updated the model with helper function to get the completed and the correct output

README.md

@@ -10,3 +10,41 @@ pinned: false
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# ⚡ Receipt Extractor
+
+A simple web application to extract information from receipt images using **YOLOv8** and **EasyOCR**. Built with **Gradio** for an interactive interface.
+
+---
+
+## Features
+
+- Detects and extracts:
+  - Merchant Name
+  - Date
+  - Total Amount
+  - Items with prices
+  - Time, Discount, and Tax (if present)
+- Handles receipts with multiple items.
+- Interactive web interface via Gradio.
+
+---
+
+## Tech Stack
+
+- **Python 3.12+**
+- **YOLOv8** (Ultralytics) – Object Detection
+- **EasyOCR** – Text Extraction
+- **OpenCV** – Image Processing
+- **Gradio** – Web Interface
+- **NumPy** – Numerical Operations
+
+---
+
+## Installation (Local / Colab)
+
+1. Clone the repository:
+
+```bash
+git clone git clone https://huggingface.co/spaces/Sivakkanth/receipt-extractor
+cd receipt-extractor

app.py

@@ -3,9 +3,11 @@ import cv2
 from ultralytics import YOLO
 import easyocr
 import numpy as np
+import re
+from datetime import datetime
 
-# Load YOLO model (replace with your custom weights path if needed)
-model = YOLO("model/best.pt")  
+# Load YOLO model
+model = YOLO("model/best.pt")
 
 # Initialize OCR
 reader = easyocr.Reader(['en'])
@@ -13,53 +15,177 @@ reader = easyocr.Reader(['en'])
 # Class names
 class_names = ["Merchant","date","total","no","item"]
 
+# Regex for numbers
+NUMBER_RE = re.compile(r"\d+(?:\.\d+)?")
+NUMBER_RE_PARSE = re.compile(r'[-+]?\d{1,3}(?:[,\d]*\d)?(?:[.,]\d{1,2})?')
+
+# OCR fixes
+OCR_FIXES = {'O':'0', 'o':'0', 'l':'1', '`':"'", 'S':'5', '$':'5', 'I':'1'}
+
+# ---------- Helper functions ----------
+def normalize_ocr_text(s: str) -> str:
+    s = s.replace('\n',' ').strip()
+    for k,v in OCR_FIXES.items():
+        s = s.replace(k,v)
+    s = re.sub(r'\s{2,}', ' ', s)
+    return s
+
+def extract_numbers_parse(s: str):
+    tokens = NUMBER_RE_PARSE.findall(s)
+    nums = []
+    for t in tokens:
+        t_norm = t.replace(',', '')
+        if ',' in t and '.' not in t and re.search(r',\d{1,2}$', t):
+            t_norm = t.replace(',', '.')
+        try:
+            nums.append(float(t_norm))
+        except:
+            continue
+    return nums
+
+def pick_price_from_numbers(numbers, original_str):
+    if not numbers:
+        return None
+    if len(numbers) > 1:
+        largest = max(numbers)
+        matches = NUMBER_RE_PARSE.finditer(original_str)
+        found = [m.group(0) for m in matches]
+        if found:
+            try:
+                t = found[-1].replace(',', '')
+                if ',' in found[-1] and '.' not in found[-1] and re.search(r',\d{1,2}$', found[-1]):
+                    t = found[-1].replace(',', '.')
+                return float(t)
+            except:
+                return largest
+        return largest
+    else:
+        return numbers[0]
+
+def clean_product_name(s: str):
+    s = re.sub(r'\b(x|qty|pcs|pc|nos|no|each)\b', '', s, flags=re.IGNORECASE)
+    s = re.sub(NUMBER_RE_PARSE, '', s)
+    s = re.sub(r'[\$₹£€:,()*`"“”]', ' ', s)
+    s = re.sub(r'\s{2,}', ' ', s).strip()
+    return s
+
+def parse_line_item(raw_line: str):
+    raw = normalize_ocr_text(raw_line)
+    numbers = extract_numbers_parse(raw)
+    price = pick_price_from_numbers(numbers, raw)
+    product = clean_product_name(raw)
+    return {"product": product if product else raw_line, "price": f"{price:.2f}" if price is not None else ""}
+
+def extract_total_amount(total_str: str):
+    if not total_str:
+        return None
+    matches = NUMBER_RE.findall(total_str)
+    for m in matches[::-1]:
+        try:
+            return float(m.replace(",",""))
+        except:
+            continue
+    return None
+
+def parse_date(text):
+    text = text.replace('Date','').replace('date','').replace(':','').strip()
+    patterns = [r"(\d{2}[/-]\d{2}[/-]\d{2,4})", r"(\d{4}[/-]\d{2}[/-]\d{2})"]
+    for pat in patterns:
+        match = re.search(pat, text)
+        if match:
+            dt_str = match.group(1)
+            for fmt in ("%d/%m/%y", "%d/%m/%Y", "%Y-%m-%d"):
+                try:
+                    dt = datetime.strptime(dt_str, fmt)
+                    return dt.strftime("%Y-%m-%d")
+                except:
+                    continue
+    return None
+
+def parse_time(text):
+    text = text.replace('Time','').replace('time','').replace(':','').strip()
+    patterns = [r"(\d{1,2}:\d{2}(:\d{2})?)"]
+    for pat in patterns:
+        match = re.search(pat, text)
+        if match:
+            tm_str = match.group(1)
+            for fmt in ("%H:%M:%S","%H:%M"):
+                try:
+                    tm = datetime.strptime(tm_str, fmt)
+                    return tm.strftime("%H:%M:%S")
+                except:
+                    continue
+    return None
+
+# ---------- Main extraction function ----------
 def extract_receipt(image):
-    # Convert from PIL to OpenCV
     img = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
-    
     results = model(img)[0]
-    
-    output = {
-        "items": [],
-        "name": "",
-        "total": "",
-        "date": "",
-        "time": "",
-        "discount": "",
-        "tax": ""
-    }
-    
+
+    output = {"items": [], "name": "", "total": "", "date": "", "time": "", "discount": 0.0, "tax": 0.0}
+
     for box, cls_id, conf in zip(results.boxes.xyxy, results.boxes.cls, results.boxes.conf):
         x1, y1, x2, y2 = [int(i) for i in box]
         cls_id = int(cls_id)
         cls_name = class_names[cls_id]
+
         crop = img[y1:y2, x1:x2]
         text_result = reader.readtext(crop)
         text = " ".join([t[1] for t in text_result])
-        
+
         if cls_name == "Merchant":
             output["name"] = text
         elif cls_name == "date":
-            output["date"] = text
+            parsed_date = parse_date(text)
+            if parsed_date:
+                output["date"] = parsed_date
         elif cls_name == "total":
             output["total"] = text
         elif cls_name == "no":
-            output["time"] = text
+            parsed_time = parse_time(text)
+            if parsed_time:
+                output["time"] = parsed_time
         elif cls_name == "item":
-            parts = text.rsplit(" ", 1)
-            if len(parts) == 2 and parts[1].replace(".","").isdigit():
-                output["items"].append({"product": parts[0], "price": parts[1]})
-            else:
-                output["items"].append({"product": text, "price": ""})
+            parsed = parse_line_item(text)
+            new_product = parsed["product"]
+            new_price = float(parsed["price"]) if parsed["price"] else None
+            output["items"].append({"product": new_product, "price": new_price if new_price is not None else ""})
+
+    # ---------- Post-processing totals ----------
+    model_total = extract_total_amount(output.get("total",""))
+    item_sum = sum([it["price"] for it in output["items"] if it.get("price") not in ("",None)])
+
+    if model_total is None or model_total > item_sum*10:
+        model_total = round(item_sum,2)
+        tax, discount = 0.0, 0.0
+    else:
+        if abs(model_total - item_sum) < 0.01:
+            tax, discount = 0.0, 0.0
+        elif model_total > item_sum:
+            tax, discount = round(model_total - item_sum,2), 0.0
+        else:
+            tax, discount = 0.0, round(item_sum - model_total,2)
+
+    output["total"] = model_total
+    output["tax"] = tax
+    output["discount"] = discount
+
+    # ---------- Fill missing date/time ----------
+    now = datetime.now()
+    if not output["date"]:
+        output["date"] = now.strftime("%Y-%m-%d")
+    if not output["time"]:
+        output["time"] = now.strftime("%H:%M:%S")
+
     return output
 
-# Gradio interface
+# ---------- Gradio Interface ----------
 iface = gr.Interface(
     fn=extract_receipt,
     inputs=gr.Image(type="pil"),
     outputs=gr.JSON(),
     title="Receipt Extractor",
-    description="Upload a receipt image to extract merchant, date, total, and items."
+    description="Upload a receipt image to extract merchant, date, total, time, and items."
 )
 
 iface.launch(share=True)

requirements.txt

@@ -1,6 +1,7 @@
-torch
-torchvision
-ultralytics
-opencv-python-headless
-easyocr
-gradio
+torch==2.8.0+cu126
+torchvision==0.23.0+cu126
+ultralytics==8.3.203
+opencv-python-headless==4.12.0.88
+easyocr==1.7.2
+gradio==5.46.0
+numpy==2.0.2