changes i dont remember #yolo

2017-12-16 Marktkauf Getraenke 3523.pdf.ptt

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\ No newline at end of file

2018_02_03_19_56_07.pdf.ms

+ 
+
+
+
+  
+ W 
+
+
+
+  
+ _____ _.FEMHNN 
+
+
+
+  
+ m täande 3 
+
+
+
+  
+ 49549 Ladbergen 
+
+
+
+  
+ 515t„ EU Cli'llélb'fllbälfl 
+ r'>'\: . -N“ . L?'\?l '} 1-3".’ €. 5"« 
+
+
+
+  
+ Kää$öLßl 
+
+
+
+  
+ Rechnung -Nr.17945um 06,01.2018 
+ Mitarbeiter Marlene Fröfi1:28:ll 
+
+
+
+  
+ 38 K 0,75 
+
+
+
+  
+ KI-Dominos ZB 250g 28,50 
+ 13 X 1,99 
+ LA-Zimtsterne 1759 25,87 
+ 50 X 1,50 
+ HL-Mozartkugeln 200g 75,00 
+
+
+
+  
+ /" P /_\ // ' / /‚ 
+ “.Ä‚ ‘ \/” ZU, („’ (L „(7 . 
+ “ “7 
+ Betrag netto ' 120,91 
+ MWSt 19% 0,00 
+ MWSt 7% 8,46 
+ Rückgeld 0,00 
+ Gegeben 129,37 
+
+
+
+  
+ Vielen Dank für Ihren Einkauf ! 
+ Die Ware ist vom Umtausch 
+ ausgeschlossen. 
+
+
+
+  
+ 0000000179454 
+
+
+
+
+##################
+ 
+
+
+
+  
+ Y@QJ 
+
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+ r;b‚‘ ESG 
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+ _‚.- “'e_ K.} 
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+ 13 
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+ 7 !! N N !! l!1lll| ililllllll! 
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+ ‚‘ ‚-.nw [güg5fyz-‘f.p 
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+  
+
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+
+
+##################

global.schema

+[
+  "Rechnungsdatum",
+  "Leistungsdatum",
+  "Rechnungsadresse",
+  "Kundennummer",
+  "Bruttobetrag",
+  "Nettobetrag",
+  "IBAN",
+  "Zahlungsart",
+  "Abrechnungszeitraum",
+  "Rechnungssteller"
+]

image_to_text.py

+from PIL import Image, ImageEnhance
+import pytesseract
+import json
+import datetime
+
+from text_model import Page, Word
+from pdf_to_image import get_pdf_as_image
+
+def _read_text_via_ocr(p_image, p_lang="deu"):
+    return pytesseract.image_to_data(p_image, lang=p_lang).split("\n")[1:]
+
+def _generate_wordlist_from_rawtext(p_raw):
+    word_list = []
+    for raw_word in p_raw:
+        raw_word = raw_word.split("\t")
+        word = Word(raw_word)
+        word_list.append(word)
+    return word_list
+
+def _generate_textmodel_from_wordlist(p_wordlist):
+    page = Page()
+    for word in p_wordlist:
+        page.insert_word(word)
+    return page
+
+def _binarize_image(p_image):
+    width, height = p_image.size
+    binarized = Image.new("RGB", p_image.size)
+    binarized_data = []
+    pixeldata = p_image.getdata()
+    for pixel in pixeldata:
+
+def _preprocess_image(p_image):
+    p_image = p_image.convert("L")
+    #contrast = ImageEnhance.Contrast(p_image)
+    #return contrast.enhance(8)
+
+def generate_text_from_image(p_image, p_lang="deu"):
+    image = _preprocess_image(p_image)
+    image.save(str(int(datetime.datetime.now().timestamp())) + ".png")
+    raw_data = _read_text_via_ocr(image, p_lang)
+    wordlist = _generate_wordlist_from_rawtext(raw_data)
+    return _generate_textmodel_from_wordlist(wordlist)
+
+def _page_to_list(p_page):
+    block_as_string = []
+    for block in p_page.get_block_list():
+        line_as_string = []
+        for line in block.get_line_list():
+            line_as_string.append(str(line))
+        block_as_string.append(line_as_string)
+    return block_as_string
+
+def save_page_list_to_file(p_page_list, p_name):
+    page_list = []
+    for page in p_page_list:
+        block_list = _page_to_list(page)
+        page_list.append(block_list)
+    file = open(p_name + ".ptt", "w")
+    json.dump(page_list, file)
+    file.close()
+
+def pdf_to_text(p_path_to_pdf):
+    images = get_pdf_as_image(p_path_to_pdf)
+    pdf_name = p_path_to_pdf.split("/")[-1]
+    file = open(pdf_name + ".ms", "w")
+    for image in images:
+        text = generate_text_from_image(image)
+        file.write(str(text))
+        file.write("\n##################\n")
+    file.close()
+    
+    
\ No newline at end of file