MtG-OCR

This program identifies Magic the Gathering (MtG) cards from images by optical-character-recognition (OCR) via pytesseract. The cards are safed as a cubecobra cube file in ~/git/MtG-OCR/data/Card_Identification/results/CubeCobra_DATETIME.csv. The program requires one card per image. The card may not project out of the image.

Setup

Start by installing the required modules.

  pip install -r requirements.txt
  

Install pytesseract. This version was tested with tesseract-ocr-w64-setup-5.3.4.20240503.exe Set pytesseract path to C:/Programm Files(x86)/Tesseract-OCR/.

This step is optional: To use the adb mode, install adb first. Enable debugging on your android device. See https://developer.android.com/tools/adb for an explanation on how to enable debugging. Prepare a folder named MTG-OCR on your android device and safe card images there. Set adb to path.

The package is not uploaded to pip yet. The modules cannot be imported via the package path, yet. Here is the instruction how it will be implemented stackexchange

Workflow

Running the program

Start the main function

The main function is located in ~/git/MtG-OCR/scr/Card_Identification/main_Card_Identification.py and called main_Card_Identification(mode:str = None, verbose = 2). The suggested mode is quickstart.

Modes

• quickstart Select the folder where the card images are present. The images are safed to the internal working direction. All already present images will be moved to subfolders with the current DATETIME. Only the selected cards will be processed.
• all files: The images must be safed to ~/git/MtG-OCR/data/Card_Identification/raw_IMGs beforehand. Then the contents of the selected folder is processed within the working directory (~/git/MtG-OCR/data/Card_Identification/raw_IMGs). All these images are processed.
• adb: At program start all images from the folder MTG-OCR on the connected android device are downloaed and transfered via adb to the working directory ~/git/MtG-OCR/data/Card_Identification/raw_IMGs. All images from the android device are processed.
• adb-live: Like adb, but the image contents of the MtG-OCR folder are downloaed continuously and only the newest image is processed. After each processed card a new image needs to be taken. This mode is suited for live analysis.

Output

The location of the safed files is ~/git/MtG-OCR/data/Card_Identification/results.

The results are safed as:

• results_DATETIME.txt: identified card as a list of scryfall data [["filename1.jpg",{dict of scryfall_data of filename1}]]

• identified_cards_DATETIME.txt: a list of filename the correspondig list
  [["filename1.jpg",[name,CMC,Type,Color,Set,Collector Number,Rarity,Color Category,status,Finish,maybeboard,image URL,image Back URL,tags,Notes,MTGO ID]]

• unidentified_cards_DATETIME.txt: a list of filenames which could not be identified [["filename1.jpg"]]

• CubeCobraCSV.csv: Created from identified_cards_DATETIME.txt. This .csv file can be exported manually to cubecobra to exchange ones cube.

Explanation of the program

The scripts are safed in ~/git/MtG-OCR/scr/Card_Identification

1. The program is started with the function main_Card_Identification(mode:str = None, verbose = 2) in~/git/MtG-OCR/scr/Card_Identification/main_Card_Identification.py.
2. The function extract_card(path_to_image, verbose) in card_extraction.py outputs just the card part of an image (displaying a single card) as a CV2 image. Error shall be None or is a str if something went wrong.

path_to_img = ../../MtG-OCR/data/Card_Identification/raw_image/ imagename.jpg

	def extract_card(path_to_img, verbose=0)
	
	return error, card

3. The card is processed with create_rois_from_filename(filename, mtg_ocr_config, card= None, verbose =0)in ~/git/MtG-OCR/scr/Card_Identification/process_card.py

   This function gets input from extract_card() and creates ROIs (pictures of regions of interest) in the directory ~/git/MtG-OCR/data/Card_Identification/processed_ROI/ imagename.jpg

4. The rois are pcoessed with return_cardname_from_ROI(filename, scryfall_all_data, verbose = 0) --> Cardname in ~/git/MtG-OCR/scr/Card_Identification/process_rois.py

   This function checks the rois for information to extract the cardname, set and collector_number. Output is Cardname which is a list of dicts of fitting scryfall entries. The list is sorted according to the levenshtein distance of the identified cardnames, sets and collector_numbers in comparision to the scryfall card data. The first entry is the best fitting card data.

5. The user confirms the found cardname, collector_number, and set with user_cardname_confirmation(filename, card_infos, card_data, card, scryfall_file, mtg_ocr_config, default_action=None) in ~/git/MtG-OCR/scr/Card_Identification/user_dialog_cardname.py.

6. The results are safed with write_results_to_file(card_names, name=None, nodatetime=None, location=None) in ~/git/MtG-OCR/scr/Card_Identification/save_results.py.

Notes

Program Handling

If verbose > 0 the program will keep displaying images, and not move on, until the the user presses any key. An exception to this rule is when the user defines new ROIs. Read the window name then. The ROIs are defined by clicking inside the window. Green squares appear and define the ROI. To save the ROIs press ENTER. Quit the window by pressing q, Q or ESC.

Verbose

Errors shall always be printed. Output in terminal:

• verbose == 0: no output except the image of the card and the dialog to identify the card
• verbose == 1: the above and output of the filepath and the identified potential cardnames, sets and collector_number
• verbose > 1: the above and the display of internally createdd images and collected informations.