Update app.py

app.py

@@ -10,10 +10,36 @@ from simple_salesforce import Salesforce
 from datetime import datetime
 import base64
 import io
+import boto3
 
 # 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.
+    """
+    s3_client = boto3.client(
+        's3',
+        aws_access_key_id=os.environ['AWS_ACCESS_KEY_ID'],
+        aws_secret_access_key=os.environ['AWS_SECRET_ACCESS_KEY'],
+        region_name='your-region'
+    )
+
+    # Define the S3 bucket name
+    bucket_name = 'your-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.{os.environ['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.
@@ -82,15 +108,6 @@ 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'],
@@ -164,6 +181,7 @@ 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)
 
@@ -171,7 +189,7 @@ 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")
     ],