MTGO Economy Analyzer By Jon Jelinek

1. MTGO Economy Analyzer By Jon Jelinek

2. Overall goals for this project • Pulling the buying and selling data from the magic online game. • Parse out whether or not the card was being bought or sold, the card name and the price. • Have this service run continuously, and provide a web page where users could search for a given card name, and have the buy / sell values returned to them in a useful form. (Charts and listing of data points. )

3. Step 1: Pulling the buying and selling data from the magic online game. The main source of relevant price information exists on the Classifieds section of the game. It is here that any player can post a classified ad to try and buy or sell mtgo products “cards”. Which ends up looking something like this to everyone else in the world.

4. Automated Software for ripping some screens I used AutoIT, a feature rich scripting language that is especially good at automating tasks in the microsoft windows environment. Some features that swayed me to use the AutoIT include: checkPixelSum() - takes an area on the screen and returns the checksum value of the image in that region. My thought was remember what the checksum values were for the letters on the screen, and build my text output from that library of checksums. I was also interested in trying out the tesseract OCR wrapper for AutoIT.

5. AutoIT results: pixelCheckSum() was not my friend. While blatantly obvious now, the background colors/images used by magic online make gathering pixelCheckSum for a given region of the screen ( a given letter’s region ) worthless. Example: Another issue with my autoIT scripts was I had setup my first set of scripts to read off two lines of text, from a saved screenshot. The real-time Classifieds section does not guarantee that I will have my text on the same line, it could be off by a few pixels, and that would throw off all of my checksum values. In the end I wrote 15 autoIT scripts for various tasks. The scripts ranged in size from 1K to 17K. The 17K script was 550 lines of code. I only emphasize this point because I spent a majority of my time fighting with the autoIT scripting language. In the end, the autoIT application could not handle doing 1.2 million checksums per screen. I wrote a smaller script to automatically click down the scrollbar and save off screenshots to a directory that Java would read in. On to Java…

6. Java tries its luck on the screenshots There were a very key tasks I wanted Java to perform for this project: Clean up the screenshots by eliminating any backgrounds, and then run the image through an OCR and see if the output is better. Using the OCR engine with AutoIT resulted in unreadable text. I also wanted the Java end of the project to run continuously. Feeding on new screenshots as they hit a given directory, processing the image into useful text, dropping it into a database, and finally parsing that bulk text into intelligent data. …At least that’s what I hoped to accomplish.

7. Java tries its luck on the screenshots Over a 1000 lines of code later and the project is not done because of character recognition problems. I’ve learned that making your own character recognition software is REALLY HARD, and the most popular open source solutions are not that great. Estimated project status for each component below: 100% DB model in place, waiting on quality data. 100% AutoIT scripts 70% Character recognition is holding me back. 50% Web front end. AJAX query and db link working. Chart code needs work. I didn’t want to work on this until I actually had good data. Cleaned images 100% (Java)

9. Output from Tesseract OCR \OPEN\Trad¤ng, Buyung and Sawng SOM, M11, ROE, ZEN, ININK, ALA,GON, ARB cards Many MITHIG and EOIL cards, quad pr¤n¤s* \NaL¤m¤* Human SawngNwssaRavana TBI Name Huararnn W KnwgntufmaRamuary ISI SMARTBOT SELLING Warm >·<arv2st\¤ 5\ Heartmendzrm BI RustrazurBmnnzrm ¤2\ TurpurDustm ¤2\ Umbra Mysunm UBI /O¤na‘sGatewardanm BSI /BaHyn¤¤k Gunurtm ¤2\ /Gnang¤\¤ngHarum BSI rDrag¤n‘s (lawn BM rDam¤n‘s H¤rn\¤ BM Tnur .¤ .> .> BUSV DECKTEGHBOT ·> H ·> NEW AUTOMATED SMARTBOT STORE SELLING / BUVING ALL CARDS 7 Mytnuns /Raras /Unn¤mm¤ns /G¤mm¤ns /B¤¤s¢ers 7 SAVE Up Tu 1B% OEE 7 GardB¤t, MTGO Traders, Suparnuva 7 SOM/ROE/ZZIN/M11 Mwnutaurm ¤2\[

13. Output from my homemade character recogition program after training alphabet N.Tra..dng,ying.an.dS.eling.SOM,1ROE,E.NW,CON..,RBd.Ma..nyMTHO.ILcadsg..oodprces..We.co Ho.'rnl0.h,..'o'r BUS.DECK.TC.H.B.O.TN.E...WA.UTOM..A.TE.D.S.MA.BO.TSTO..RE.S.E..LL.N.GBUYI...NG..A.L.L.C.R.DSM.ythcs./Ra.es/Uc.om..m.on./C.o.mm.o..n.s/Bosters.S.AVEUp.To.10OFC.a..rd.Bot,M.GO...ad..ers.,S.upeno.va S.M.A.R.Gla...ts...5..ecstBror.Ra0VitwM.no.ta.u.0.02. B..U...YI..N..G...Prime..va...lita.....n35Ven.g...e...v

14. Worth mentioning: Classifieds section can produce 50+ screenshots worth of ads on one run down the scrollbar. It takes my Java program 5 to 10 minutes to process 1 screenshot. Designing a way to discover letters was my greatest programming feat on this project. Recursive growing function. Stops when no more black pixels are reachable. Returns left, upper most X,Y coordinate, and the width and height of the region. This allowed me to save off sub images of the over screenshot into little letters. I created a Hash of the checksum value for each little image, and wrote a config file with all known checksum values and their corresponding values.

15. End