gemini model integration

src/app/(modules)/upload/page.tsx

@@ -31,6 +31,7 @@ const DETECTION_METHODS = [
   // { value: 'yoloe_trained_vl', label: 'YOLOE With Vision Language Model' },
   { value: 'culvert_detection', label: 'Culvert Detection' },
   { value: 'combined', label: 'Road Defect Detection' },
+  { value: 'gemini_video', label: 'Gemini AI Analysis' },
 ] as const;
 
 export default function UploadPage() {

src/components/video-player-section.tsx

@@ -86,13 +86,70 @@ export default function VideoPlayerSection({
   // Logs Reducer
   const [logs, dispatchLogs] = useReducer(logsReducer, []);
 
+  // Memoize a unified data object with frames generated if missing
+  const normalizedData = useMemo(() => {
+    if (data.frames && Array.isArray(data.frames) && data.frames.length > 0) {
+      return data;
+    }
+
+    // Synthesize frames from lists if not present (like in gemini_video)
+    const framesMap = new Map<number, any>();
+    
+    // Sort all detections by their first_detected_frame
+    const allDetections: any[] = [];
+    enabledTypes.forEach(type => {
+      const list = (data as any)[type.listKey];
+      if (list && Array.isArray(list)) {
+        list.forEach((item: any) => {
+          allDetections.push({ ...item, _detType: type.id });
+        });
+      }
+    });
+
+    allDetections.sort((a, b) => (a.first_detected_frame || 0) - (b.first_detected_frame || 0));
+
+    // Current counts for sticky stats
+    const currentCounts: Record<string, number> = {};
+    enabledTypes.forEach(t => { currentCounts[t.frameCountKey] = 0; });
+
+    allDetections.forEach(det => {
+      const frameId = det.first_detected_frame || det.frame_number || 0;
+      
+      if (!framesMap.has(frameId)) {
+        framesMap.set(frameId, { frame_id: frameId, detections: [] });
+      }
+      
+      const frameData = framesMap.get(frameId);
+      
+      // Update cumulative counts
+      const typeConfig = enabledTypes.find(t => t.id === det._detType);
+      if (typeConfig) {
+        currentCounts[typeConfig.frameCountKey] = (currentCounts[typeConfig.frameCountKey] || 0) + 1;
+      }
+      
+      const countCopy = { ...currentCounts };
+      
+      frameData.detections.push({
+        ...det,
+        type: det.type || det._detType,
+        detection_id: det.detection_id || det.id,
+        count: countCopy
+      });
+    });
+
+    return {
+      ...data,
+      frames: Array.from(framesMap.values()).sort((a, b) => (a.frame_id || 0) - (b.frame_id || 0))
+    };
+  }, [data, enabledTypes]);
+
   // Custom Hooks
-  const gpsMap = useGpsMap(data);
+  const gpsMap = useGpsMap(normalizedData);
   const { getNearestDetections, sortedDetectionIndices } = useFrameDetectionMap(
-    data,
+    normalizedData,
     detectionType,
   );
-  const { getStickyCounts, sortedFrameIndices } = useCumulativeCounts(data.frames);
+  const { getStickyCounts, sortedFrameIndices } = useCumulativeCounts(normalizedData.frames || []);
 
   // Memoized video URL
   const videoUrl = useMemo(() => {

src/constants/detectionModeConfig.ts

@@ -136,6 +136,20 @@ export const DETECTION_MODES: Record<string, DetectionModeConfig> = {
     label: 'Culvert Detection',
     enabledTypes: ['good_culvert', 'defective_culvert'],
   },
+  gemini_video: {
+    id: 'gemini_video',
+    label: 'Gemini AI Analysis',
+    enabledTypes: [
+      'pothole',
+      'defected_sign_board',
+      'road_crack',
+      'damaged_road_marking',
+      'good_sign_board',
+      'drain_issue',
+      'good_culvert',
+      'defective_culvert',
+    ],
+  },
 };
 
 // Fallback config for unknown modes

src/types/detection.ts

@@ -22,7 +22,8 @@ export type DetectionType =
   | 'yolo_vl'
   | 'sam3'
   | 'yoloe'
-  | 'yoloe_trained_vl';
+  | 'yoloe_trained_vl'
+  | 'gemini_video';
 
 export interface DetectionListItem {
   detection_id?: number;