Update app.py

app.py

@@ -16,16 +16,25 @@ ocr_model = PaddleOCR(use_textline_orientation=True, lang='en')
 def upload_image_and_get_url(image_path):
     """
     Upload the image to AWS S3 and return the public URL.
+    The AWS credentials must be set in the environment variables.
     """
+    # Ensure that AWS credentials are set in the environment variables
+    aws_access_key_id = os.environ.get('AWS_ACCESS_KEY_ID')
+    aws_secret_access_key = os.environ.get('AWS_SECRET_ACCESS_KEY')
+    aws_region = os.environ.get('AWS_REGION')
+
+    if not aws_access_key_id or not aws_secret_access_key or not aws_region:
+        raise ValueError("AWS credentials (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION) are missing in environment variables.")
+
     s3_client = boto3.client(
         's3',
-        aws_access_key_id=os.environ['AWS_ACCESS_KEY_ID'],  # Set environment variable
-        aws_secret_access_key=os.environ['AWS_SECRET_ACCESS_KEY'],  # Set environment variable
-        region_name=os.environ['AWS_REGION']  # Set environment variable
+        aws_access_key_id=aws_access_key_id,
+        aws_secret_access_key=aws_secret_access_key,
+        region_name=aws_region
     )
 
     # Define the S3 bucket name
-    bucket_name = 'your-bucket-name'
+    bucket_name = 'your-bucket-name'  # Replace with your S3 bucket name
 
     # Generate a unique key for the image (e.g., using the file name)
     image_key = f"images/{os.path.basename(image_path)}"
@@ -34,7 +43,7 @@ def upload_image_and_get_url(image_path):
     s3_client.upload_file(image_path, bucket_name, image_key)
 
     # Construct the public URL for the uploaded image
-    image_url = f"https://{bucket_name}.s3.{os.environ['AWS_REGION']}.amazonaws.com/{image_key}"
+    image_url = f"https://{bucket_name}.s3.{aws_region}.amazonaws.com/{image_key}"
 
     return image_url
 
@@ -148,7 +157,7 @@ def process_image(input_img, brightness_threshold=150):
         img = cv2.resize(img, (int(w * scale), int(h * scale)))
 
     start_time = time.time()
-    ocr_result = ocr_model.ocr(img)
+    ocr_result = ocr_model.ocr(img)  # DeprecationWarning: Use 'predict' instead of 'ocr'
     ocr_time = time.time() - start_time
 
     extracted_texts = []
@@ -179,7 +188,6 @@ def process_image(input_img, brightness_threshold=150):
 
     report_text = f"UV Sterilization Coverage: {coverage_percent:.2f}%"
 
-
     # Clean up temp image file after PDF generation
     os.unlink(annotated_img_path)