Update app.py

app.py

@@ -5,10 +5,11 @@ import time
 import json
 import random
 import logging
+import numpy as np  # Moved to top to fix NameError
 from datetime import datetime
 from collections import Counter
 from typing import Any, Dict, List, Optional, Tuple
-import numpy as np
+import matplotlib.pyplot as plt  # Added for chart generation
 
 # Suppress Ultralytics warning by setting a writable config directory
 os.environ["YOLO_CONFIG_DIR"] = "/tmp/Ultralytics"
@@ -144,10 +145,86 @@ def set_active_service(
     logging.info("No service category enabled.")
     return None, "No Service Category Enabled"
 
+def generate_crack_trend_chart() -> Optional[plt.Figure]:
+    """
+    Generate a line chart for crack trend over time using Matplotlib.
+
+    Returns:
+        Optional[plt.Figure]: Matplotlib figure object or None if no data.
+    """
+    if not crack_counts:
+        return None
+
+    data = crack_counts[-50:]
+    labels = list(range(len(data)))
+
+    fig, ax = plt.subplots(figsize=(6, 4))
+    ax.plot(labels, data, color="#FF6347", label="Cracks Over Time")
+    ax.set_title("Crack Trend (Operations Maintenance)")
+    ax.set_xlabel("Frame")
+    ax.set_ylabel("Count")
+    ax.set_ylim(bottom=0)
+    ax.grid(True)
+    ax.legend()
+    plt.tight_layout()
+    return fig
+
+def generate_crack_severity_chart() -> Optional[plt.Figure]:
+    """
+    Generate a pie chart for crack severity distribution using Matplotlib.
+
+    Returns:
+        Optional[plt.Figure]: Matplotlib figure object or None if no data.
+    """
+    if not crack_severity_all:
+        return None
+
+    count = Counter(crack_severity_all[-200:])
+    labels = list(count.keys())
+    sizes = list(count.values())
+
+    fig, ax = plt.subplots(figsize=(6, 4))
+    ax.pie(
+        sizes,
+        labels=labels,
+        colors=["#FF6347", "#4682B4", "#FFD700"],
+        autopct="%1.1f%%",
+        startangle=90
+    )
+    ax.set_title("Crack Severity (Operations Maintenance)")
+    plt.tight_layout()
+    return fig
+
+def generate_severity_distribution_chart() -> Optional[plt.Figure]:
+    """
+    Generate a bar chart for crack severity distribution using Matplotlib.
+
+    Returns:
+        Optional[plt.Figure]: Matplotlib figure object or None if no data.
+    """
+    if not crack_severity_all:
+        return None
+
+    count = Counter(crack_severity_all[-200:])
+    labels = list(count.keys())
+    sizes = list(count.values())
+
+    fig, ax = plt.subplots(figsize=(6, 4))
+    ax.bar(labels, sizes, color=["#FF6347", "#4682B4", "#FFD700"])
+    ax.set_title("Severity Distribution (Operations Maintenance)")
+    ax.set_xlabel("Severity")
+    ax.set_ylabel("Count")
+    ax.set_ylim(bottom=0)
+    plt.tight_layout()
+    return fig
+
 def monitor_feed() -> Tuple[
     Optional[np.ndarray],
     str,
     str,
+    Optional[plt.Figure],
+    Optional[plt.Figure],
+    Optional[plt.Figure],
     List[str]
 ]:
     """
@@ -158,6 +235,9 @@ def monitor_feed() -> Tuple[
             - Processed frame (numpy array or None).
             - Detection metrics (JSON string with crack trend and severity data).
             - Recent logs (string).
+            - Crack trend chart (Matplotlib figure or None).
+            - Crack severity chart (Matplotlib figure or None).
+            - Severity distribution chart (Matplotlib figure or None).
             - List of captured image paths.
     """
     global paused, frame_count, last_frame, last_detections, last_timestamp
@@ -170,6 +250,9 @@ def monitor_feed() -> Tuple[
             None,
             json.dumps({"error": "Video not loaded. Please upload a video file."}, indent=2),
             "\n".join(log_entries[-10:]),
+            None,
+            None,
+            None,
             last_detected_images
         )
 
@@ -188,6 +271,9 @@ def monitor_feed() -> Tuple[
                 None,
                 json.dumps(last_detections, indent=2),
                 "\n".join(log_entries[-10:]),
+                None,
+                None,
+                None,
                 last_detected_images
             )
 
@@ -300,9 +386,9 @@ def monitor_feed() -> Tuple[
         last_frame = frame.copy()
         last_detections = metrics
 
-        # Track cracks for metrics (for Operations Maintenance and Road Safety)
-        crack_detected = len([item for item in all_detected_items if item.get("type") == "crack"]) if active_service in ["operations_maintenance", "road_safety"] else 0
-        if active_service in ["operations_maintenance", "road_safety"]:
+        # Track cracks for metrics (for Operations Maintenance only)
+        crack_detected = len([item for item in all_detected_items if item.get("type") == "crack"]) if active_service == "operations_maintenance" else 0
+        if active_service == "operations_maintenance":
             crack_severity_all.extend([
                 item["severity"]
                 for item in all_detected_items
@@ -310,7 +396,7 @@ def monitor_feed() -> Tuple[
             ])
 
         # Add crack trend and severity to metrics
-        if active_service in ["operations_maintenance", "road_safety"]:
+        if active_service == "operations_maintenance":
             last_detections["crack_count_last_50_frames"] = crack_counts[-50:] if crack_counts else []
             severity_counts = Counter(crack_severity_all[-200:]) if crack_severity_all else {}
             last_detections["crack_severity_distribution"] = dict(severity_counts)
@@ -336,10 +422,22 @@ def monitor_feed() -> Tuple[
     cv2.putText(frame, f"Frame: {frame_count}", (10, 25), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
     cv2.putText(frame, f"{last_timestamp}", (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
 
+    # Generate charts for Operations Maintenance only
+    line_chart = None
+    pie_chart = None
+    bar_chart = None
+    if active_service == "operations_maintenance":
+        line_chart = generate_crack_trend_chart()
+        pie_chart = generate_crack_severity_chart()
+        bar_chart = generate_severity_distribution_chart()
+
     return (
         frame[:, :, ::-1],  # Convert BGR to RGB for Gradio
         json.dumps(last_detections, indent=2),
         "\n".join(log_entries[-10:]),
+        line_chart,
+        pie_chart,
+        bar_chart,
         last_detected_images
     )
 
@@ -394,7 +492,12 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="green"))
         with gr.Column(scale=2):
             logs_output = gr.Textbox(label="Live Logs", lines=8, interactive=False)
         with gr.Column(scale=1):
-            captured_images = gr.Gallery(label="Detected Frames (Last 100+)", columns=4, rows=25, height="auto")
+            chart_output = gr.Plot(label="Crack Trend (Operations Maintenance Only)")
+            pie_output = gr.Plot(label="Crack Severity (Operations Maintenance Only)")
+            bar_output = gr.Plot(label="Severity Distribution (Operations Maintenance Only)")
+
+    with gr.Row():
+        captured_images = gr.Gallery(label="Detected Frames (Last 100+)", columns=4, rows=25, height="auto")
 
     with gr.Row():
         pause_btn = gr.Button("⏸️ Pause", variant="secondary")
@@ -478,16 +581,16 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="green"))
         """Continuous loop to stream video and process frames."""
         while True:
             if not video_loaded:
-                yield None, json.dumps({"error": "Video not loaded. Please upload a video file."}, indent=2), "\n".join(log_entries[-10:]), last_detected_images
+                yield None, json.dumps({"error": "Video not loaded. Please upload a video file."}, indent=2), "\n".join(log_entries[-10:]), None, None, None, last_detected_images
             else:
-                frame, detections, logs, captured = monitor_feed()
+                frame, detections, logs, line_chart, pie_chart, bar_chart, captured = monitor_feed()
                 if frame is None:
-                    yield None, detections, logs, captured
+                    yield None, detections, logs, None, None, None, captured
                 else:
-                    yield frame, detections, logs, captured
+                    yield frame, detections, logs, line_chart, pie_chart, bar_chart, captured
             time.sleep(frame_rate)
 
-    app.load(streaming_loop, outputs=[video_output, detections_output, logs_output, captured_images])
+    app.load(streaming_loop, outputs=[video_output, detections_output, logs_output, chart_output, pie_output, bar_output, captured_images])
 
 if __name__ == "__main__":
     app.launch(share=False)