Update app.py

app.py

@@ -8,45 +8,12 @@ from paddleocr import PaddleOCR
 import time
 from simple_salesforce import Salesforce
 from datetime import datetime
-import boto3
+import base64
+import io
 
 # Initialize PaddleOCR once with updated parameters
 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=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'  # 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)}"
-
-    # Upload the image to S3
-    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.{aws_region}.amazonaws.com/{image_key}"
-
-    return image_url
-
 def analyze_uv_coverage(img, brightness_threshold=150, kernel_size=5, apply_blur=True, adaptive_thresh=False):
     """
     Analyze UV sterilization coverage by thresholding the grayscale image.
@@ -115,6 +82,15 @@ def create_pdf_report(coverage_percent, extracted_texts, annotated_image_path, o
 
     pdf.output(output_path)
 
+def upload_image_and_get_url(image_path):
+    """
+    TODO: Implement your image upload to public storage here.
+    For now, returns a placeholder URL.
+    """
+    # Example: upload to AWS S3, Azure Blob Storage, or other service
+    # Return the public URL to the uploaded image
+    return "https://example.com/path/to/your/annotated_image.jpg"
+
 def save_record_to_salesforce(annotated_image_url, coverage_percent, original_image_pil, compliance_threshold=80):
     sf = Salesforce(
         username=os.environ['SF_USERNAME'],
@@ -157,7 +133,7 @@ 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)  # DeprecationWarning: Use 'predict' instead of 'ocr'
+    ocr_result = ocr_model.ocr(img)
     ocr_time = time.time() - start_time
 
     extracted_texts = []
@@ -195,7 +171,7 @@ def process_image(input_img, brightness_threshold=150):
 
 iface = gr.Interface(
     fn=process_image,
-    inputs=[ 
+    inputs=[
         gr.Image(type="pil", label="Upload Post-UV Sterilization Image"),
         gr.Slider(50, 255, value=150, step=1, label="Brightness Threshold")
     ],