Sanjayraju30 commited on
Commit
2f21856
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verified ·
1 Parent(s): c52373a

Update ocr_engine.py

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  1. ocr_engine.py +14 -32
ocr_engine.py CHANGED
@@ -1,35 +1,17 @@
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  from transformers import TrOCRProcessor, VisionEncoderDecoderModel
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- from PIL import Image, ImageEnhance
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- import re
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- # Load model optimized for printed text (NOT handwritten)
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- processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-printed")
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- model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-printed")
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- def extract_weight(image: Image.Image) -> str:
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- # Step 1: Preprocess image to enhance readability
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- image = image.convert("L") # grayscale
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- image = ImageEnhance.Contrast(image).enhance(2.0)
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- image = ImageEnhance.Sharpness(image).enhance(2.5)
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- image = image.convert("RGB")
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-
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- # Step 2: Run TrOCR
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- pixel_values = processor(images=image, return_tensors="pt").pixel_values
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- generated_ids = model.generate(pixel_values, max_length=32)
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- full_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
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- print("OCR Output:", full_text)
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-
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- # Step 3: Extract numeric value
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- cleaned = full_text.lower().replace(" ", "")
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- match = re.search(r"(\d+(\.\d+)?)", cleaned)
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- weight = match.group(1) if match else None
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-
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- # Step 4: Determine unit
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- if any(u in cleaned for u in ["kg", "kgs", "kilo"]):
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- unit = "kg"
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- elif any(u in cleaned for u in ["g", "gram", "grams"]):
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- unit = "grams"
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- else:
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- unit = "kg" if weight and float(weight) >= 20 else "grams"
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-
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- return f"{weight} {unit}" if weight else "No valid weight detected"
 
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  from transformers import TrOCRProcessor, VisionEncoderDecoderModel
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+ from PIL import Image
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+ import torch
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+ # Load processor and model only once
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+ processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-handwritten")
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+ model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-handwritten")
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+ def extract_weight(image):
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+ try:
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+ # Resize or preprocess if needed
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+ pixel_values = processor(images=image, return_tensors="pt").pixel_values
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+ generated_ids = model.generate(pixel_values)
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+ text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
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+ return text.strip()
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+ except Exception as e:
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+ return f"Error: {str(e)}"