Update utility/utils.py

utility/utils.py

@@ -4,7 +4,7 @@ from huggingface_hub import InferenceClient
 from dotenv import load_dotenv
 import json
 import re
-import easyocr
+#import easyocr
 from PIL import Image, ImageEnhance, ImageDraw
 import cv2
 import numpy as np
@@ -20,10 +20,10 @@ HFT = os.getenv('HF_TOKEN')
 client = InferenceClient(model="mistralai/Mistral-7B-Instruct-v0.3", token=HFT)
 
 # Specify a custom model storage directory (ensure this path is writable)
-model_storage_directory = '/app/models'
+#model_storage_directory = '/app/models'
 
 # Create the reader object and set the model storage directory
-reader = easyocr.Reader(['en'], model_storage_directory=model_storage_directory)
+#reader = easyocr.Reader(['en'], model_storage_directory=model_storage_directory)
 
 def draw_boxes(image, bounds, color='red', width=2):
     draw = ImageDraw.Draw(image)
@@ -105,10 +105,10 @@ def extract_text_from_images(image_paths, RESULT_FOLDER):
         # Enhance the image before OCR
         #enhanced_image = load_image(image_path)
         enhanced_image = process_image(image_path, scale=2)
-        bounds = reader.readtext(enhanced_image)
+        #bounds = reader.readtext(enhanced_image)
             # Draw boxes on the processed image
         img_result = Image.fromarray(enhanced_image)
-        draw_boxes(img_result, bounds)
+        #draw_boxes(img_result, bounds)
 
         result_image_path = os.path.join(RESULT_FOLDER, f'result_{os.path.basename(image_path)}')
         img_result.save(result_image_path)  # Save the processed image