Update ocr_engine.py

ocr_engine.py

@@ -9,24 +9,30 @@ model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-stage1")
 def extract_weight(image: Image.Image) -> str:
     image = image.convert("RGB")
     pixel_values = processor(images=image, return_tensors="pt").pixel_values
-    generated_ids = model.generate(pixel_values)
+    generated_ids = model.generate(pixel_values, max_length=20)
     full_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
 
-    # Lowercase text but don't strip spacing before kg detection
-    full_text_lower = full_text.lower()
+    # For debugging (optional):
+    print("OCR Output:", full_text)
 
-    # Detect unit
-    if "kg" in full_text_lower.replace(" ", ""):
-        unit = "kg"
-    elif "g" in full_text_lower.replace(" ", "") or "gram" in full_text_lower:
-        unit = "grams"
-    else:
-        unit = "grams"  # default
-
-    # Extract number using regex
+    # Extract number (weight)
     match = re.search(r"(\d+(\.\d+)?)", full_text)
     if match:
         weight = match.group(1)
-        return f"{weight} {unit}"
     else:
         return "No valid weight detected"
+
+    # Detect unit — smarter match
+    text_lower = full_text.lower().replace(" ", "")
+    if any(unit in text_lower for unit in ["kg", "kgs", "kilogram", "kilo", "k.g"]):
+        unit = "kg"
+    elif any(unit in text_lower for unit in ["g", "gram", "grams"]):
+        unit = "grams"
+    else:
+        # Smart fallback: use value
+        if float(weight) >= 5:
+            unit = "kg"
+        else:
+            unit = "grams"
+
+    return f"{weight} {unit}"