Update app.py

app.py

@@ -4,6 +4,7 @@ from PIL import Image
 import json
 from reportlab.lib.pagesizes import letter
 from reportlab.pdfgen import canvas
+import re
 
 # Load BioGPT model for recommendations
 bio_gpt = pipeline("text-generation", model="microsoft/BioGPT")
@@ -19,33 +20,52 @@ def load_reference_ranges(file_path="dataset.json"):
 
 reference_ranges = load_reference_ranges()
 
+# Parameter name mapping
+parameter_mapping = {
+    "hgb": "hemoglobin",
+    "hemoglobin": "hemoglobin",
+    "rbc": "rbc",
+    "wbc": "wbc",
+    "plt": "platelet",
+    "platelets": "platelet",
+    # Add more mappings as needed
+}
+
 # Extract text from uploaded image using Hugging Face OCR
 def extract_text_from_image(image_path):
     try:
         image = Image.open(image_path)
         text = ocr_model(image)[0]["generated_text"]
+        print("Extracted Text:", text)  # Debugging
         return text
     except Exception as e:
         return f"Error extracting text: {e}"
 
+# Extract value using regex
+def extract_value(text, param):
+    match = re.search(rf"{param}\s*:\s*([\d.]+)", text, re.IGNORECASE)
+    if match:
+        return float(match.group(1))
+    return None
+
 # Analyze extracted text and compare against reference ranges
 def analyze_blood_report(text):
     abnormalities = []
     analysis = "Blood Test Analysis Results:\n\n"
 
-    for param, ranges in reference_ranges.items():
-        if param in text.lower():
-            try:
-                # Mock parsing logic to extract the value
-                value = float(text.split(param)[1].split()[0])  # Extract value after the parameter name
+    for key, standard_param in parameter_mapping.items():
+        if key in text.lower():
+            ranges = reference_ranges[standard_param]
+            value = extract_value(text, key)
+            if value is not None:
                 if value < ranges["low"]:
-                    abnormalities.append(f"{param.capitalize()} is LOW ({value} {ranges['unit']}).")
+                    abnormalities.append(f"{standard_param.capitalize()} is LOW ({value} {ranges['unit']}).")
                 elif value > ranges["high"]:
-                    abnormalities.append(f"{param.capitalize()} is HIGH ({value} {ranges['unit']}).")
+                    abnormalities.append(f"{standard_param.capitalize()} is HIGH ({value} {ranges['unit']}).")
                 else:
-                    analysis += f"{param.capitalize()} is NORMAL ({value} {ranges['unit']}).\n"
-            except Exception:
-                analysis += f"{param.capitalize()} could not be analyzed.\n"
+                    analysis += f"{standard_param.capitalize()} is NORMAL ({value} {ranges['unit']}).\n"
+            else:
+                analysis += f"{standard_param.capitalize()} could not be analyzed.\n"
 
     # Flag abnormalities
     if abnormalities:
@@ -111,7 +131,7 @@ interface = gr.Interface(
     css="""
         body {
             font-family: 'Arial', sans-serif;
-            background-color: #000000;
+            background-color: #f9f9f9;
         }
         .gradio-container {
             color: #333;