Added Report

app.py

@@ -178,12 +178,78 @@ def segment_image(image: Image.Image, model: nn.Module) -> dict:
         'red_area': (np.sum(final_mask == 2) / total_pixels * 100)
     }
 
+# ====================== PDF REPORT GENERATION ======================
+def generate_pdf_report(original_img: Image.Image, mask: np.ndarray, overlay: Image.Image, 
+                       diagnosis: str, grade: str, bright_area: float, red_area: float):
+    pdf = FPDF()
+    pdf.add_page()
+    
+    # Title
+    pdf.set_font("Arial", 'B', 16)
+    pdf.cell(0, 10, "Diabetic Retinopathy Diagnosis Report", 0, 1, 'C')
+    pdf.ln(10)
+    
+    # Patient Info (placeholder)
+    pdf.set_font("Arial", '', 12)
+    pdf.cell(0, 10, "Patient: ___________________________", 0, 1)
+    pdf.cell(0, 10, "Date: _____________________________", 0, 1)
+    pdf.ln(10)
+    
+    # Diagnosis
+    pdf.set_font("Arial", 'B', 14)
+    pdf.cell(0, 10, "Diagnosis:", 0, 1)
+    pdf.set_font("Arial", '', 12)
+    pdf.cell(0, 10, f"Stage: {diagnosis}", 0, 1)
+    pdf.cell(0, 10, f"UK Grading: {grade}", 0, 1)
+    pdf.ln(10)
+    
+    # Lesion Analysis
+    pdf.set_font("Arial", 'B', 14)
+    pdf.cell(0, 10, "Lesion Analysis:", 0, 1)
+    pdf.set_font("Arial", '', 12)
+    pdf.cell(0, 10, f"Bright Lesions: {bright_area:.2f}%", 0, 1)
+    pdf.cell(0, 10, f"Red Lesions: {red_area:.2f}%", 0, 1)
+    pdf.cell(0, 10, f"Total Affected Area: {bright_area + red_area:.2f}%", 0, 1)
+    pdf.ln(15)
+    
+    # Convert images to bytes
+    def pil_to_bytes(img, format='PNG'):
+        img_byte_arr = io.BytesIO()
+        img.save(img_byte_arr, format=format)
+        return img_byte_arr.getvalue()
+    
+    # Original Image
+    pdf.set_font("Arial", 'B', 12)
+    pdf.cell(0, 10, "Original Retinal Image:", 0, 1)
+    pdf.image(io.BytesIO(pil_to_bytes(original_img)), x=50, w=100)
+    pdf.ln(5)
+    
+    # Segmentation Mask
+    mask_img = Image.fromarray((mask * 85).astype(np.uint8))
+    pdf.set_font("Arial", 'B', 12)
+    pdf.cell(0, 10, "Lesion Segmentation Mask:", 0, 1)
+    pdf.image(io.BytesIO(pil_to_bytes(mask_img)), x=50, w=100)
+    pdf.ln(5)
+    
+    # Overlay Image
+    pdf.set_font("Arial", 'B', 12)
+    pdf.cell(0, 10, "Lesion Overlay:", 0, 1)
+    pdf.image(io.BytesIO(pil_to_bytes(overlay)), x=50, w=100)
+    
+    # Footer
+    pdf.ln(15)
+    pdf.set_font("Arial", 'I', 10)
+    pdf.cell(0, 10, "This report was generated by DR Analysis System", 0, 1, 'C')
+    
+    return pdf.output(dest='S').encode('latin1')
+    
+
 # ====================== MAIN APP ======================
 def main():
     st.set_page_config(layout="wide")
     st.title("Diabetic Retinopathy Analysis")
     
-    uploaded_file = st.file_uploader("Upload retinal image", type=["jpg", "jpeg", "png"])
+    uploaded_file = st.file_uploader("", type=["jpg", "jpeg", "png"])
     if not uploaded_file:
         st.info("Please upload an image")
         return
@@ -244,13 +310,33 @@ def main():
                 cols[2].metric("Total Affected", 
                               f"{seg_results['bright_area'] + seg_results['red_area']:.2f}%")
 
-                # Download
-                st.download_button(
-                    "Download Mask",
-                    cv2.imencode('.png', seg_results['mask'] * 85)[1].tobytes(),
-                    "dr_mask.png",
-                    "image/png"
-                )
+                # Download buttons
+                col1, col2 = st.columns(2)
+                with col1:
+                    st.download_button(
+                        "Download Mask",
+                        cv2.imencode('.png', seg_results['mask'] * 85)[1].tobytes(),
+                        "dr_mask.png",
+                        "image/png"
+                    )
+                
+                with col2:
+                    # Generate and download PDF report
+                    pdf_bytes = generate_pdf_report(
+                        original_image,
+                        seg_results['mask'],
+                        overlay,
+                        predicted_class_name,
+                        uk_grade,
+                        seg_results['bright_area'],
+                        seg_results['red_area']
+                    )
+                    st.download_button(
+                        "Download Full Report",
+                        data=pdf_bytes,
+                        file_name="dr_diagnosis_report.pdf",
+                        mime="application/pdf"
+                    )
 
     except Exception as e:
         st.error(f"Error processing image: {str(e)}")