Update app.py

app.py

@@ -162,249 +162,217 @@ def generate_report(
     inference_times: List[float],
     io_times: List[float]
 ) -> str:
-    log_entries.append("Generating report...")
-    report_path = os.path.join(OUTPUT_DIR, f"drone_analysis_report_{datetime.now().strftime('%Y%m%d_%H%M%S')}.tex")
+    # Generating LaTeX-based PDF report
+    log_entries.append("Generating LaTeX report...")
+    report_path = os.path.join(OUTPUT_DIR, f"drone_analysis_report_{datetime.now().strftime('%Y%m%d_%H%M%S')}.pdf")
+    tex_path = os.path.join(OUTPUT_DIR, f"drone_analysis_report_{datetime.now().strftime('%Y%m%d_%H%M%S')}.tex")
     timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
 
-    # Prepare items for the breakdown
-    items = []
+    # LaTeX document content
+    report_content = [
+        r"\documentclass[a4paper,12pt]{article}",
+        r"\usepackage[utf8]{inputenc}",
+        r"\usepackage[T1]{fontenc}",
+        r"\usepackage{geometry}",
+        r"\geometry{margin=1in}",
+        r"\usepackage{graphicx}",
+        r"\graphicspath{{./}}",
+        r"\usepackage{booktabs}",
+        r"\usepackage{longtable}",
+        r"\usepackage{enumitem}",
+        r"\usepackage{hyperref}",
+        r"\hypersetup{colorlinks=true,linkcolor=blue,filecolor=blue,urlcolor=blue}",
+        r"\usepackage{amsmath}",
+        r"\usepackage{caption}",
+        r"\usepackage{pdfpages}",
+        r"\usepackage{times}",  # Using Times font
+        r"\begin{document}",
+        r"\title{NHAI Drone Survey Analysis Report}",
+        r"\author{Nagasurendra, Data Analyst}",
+        r"\date{\today}",
+        r"\maketitle",
+        r"\tableofcontents",
+        r"\newpage",
+        r"\section{Project Details}",
+        r"\begin{itemize}",
+        r"\item \textbf{Project Name}: NH-44 Delhi-Hyderabad Section (Package XYZ)",
+        r"\item \textbf{Highway Section}: Km 100 to Km 150",
+        r"\item \textbf{State}: Telangana",
+        r"\item \textbf{Region}: South",
+        rf"\item \textbf{Survey Date}: {datetime.now().strftime('%Y-%m-%d')}",
+        r"\item \textbf{Drone Service Provider}: ABC Drone Services Pvt. Ltd.",
+        r"\item \textbf{Technology Service Provider}: XYZ AI Analytics Ltd.",
+        rf"\item \textbf{Work Order Reference}: Data Lake WO-{datetime.now().strftime('%Y-%m-%d')}-XYZ",
+        r"\item \textbf{Report Prepared By}: Nagasurendra, Data Analyst",
+        rf"\item \textbf{Report Date}: {datetime.now().strftime('%Y-%m-%d')}",
+        r"\end{itemize}",
+        r"\section{Introduction}",
+        r"This report consolidates drone survey results for NH-44 (Km 100--150) under Operations \& Maintenance, per NHAI Policy Circular No. 18.98/2024, detecting potholes and cracks using YOLOv8 for Monthly Progress Report integration.",
+        r"\section{Drone Survey Metadata}",
+        r"\begin{itemize}",
+        r"\item \textbf{Drone Speed}: 5 m/s",
+        r"\item \textbf{Drone Height}: 60 m",
+        r"\item \textbf{Camera Sensor}: RGB, 12 MP",
+        r"\item \textbf{Recording Type}: JPEG, 90$^\circ$ nadir",
+        r"\item \textbf{Image Overlap}: 85\%",
+        r"\item \textbf{Flight Pattern}: Single lap, ROW centered",
+        r"\item \textbf{Geotagging}: Enabled",
+        r"\item \textbf{Satellite Lock}: 12 satellites",
+        r"\item \textbf{Terrain Follow Mode}: Enabled",
+        r"\end{itemize}",
+        r"\section{Quality Check Results}",
+        r"\begin{itemize}",
+        r"\item \textbf{Resolution}: 4000x3000 (12 MP)",
+        r"\item \textbf{Overlap}: 85\%",
+        r"\item \textbf{Camera Angle}: 90$^\circ$ nadir",
+        r"\item \textbf{Drone Speed}: $\leq$ 5 m/s",
+        r"\item \textbf{Geotagging}: 100\% compliant",
+        r"\item \textbf{QC Status}: Passed",
+        r"\end{itemize}",
+        r"\section{AI/ML Analytics}",
+        rf"Total Frames Processed: {frame_count}\par",
+        rf"Detection Frames: {detection_frame_count} ({detection_frame_count/frame_count*100:.2f}\%)\par",
+        rf"Total Detections: {metrics['total_detections']}\par",
+        r"\textbf{Breakdown:}",
+        r"\begin{itemize}"
+    ]
+
     for item in metrics.get("items", []):
         percentage = (item["count"] / metrics["total_detections"] * 100) if metrics["total_detections"] > 0 else 0
-        items.append(f"\\item {item['type']}: {item['count']} ({percentage:.2f}\\%)")
+        report_content.append(rf"\item {item['type']}: {item['count']} ({percentage:.2f}\%)")
+    report_content.extend([
+        r"\end{itemize}",
+        rf"Processing Time: {total_time:.2f} seconds\par",
+        rf"Average Frame Time: {sum(frame_times)/len(frame_times):.2f} ms" if frame_times else r"Average Frame Time: N/A\par",
+        rf"Average Resize Time: {sum(resize_times)/len(resize_times):.2f} ms" if resize_times else r"Average Resize Time: N/A\par",
+        rf"Average Inference Time: {sum(inference_times)/len(inference_times):.2f} ms" if inference_times else r"Average Inference Time: N/A\par",
+        rf"Average I/O Time: {sum(io_times)/len(io_times):.2f} ms" if io_times else r"Average I/O Time: N/A\par",
+        rf"Timestamp: {metrics.get('timestamp', 'N/A')}\par",
+        r"Summary: Potholes and cracks detected in high-traffic segments.\par",
+        r"\section{Output File Structure}",
+        r"\begin{itemize}",
+        rf"\item \texttt{{drone\_analysis\_report\_<{timestamp}>.pdf}}: This report",
+        r"\item \texttt{outputs/processed\_output.mp4}: Processed video with annotations",
+        rf"\item \texttt{{outputs/chart\_<{timestamp}>.png}}: Detection trend chart",
+        rf"\item \texttt{{outputs/map\_<{timestamp}>.png}}: Issue locations map",
+        r"\item \texttt{captured\_frames/detected\_<frame>.jpg}: Geotagged images for detected issues",
+        r"\item \texttt{flight\_logs/flight\_log\_<frame>.csv}: Flight logs matching image frames",
+        r"\end{itemize}",
+        r"\textbf{Note}: Images and logs share frame numbers (e.g., \texttt{detected\_000001.jpg} corresponds to \texttt{flight\_log\_000001.csv}).",
+        r"\section{Geotagged Images}",
+        rf"Total Images: {len(detected_issues)}\par",
+        rf"Storage: Data Lake \texttt{{/project\_xyz/images/{datetime.now().strftime('%Y-%m-%d')}}}\par",
+        r"\begin{longtable}{|c|l|l|l|l|l|}",
+        r"\hline",
+        r"\textbf{Frame} & \textbf{Issue Type} & \textbf{GPS (Lat, Lon)} & \textbf{Timestamp} & \textbf{Confidence} & \textbf{Image Path} \\ \hline",
+        r"\endhead"
+    ])
 
-    # Prepare image rows with embedded images
-    image_rows = []
     for detection in all_detections[:100]:
-        image_basename = os.path.basename(detection['path'])
-        image_rows.append(
-            f"{detection['frame']:06d} & {detection['label']} & "
-            f"({detection['gps'][0]:.6f}, {detection['gps'][1]:.6f}) & "
-            f"{detection['timestamp']} & {detection['conf']:.2f} & "
-            f"\\includegraphics[width=4cm, height=3cm, keepaspectratio]{{{image_basename}}} \\\\"
+        report_content.append(
+            rf"{detection['frame']:06d} & {detection['label']} & ({detection['gps'][0]:.6f}, {detection['gps'][1]:.6f}) & {detection['timestamp']} & {detection['conf']:.2f} & \texttt{{{os.path.basename(detection['path'])}}} \\ \hline"
         )
+    report_content.append(r"\end{longtable}")
+
+    # Embedding geotagged images
+    report_content.append(r"\subsection{Geotagged Images Display}")
+    for detection in all_detections[:100]:
+        image_path = detection['path']
+        if os.path.exists(image_path):
+            report_content.append(rf"\begin{{figure}}[h]")
+            report_content.append(rf"\centering")
+            report_content.append(rf"\includegraphics[width=0.8\textwidth]{{{image_path}}}")
+            report_content.append(rf"\caption{{Frame {detection['frame']:06d}: {detection['label']} at ({detection['gps'][0]:.6f}, {detection['gps'][1]:.6f}), Confidence: {detection['conf']:.2f}}}")
+            report_content.append(rf"\end{{figure}}")
+
+    report_content.extend([
+        r"\section{Flight Logs}",
+        rf"Total Logs: {len(detected_issues)}\par",
+        rf"Storage: Data Lake \texttt{{/project\_xyz/flight\_logs/{datetime.now().strftime('%Y-%m-%d')}}}\par",
+        r"\begin{longtable}{|c|l|l|l|l|l|l|l|}",
+        r"\hline",
+        r"\textbf{Frame} & \textbf{Timestamp} & \textbf{Latitude} & \textbf{Longitude} & \textbf{Speed (m/s)} & \textbf{Satellites} & \textbf{Altitude (m)} & \textbf{Log Path} \\ \hline",
+        r"\endhead"
+    ])
 
-    # Prepare flight log rows
-    log_rows = []
     for detection in all_detections[:100]:
         log_path = f"flight_logs/flight_log_{detection['frame']:06d}.csv"
-        log_rows.append(
-            f"{detection['frame']:06d} & {detection['timestamp']} & "
-            f"{detection['gps'][0]:.6f} & {detection['gps'][1]:.6f} & "
-            f"5.0 & 12 & 60 & \\texttt{{{log_path}}} \\\\"
+        report_content.append(
+            rf"{detection['frame']:06d} & {detection['timestamp']} & {detection['gps'][0]:.6f} & {detection['gps'][1]:.6f} & 5.0 & 12 & 60 & \texttt{{{os.path.basename(log_path)}}} \\ \hline"
         )
+    report_content.extend([
+        r"\end{longtable}",
+        r"\section{Processed Video}",
+        rf"Path: \texttt{{outputs/processed\_output.mp4}}\par",
+        rf"Frames: {output_frames}\par",
+        rf"FPS: {output_fps:.2f}\par",
+        rf"Duration: {output_duration:.2f} seconds\par",
+        r"\section{Visualizations}",
+        rf"Detection Trend Chart: \texttt{{outputs/chart\_<{timestamp}>.png}}\par",
+        rf"Issue Locations Map: \texttt{{outputs/map\_<{timestamp}>.png}}\par"
+    ])
+
+    # Including chart and map images
+    if chart_path and os.path.exists(chart_path):
+        report_content.extend([
+            r"\begin{figure}[h]",
+            r"\centering",
+            rf"\includegraphics[width=0.8\textwidth]{{{chart_path}}}",
+            r"\caption{Detection Trend Chart}",
+            r"\end{figure}"
+        ])
+    if map_path and os.path.exists(map_path):
+        report_content.extend([
+            r"\begin{figure}[h]",
+            r"\centering",
+            rf"\includegraphics[width=0.8\textwidth]{{{map_path}}}",
+            r"\caption{Issue Locations Map}",
+            r"\end{figure}"
+        ])
+
+    report_content.extend([
+        r"\section{Processing Timestamps}",
+        rf"Total Processing Time: {total_time:.2f} seconds\par",
+        r"\textbf{Log Entries (Last 10):}",
+        r"\begin{itemize}"
+    ])
 
-    # Prepare log entries
-    log_entries_str = []
     for entry in log_entries[-10:]:
-        log_entries_str.append(f"\\item {entry}")
-
-    # Calculate average times
-    avg_frame_time = sum(frame_times) / len(frame_times) if frame_times else 0
-    avg_resize_time = sum(resize_times) / len(resize_times) if resize_times else 0
-    avg_inference_time = sum(inference_times) / len(inference_times) if inference_times else 0
-    avg_io_time = sum(io_times) / len(io_times) if io_times else 0
-
-    # LaTeX template with escaped curly braces
-    latex_template = r"""
-\documentclass[a4paper,12pt]{{article}}
-\usepackage[utf8]{{inputenc}}
-\usepackage[T1]{{fontenc}}
-\usepackage{{geometry}}
-\geometry{{margin=1in}}
-\usepackage{{graphicx}}
-\usepackage{{booktabs}}
-\usepackage{{longtable}}
-\usepackage{{hyperref}}
-\usepackage{{xcolor}}
-\usepackage{{parskip}}
-\setlength{{\parskip}}{{0.5em}}
-\usepackage{{noto}}
-\graphicspath{{{{./captured_frames/}}}}
-
-\begin{{document}}
-
-% Title and project details
-\section*{{NHAI Drone Survey Analysis Report}}
-
-\subsection*{{Project Details}}
-\begin{{itemize}}
-    \item \textbf{{Project Name:}} NH-44 Delhi-Hyderabad Section (Package XYZ)
-    \item \textbf{{Highway Section:}} Km 100 to Km 150
-    \item \textbf{{State:}} Telangana
-    \item \textbf{{Region:}} South
-    \item \textbf{{Survey Date:}} \today
-    \item \textbf{{Drone Service Provider:}} ABC Drone Services Pvt. Ltd.
-    \item \textbf{{Technology Service Provider:}} XYZ AI Analytics Ltd.
-    \item \textbf{{Work Order Reference:}} Data Lake WO-\today-XYZ
-    \item \textbf{{Report Prepared By:}} Nagasurendra, Data Analyst
-    \item \textbf{{Report Date:}} \today
-\end{{itemize}}
-
-\section{{Introduction}}
-This report consolidates drone survey results for NH-44 (Km 100--150) under Operations \& Maintenance, per NHAI Policy Circular No. 18.98/2024, detecting potholes and cracks using YOLOv8 for Monthly Progress Report integration.
-
-\section{{Drone Survey Metadata}}
-\begin{{itemize}}
-    \item \textbf{{Drone Speed:}} 5 m/s
-    \item \textbf{{Drone Height:}} 60 m
-    \item \textbf{{Camera Sensor:}} RGB, 12 MP
-    \item \textbf{{Recording Type:}} JPEG, 90° nadir
-    \item \textbf{{Image Overlap:}} 85\%
-    \item \textbf{{Flight Pattern:}} Single lap, ROW centered
-    \item \textbf{{Geotagging:}} Enabled
-    \item \textbf{{Satellite Lock:}} 12 satellites
-    \item \textbf{{Terrain Follow Mode:}} Enabled
-\end{{itemize}}
-
-\section{{Quality Check Results}}
-\begin{{itemize}}
-    \item \textbf{{Resolution:}} 4000x3000 (12 MP)
-    \item \textbf{{Overlap:}} 85\%
-    \item \textbf{{Camera Angle:}} 90° nadir
-    \item \textbf{{Drone Speed:}} $\leq$ 5 m/s
-    \item \textbf{{Geotagging:}} 100\% compliant
-    \item \textbf{{QC Status:}} Passed
-\end{{itemize}}
-
-\section{{AI/ML Analytics}}
-\begin{{itemize}}
-    \item \textbf{{Total Frames Processed:}} {frame_count}
-    \item \textbf{{Detection Frames:}} {detection_frame_count} ({detection_percentage:.2f}\%)
-    \item \textbf{{Total Detections:}} {total_detections}
-    \item \textbf{{Breakdown:}}
-    \begin{{itemize}}
-        {items}
-    \end{{itemize}}
-    \item \textbf{{Processing Time:}} {total_time:.2f} seconds
-    \item \textbf{{Average Frame Time:}} {avg_frame_time:.2f} ms
-    \item \textbf{{Average Resize Time:}} {avg_resize_time:.2f} ms
-    \item \textbf{{Average Inference Time:}} {avg_inference_time:.2f} ms
-    \item \textbf{{Average I/O Time:}} {avg_io_time:.2f} ms
-    \item \textbf{{Timestamp:}} {timestamp_str}
-    \item \textbf{{Summary:}} Potholes and cracks detected in high-traffic segments.
-\end{{itemize}}
-
-\section{{Output File Structure}}
-\begin{{itemize}}
-    \item ZIP file contains:
-    \begin{{itemize}}
-        \item \texttt{{drone_analysis_report_{timestamp}.pdf}}: This report
-        \item \texttt{{outputs/processed_output.mp4}}: Processed video with annotations
-        \item \texttt{{outputs/chart_{timestamp}.png}}: Detection trend chart
-        \item \texttt{{outputs/map_{timestamp}.png}}: Issue locations map
-        \item \texttt{{captured_frames/detected_<frame>.jpg}}: Geotagged images for detected issues
-        \item \texttt{{flight_logs/flight_log_<frame>.csv}}: Flight logs matching image frames
-    \end{{itemize}}
-    \item \textbf{{Note:}} Images and logs share frame numbers (e.g., \texttt{{detected_000001.jpg}} corresponds to \texttt{{flight_log_000001.csv}}).
-\end{{itemize}}
-
-\section{{Geotagged Images}}
-\begin{{itemize}}
-    \item \textbf{{Total Images:}} {total_images}
-    \item \textbf{{Storage:}} Data Lake \texttt{{/project_xyz/images/{date_str}}}
-\end{{itemize}}
-
-\begin{{longtable}}{{c l c c c p{{4cm}}}}
-    \toprule
-    \textbf{{Frame}} & \textbf{{Issue Type}} & \textbf{{GPS (Lat, Lon)}} & \textbf{{Timestamp}} & \textbf{{Confidence}} & \textbf{{Image}} \\
-    \midrule
-    \endhead
-    {image_rows}
-    \bottomrule
-\end{{longtable}}
-
-\section{{Flight Logs}}
-\begin{{itemize}}
-    \item \textbf{{Total Logs:}} {total_logs}
-    \item \textbf{{Storage:}} Data Lake \texttt{{/project_xyz/flight_logs/{date_str}}}
-\end{{itemize}}
-
-\begin{{longtable}}{{c c c c c c c l}}
-    \toprule
-    \textbf{{Frame}} & \textbf{{Timestamp}} & \textbf{{Latitude}} & \textbf{{Longitude}} & \textbf{{Speed (m/s)}} & \textbf{{Satellites}} & \textbf{{Altitude (m)}} & \textbf{{Log Path}} \\
-    \midrule
-    \endhead
-    {log_rows}
-    \bottomrule
-\end{{longtable}}
-
-\section{{Processed Video}}
-\begin{{itemize}}
-    \item \textbf{{Path:}} \texttt{{outputs/processed_output.mp4}}
-    \item \textbf{{Frames:}} {output_frames}
-    \item \textbf{{FPS:}} {output_fps:.2f}
-    \item \textbf{{Duration:}} {output_duration:.2f} seconds
-\end{{itemize}}
-
-\section{{Visualizations}}
-\begin{{itemize}}
-    \item \textbf{{Detection Trend Chart:}} \texttt{{outputs/chart_{timestamp}.png}}
-    \item \textbf{{Issue Locations Map:}} \texttt{{outputs/map_{timestamp}.png}}
-\end{{itemize}}
-
-\section{{Processing Timestamps}}
-\begin{{itemize}}
-    \item \textbf{{Total Processing Time:}} {total_time:.2f} seconds
-    \item \textbf{{Log Entries (Last 10):}}
-    \begin{{itemize}}
-        {log_entries}
-    \end{{itemize}}
-\end{{itemize}}
-
-\section{{Stakeholder Validation}}
-\begin{{itemize}}
-    \item \textbf{{AE/IE Comments:}} [Pending]
-    \item \textbf{{PD/RO Comments:}} [Pending]
-\end{{itemize}}
-
-\section{{Recommendations}}
-\begin{{itemize}}
-    \item Repair potholes in high-traffic segments.
-    \item Seal cracks to prevent degradation.
-    \item Schedule follow-up survey.
-\end{{itemize}}
-
-\section{{Data Lake References}}
-\begin{{itemize}}
-    \item \textbf{{Images:}} \texttt{{/project_xyz/images/{date_str}}}
-    \item \textbf{{Flight Logs:}} \texttt{{/project_xyz/flight_logs/{date_str}}}
-    \item \textbf{{Video:}} \texttt{{/project_xyz/videos/processed_output_{date_str_no_dash}.mp4}}
-    \item \textbf{{DAMS Dashboard:}} \texttt{{/project_xyz/dams/{date_str}}}
-\end{{itemize}}
-
-\end{{document}}
-"""
-
-    # Format the LaTeX template
-    report_content = latex_template.format(
-        frame_count=frame_count,
-        detection_frame_count=detection_frame_count,
-        detection_percentage=(detection_frame_count / frame_count * 100) if frame_count > 0 else 0,
-        total_detections=metrics['total_detections'],
-        items="\n        ".join(items),
-        total_time=total_time,
-        avg_frame_time=avg_frame_time,
-        avg_resize_time=avg_resize_time,
-        avg_inference_time=avg_inference_time,
-        avg_io_time=avg_io_time,
-        timestamp_str=metrics.get('timestamp', 'N/A'),
-        timestamp=timestamp,
-        total_images=len(detected_issues),
-        total_logs=len(detected_issues),
-        date_str=datetime.now().strftime('%Y-%m-%d'),
-        date_str_no_dash=datetime.now().strftime('%Y%m%d'),
-        image_rows="\n    ".join(image_rows),
-        log_rows="\n    ".join(log_rows),
-        log_entries="\n        ".join(log_entries_str)
-    )
+        report_content.append(rf"\item {entry}")
+    report_content.extend([
+        r"\end{itemize}",
+        r"\section{Stakeholder Validation}",
+        r"\begin{itemize}",
+        r"\item \textbf{AE/IE Comments}: Pending",
+        r"\item \textbf{PD/RO Comments}: Pending",
+        r"\end{itemize}",
+        r"\section{Recommendations}",
+        r"\begin{itemize}",
+        r"\item Repair potholes in high-traffic segments.",
+        r"\item Seal cracks to prevent degradation.",
+        r"\item Schedule follow-up survey.",
+        r"\end{itemize}",
+        r"\section{Data Lake References}",
+        rf"Images: \texttt{{/project\_xyz/images/{datetime.now().strftime('%Y-%m-%d')}}}\par",
+        rf"Flight Logs: \texttt{{/project\_xyz/flight\_logs/{datetime.now().strftime('%Y-%m-%d')}}}\par",
+        rf"Video: \texttt{{/project\_xyz/videos/processed\_output_{datetime.now().strftime('%Y%m%d')}.mp4}}\par",
+        rf"DAMS Dashboard: \texttt{{/project\_xyz/dams/{datetime.now().strftime('%Y-%m-%d')}}}\par",
+        r"\end{document}"
+    ])
 
     try:
-        with open(report_path, 'w') as f:
-            f.write(report_content)
-        log_entries.append(f"Report saved: {report_path}")
+        # Writing LaTeX file
+        with open(tex_path, 'w') as f:
+            f.write("\n".join(report_content))
+        log_entries.append(f"LaTeX report saved: {tex_path}")
+
+        # Compiling LaTeX to PDF using latexmk
+        import subprocess
+        subprocess.run(["latexmk", "-pdf", "-interaction=nonstopmode", tex_path], cwd=OUTPUT_DIR, check=True)
+        log_entries.append(f"PDF report generated: {report_path}")
         return report_path
     except Exception as e:
-        log_entries.append(f"Error: Failed to save report: {str(e)}")
+        log_entries.append(f"Error: Failed to generate report: {str(e)}")
         return ""
 
 def process_video(video, resize_width=4000, resize_height=3000, frame_skip=5):