateCenterOnScreen will return None if it can't find the image on the screen.
Once the buttons at the start of the game have been navigated past, the main part of the bot code can begin. Much of this functionality is passed on to other functions, which are explained later. The first part of startServing sets up all the variables for a new game:. This is handled by the getOrders function. Since you'll be repeatedly scanning for the orders but don't want to remake orders each time you scan them, you need to find out which new orders have appeared since the last scan, and which orders have disappeared since the last scan either because the customer is eating or has left.
This is handled by the getOrdersDifference. The keys in these "orders dictionaries" will be the left, top, width, height tuple of where the order image was identified. This is just to keep the customers distinct. The remakeTimes dictionary has similar keys, but it's values are unix timestamps returned from time.
The next part goes through the remakeTimes dictionary and checks if any of those timestamps are before the current time as returned by time. In that case, add this order to the remakeOrders dictionary which is similar but separate to the added orders dictionary of new orders.
Next, the program loops through all the newly requested orders in the added dictionary and attempts to make them. The makeOrder function described later will return None if the order was successfully made. Otherwise, it will return a string of the ingredient it doesn't have enough of. In that case, orderIngredient described later is called and the order is placed on the backOrders dictionary. When a customer picks up their meal, they'll spend a few seconds eating and then leave behind a dirty dish.
Click this dirty dish so that a new customer will take that seat. Instead of using image recognition which is slow , the bot can just occassionally click on all six plates. There's no penalty to clicking on the plate when the customer is eating or if there is no plate at that seat. Since this doesn't need to be done frequently, the if random. It's easy to keep track of ingredient quanties as you make dishes.
When you order ingredients they don't arrive immediately. If you used image recognition for the numbers in the lower left corner of the game window it would require grabbing tons of screenshots and slow down the bot.
The next part of code checks if the current time as returned by time. The remakeOrders dictionary contains orders that for whatever reason didn't make it to the customer. This code is similar to the previous dish-making code:.
If so, more is ordered by calling the orderIngredient function described later. This isn't something that needs to be checkeded frequently, so it is enclosed in an if statement that runs 1 in 5 times:. The next part checks for the "You Win" or "You Fail" message. Since this check doesn't need to happen frequently at all, the if time.
Also, the bot will let the user view the end-level stats for 5 seconds before clicking Continue to move on to the next level. For every level except for the last, there will be a second Continue button to click on.
On the last level, the bot doesn't do this so the user can view the game ending. The clickOnPlates function blindly clicks on all six places where there could be a dirty plate to clean up. This works because there is no penalty for clicking when there isn't a dirty plate, freeing the bot from having to use performance-costly image recognition to first identify the dirty plate. This is used to determine if a long time has passed since the plates have been cleared.
Customer orders appear as dish images in word bubbles above their heads. The getOrders function finds all the current orders being requested.