The resulting data will be saved on the local machine of the user running the script with resulting file names that match-up to the names of the videos analyzed.Īppropriate descriptive errors should be thrown if the script is unable to match up the screen recording data with the txt files. The final python script deliverable should run, and prompt the user to select the video files and txt files to be merged and converted into csv files. Another player raises to $100, then the ActionPercentofPot will be 91% (100 / (30+80) ![]() So if the flop has a pot that is initially $80 Pot sizes are the size of the pot before any players bet on that street (eg Flop, Turn, River)ĪctionPercentofPot is calculated from the initial pot plus and bets made after that. Hero = The player at the bottom center of the screen Player types are indicated by the following: If another player re-raises to $45, and then the original player re-raises to $110, then PreflopAction2 will be "Raise". For example, preflop if the player initially raises to $15, then the PreflopAction1 will be "Raise". We want to limit logging of data to two actions per street (eg Flop, Turn, River). Suits will be logged with the following format:Īvailable actions that can be logged are: ![]() Hole card values will be stored in the csv file as shown on the cards: The data from these recordings will need to be matched up with with txt files by fuzzy matching the clock visible in the screen recording. Based on the nomenclature of poker, we would like to hire an engineer that has at least a basic understanding over poker. ![]() These screen recordings come from sessions played by poker players online. The screen recordings will look like the example attached, and transcribed to look like the following csv template: ![]() We're looking for a computer vision expert to convert screen recordings into data that can be analyzed by our data scientist.
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