Update app.py

app.py

@@ -4,6 +4,7 @@ import cv2
 import os
 import base64
 import io
+import pandas as pd
 from dotenv import load_dotenv
 from groq import Groq
 from reportlab.lib.pagesizes import letter
@@ -81,50 +82,6 @@ def process_image_data(uploaded_file):
         st.error(f"Image processing error: {str(e)}")
         return None, None
 
-def extract_video_frames(uploaded_video):
-    """Extract frames from uploaded video for analysis"""
-    try:
-        tfile = io.BytesIO(uploaded_video.read())
-        temp_filename = "temp_video.mp4"
-        with open(temp_filename, "wb") as f:
-            f.write(tfile.getvalue())
-        
-        cap = cv2.VideoCapture(temp_filename)
-        frame_list = []
-        frame_count = 0
-        
-        while cap.isOpened():
-            ret, frame = cap.read()
-            if not ret or frame_count > 10:  # Process only up to 10 frames
-                break
-            frame_list.append(frame)
-            frame_count += 1
-        
-        cap.release()
-        os.remove(temp_filename)
-        return frame_list
-    except Exception as e:
-        st.error(f"Video processing error: {str(e)}")
-        return []
-
-def generate_pdf_report(report_text):
-    """Generate PDF document from report text"""
-    buffer = io.BytesIO()
-    doc = SimpleDocTemplate(buffer, pagesize=letter)
-    styles = getSampleStyleSheet()
-    story = []
-    
-    title = Paragraph("<b>Rice Quality Report</b>", styles['Title'])
-    story.append(title)
-    story.append(Spacer(1, 12))
-    
-    content = Paragraph(report_text.replace('\n', '<br/>'), styles['BodyText'])
-    story.append(content)
-    
-    doc.build(story)
-    buffer.seek(0)
-    return buffer
-
 def generate_rice_report(image_data, img_format, client):
     """Generate AI-powered rice quality analysis"""
     if not image_data:
@@ -139,12 +96,12 @@ def generate_rice_report(image_data, img_format, client):
                 "role": "user",
                 "content": [
                     {"type": "text", "text": (
-                        "Analyze the rice grain image and provide a detailed report including:\n"
-                        "1. Rice type classification\n"
-                        "2. Quality assessment (broken grains %, discoloration %, impurities %)\n"
-                        "3. Foreign object detection\n"
-                        "4. Size and shape consistency\n"
-                        "5. Recommendations for processing or improvement"
+                        "Analyze the rice grain image and provide a detailed report including:",
+                        "Rice type classification",
+                        "Quality assessment (broken grains %, discoloration %, impurities %)",
+                        "Foreign object detection",
+                        "Size and shape consistency",
+                        "Recommendations for processing or improvement"
                     )},
                     {"type": "image_url", "image_url": {"url": image_url}},
                 ]
@@ -158,6 +115,12 @@ def generate_rice_report(image_data, img_format, client):
         st.error(f"API communication error: {str(e)}")
         return None
 
+def format_report_as_table(report_text):
+    """Convert report text into structured table format"""
+    rows = [row.split(': ') for row in report_text.split('\n') if ': ' in row]
+    df = pd.DataFrame(rows, columns=["Category", "Details"])
+    return df
+
 def display_main_interface():
     """Render primary application interface"""
     st.title("🌾 Rice Quality Analyzer")
@@ -167,8 +130,8 @@ def display_main_interface():
 def render_sidebar(client):
     """Create sidebar interface elements"""
     with st.sidebar:
-        st.subheader("Upload Image or Video")
-        uploaded_file = st.file_uploader("Select an image or video", type=ALLOWED_FILE_TYPES + ALLOWED_VIDEO_TYPES)
+        st.subheader("Upload Image")
+        uploaded_file = st.file_uploader("Select an image", type=ALLOWED_FILE_TYPES)
         
         if uploaded_file:
             base64_image, img_format = process_image_data(uploaded_file)
@@ -180,7 +143,8 @@ def render_sidebar(client):
     
     if "analysis_result" in st.session_state:
         st.markdown("### 📋 Analysis Report")
-        st.markdown(f'<div class="report-container"><div class="report-text">{st.session_state.analysis_result}</div></div>', unsafe_allow_html=True)
+        report_df = format_report_as_table(st.session_state.analysis_result)
+        st.table(report_df)
 
 def main():
     configure_application()