Add model and API

app.py

@@ -0,0 +1,184 @@
+from fastapi import FastAPI, Request
+import base64
+from PIL import Image, ImageEnhance
+import pytesseract
+from langdetect import detect, DetectorFactory
+from googletrans import Translator
+import re
+import numpy as np
+import cv2
+import unicodedata
+import io
+
+# Fix language detection randomness
+DetectorFactory.seed = 0
+
+app = FastAPI()
+
+LANG_CODE_MAP = {
+    "en": "eng", "ta": "tam", "hi": "hin",
+    "kn": "kan", "ml": "mal", "te": "tel",
+    "bn": "ben", "gu": "guj", "pa": "pan", "mr": "mar"
+}
+
+# ------------------ CLEANING ------------------
+def clean_ocr_text(text):
+    text = unicodedata.normalize("NFKC", text)
+    text = re.sub(r'\s+', ' ', text).strip()
+    replacements = {
+        r'\bI(?=\d)': '1',
+        r'(?<=\d)O\b': '0',
+        r'\bO(?=\d)': '0',
+        r'(?<=\d)l\b': '1',
+        r'\bS(?=\d)': '5',
+        r'\bBi\s*11\b': 'Bill',
+    }
+    for pattern, replacement in replacements.items():
+        text = re.sub(pattern, replacement, text, flags=re.IGNORECASE)
+    text = text.replace(" .", ".").replace(" ,", ",")
+    text = re.sub(r'\s+:\s*', ': ', text)
+    text = re.sub(r'\s+#\s*', ' #', text)
+    text = re.sub(r'[^\x00-\x7F]+', ' ', text)
+    return text
+
+# ------------------ PREPROCESSING ------------------
+def preprocess_image(image):
+    if not isinstance(image, np.ndarray):
+        image = np.array(image)
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    gray = cv2.medianBlur(gray, 3)
+    kernel = np.array([[0, -1, 0], [-1, 5,-1], [0, -1, 0]])
+    gray = cv2.filter2D(gray, -1, kernel)
+    pil_img = Image.fromarray(gray)
+    enhancer = ImageEnhance.Contrast(pil_img)
+    pil_img = enhancer.enhance(2)
+    return np.array(pil_img)
+
+# ------------------ OCR ------------------
+def perform_ocr(image):
+    text = pytesseract.image_to_string(
+        image,
+        lang='eng+tam+kan+hin+tel+mal+ben+guj+pan+mar',
+        config='--psm 6'
+    ).strip()
+    detected_lang = detect(text) if text else "en"
+    translated_text = None
+    if detected_lang != 'en' and text:
+        translator = Translator()
+        translated_text = translator.translate(text, src=detected_lang, dest='en').text
+    return {
+        "detected_language": detected_lang,
+        "original_text": text,
+        "translated_text": translated_text
+    }
+
+# ------------------ FIELD EXTRACTION ------------------
+def extract_field_from_lines(lines, patterns):
+    for line in lines:
+        for pattern in patterns:
+            match = re.search(pattern, line, flags=re.IGNORECASE)
+            if match:
+                return match.group(1).strip() if match.lastindex else match.group(0).strip()
+    return None
+
+def extract_invoice_fields(text):
+    lines = [line.strip() for line in text.split('\n') if line.strip()]
+    invoice_number_patterns = [
+      # Tax Invoice with number explicitly mentioned
+      r'(?i)(?:invoice\s*(?:number|no)?\.?\s*[:\-]?\s*)([A-Z0-9][A-Z0-9\-_/]{4,})',
+
+      r'(?i)(?:invoice\s*(?:number|no)?\.?\s*[:\-]?\s*)(?!date)([A-Z0-9][A-Z0-9\-_/]{4,})',
+
+
+
+      # Generic Invoice No. / Invoice #
+      r'(?:invoice\s*(?:number|no|nos|na|#)?\s*[:\-\=\.]?\s*)([A-Z0-9][A-Z0-9\-_/\.]{3,})',
+
+      # Receipt patterns
+      r'(?:receipt\s*(?:number|no|#)?\s*[:\-]?\s*)([A-Z0-9][A-Z0-9\-_/\.]{2,})',
+      
+      # Generic # prefix
+      r'(?:^|\s)#\s*([A-Z0-9][A-Z0-9\-_/\.]{2,})',
+
+      # Order after Receipt
+      r'(?:order\s*)([A-Z0-9][A-Z0-9\-_/\.]{2,})'
+  ]
+
+
+
+    # Context-aware patterns first (with "date" keywords)
+    date_patterns = [
+        r'(?:invoice\s*date|bill\s*date|receipt\s*date|date)\s*[:\-]?\s*(\d{1,2}[/-][A-Za-z]{3,9}[/-]?\d{2,4})',
+        r'(?:invoice\s*date|bill\s*date|receipt\s*date|date)\s*[:\-]?\s*([A-Za-z]{3,9}[ ]?\d{1,2},?[ ]?\d{4})',
+        r'(?:invoice\s*date|bill\s*date|receipt\s*date|date)\s*[:\-]?\s*(\d{4}[/-]\d{1,2}[/-]\d{1,2})',
+        r'(?:invoice\s*date|bill\s*date|receipt\s*date|date)\s*[:\-]?\s*(\d{1,2}[/-]\d{1,2}[/-]\d{2,4})',
+        r'(?:receipt\s*date)\s*[:\-]?\s*(\d{1,2}[/-]\d{1,2}[/-]\d{2,4})',
+    ]
+
+    # Fallback patterns (no keywords, match only if above fail)
+    fallback_date_patterns = [
+        r'\b(\d{1,2}\s[A-Za-z]{3,9}\s?\d{2,4})\b',
+        r'\b(\d{1,2}[/-][A-Za-z]{3,9}[/-]?\d{2,4})\b',
+        r'\b([A-Za-z]{3,9}\s*\d{1,2},?\s*\d{4})\b',
+        r'\b(\d{4}[/-]\d{1,2}[/-]\d{1,2})\b',
+        r'\b(\d{1,2}[/-]\d{1,2}[/-]\d{2,4})\b',
+    ]
+
+
+
+
+    amount_patterns = [
+        r'(?:total\s*amount|grand\s*total|amount\s*payable|net\s*amount|total|rounding)\s*[:\-]?\s*\₹?\s*([\d,]+\.\d{2})',
+        # r'Total\s+Sales\s*\(Inclusive\s+GST\)\s*[A-Za-z]*\s*([\d,.]+)'
+        #r'[\s:](\d{3,6}\.\d{2})[\s]*$',
+         #r'(?i)(?:total\s*(?:value|due)?|invoice\s*value)\s*[:\-]?\s*(?:₹|Rs\.?|INR)?\s*([\d,.]+)', # Added this pattern
+         r'\b(₹|Rs\.?|INR)\s*([\d,]+\.\d{2})\b', # Added this pattern
+         #r'(?i)(total\s*(amount|value|due)?|invoice\s*value|grand\s*total)[:\-]?\s*(₹|Rs\.?|INR)?\s*([\d,.]+)',
+         r'\b(₹|Rs\.?|INR)\s*([\d,]+\.\d{2})\b'
+
+    ]
+
+    invoice_number = extract_field_from_lines(lines, invoice_number_patterns)
+    invoice_date = extract_field_from_lines(lines, date_patterns) or extract_field_from_lines(lines, fallback_date_patterns)
+    total_amount = extract_field_from_lines(lines, amount_patterns)
+    if not total_amount:
+        numbers = []
+        for line in lines:
+            matches = re.findall(r'\d{1,3}(?:,\d{3})*(?:\.\d{2})', line)
+            numbers += [float(m.replace(',', '')) for m in matches if m]
+        if numbers:
+            total_amount = f"{max(numbers):.2f}"
+    return {
+        "invoice_number": invoice_number,
+        "invoice_date": invoice_date,
+        "total_amount": total_amount
+    }
+
+# ------------------ API ENDPOINT ------------------
+@app.post("/predict")
+async def predict(request: Request):
+    data = await request.json()
+    img_base64 = data.get("image")
+    if not img_base64:
+        return {"error": "No image provided"}
+
+    image_data = base64.b64decode(img_base64)
+    image = Image.open(io.BytesIO(image_data))
+
+    # Preprocess
+    processed_img = preprocess_image(image)
+
+    # OCR + Translation
+    text_data = perform_ocr(processed_img)
+
+    # Cleaning
+    cleaned_text = clean_ocr_text(text_data["translated_text"] or text_data["original_text"])
+
+    # Extraction
+    fields = extract_invoice_fields(cleaned_text)
+
+    return {
+        "language": text_data["detected_language"],
+        "text": cleaned_text,
+        "fields": fields
+    }

requirements.txt

@@ -0,0 +1,8 @@
+fastapi
+uvicorn
+pillow
+pytesseract
+googletrans==4.0.0-rc1
+langdetect
+opencv-python
+numpy