Updated receipt details extract function

app.py

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+import gradio as gr
+import cv2
+from ultralytics import YOLO
+import easyocr
+import numpy as np
+
+# Load YOLO model (replace with your custom weights path if needed)
+model = YOLO("model/best.pt")  
+
+# Initialize OCR
+reader = easyocr.Reader(['en'])
+
+# Class names
+class_names = ["Merchant","date","total","no","item"]
+
+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": ""
+    }
+    
+    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
+        elif cls_name == "total":
+            output["total"] = text
+        elif cls_name == "no":
+            output["time"] = text
+        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": ""})
+    return output
+
+# 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."
+)
+
+iface.launch()

model/best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:81a4e87311bbd29b5c4e7d76445323cbcca276f788ff6900e4957e1ee90bae42
+size 6250602

requirements.txt

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+torch
+torchvision
+ultralytics
+opencv-python-headless
+easyocr
+gradio