Combine classification objects by event

frigate/data_processing/real_time/custom_classification.py

@@ -151,6 +151,7 @@ class CustomStateClassificationProcessor(RealTimeProcessorApi):
             write_classification_attempt(
                 self.train_dir,
                 cv2.cvtColor(frame, cv2.COLOR_RGB2BGR),
+                "none-none",
                 now,
                 "unknown",
                 0.0,
@@ -171,6 +172,7 @@ class CustomStateClassificationProcessor(RealTimeProcessorApi):
         write_classification_attempt(
             self.train_dir,
             cv2.cvtColor(frame, cv2.COLOR_RGB2BGR),
+            "none-none",
             now,
             self.labelmap[best_id],
             score,
@@ -293,6 +295,7 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
             write_classification_attempt(
                 self.train_dir,
                 cv2.cvtColor(crop, cv2.COLOR_RGB2BGR),
+                obj_data["id"],
                 now,
                 "unknown",
                 0.0,
@@ -314,6 +317,7 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
         write_classification_attempt(
             self.train_dir,
             cv2.cvtColor(crop, cv2.COLOR_RGB2BGR),
+            obj_data["id"],
             now,
             self.labelmap[best_id],
             score,
@@ -372,6 +376,7 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
 def write_classification_attempt(
     folder: str,
     frame: np.ndarray,
+    event_id: str,
     timestamp: float,
     label: str,
     score: float,
@@ -379,7 +384,7 @@ def write_classification_attempt(
     if "-" in label:
         label = label.replace("-", "_")
 
-    file = os.path.join(folder, f"{timestamp}-{label}-{score}.webp")
+    file = os.path.join(folder, f"{event_id}-{timestamp}-{label}-{score}.webp")
     os.makedirs(folder, exist_ok=True)
     cv2.imwrite(file, frame)
 

web/src/views/classification/ModelTrainingView.tsx

@@ -1,4 +1,3 @@
-import { baseUrl } from "@/api/baseUrl";
 import TextEntryDialog from "@/components/overlay/dialog/TextEntryDialog";
 import { Button, buttonVariants } from "@/components/ui/button";
 import {
@@ -61,7 +60,11 @@ import { MdAutoFixHigh } from "react-icons/md";
 import TrainFilterDialog from "@/components/overlay/dialog/TrainFilterDialog";
 import useApiFilter from "@/hooks/use-api-filter";
 import { ClassificationItemData, TrainFilter } from "@/types/classification";
-import { ClassificationCard } from "@/components/card/ClassificationCard";
+import {
+  ClassificationCard,
+  GroupedClassificationCard,
+} from "@/components/card/ClassificationCard";
+import { Event } from "@/types/event";
 
 type ModelTrainingViewProps = {
   model: CustomClassificationModelConfig;
@@ -687,11 +690,12 @@ function TrainGrid({
       trainImages
         .map((raw) => {
           const parts = raw.replaceAll(".webp", "").split("-");
-          const rawScore = Number.parseFloat(parts[2]);
+          const rawScore = Number.parseFloat(parts[4]);
           return {
             filename: raw,
             filepath: `clips/${model.name}/train/${raw}`,
-            timestamp: Number.parseFloat(parts[0]),
+            timestamp: Number.parseFloat(parts[2]),
+            eventId: `${parts[0]}-${parts[1]}`,
             name: parts[1],
             score: rawScore,
           };
@@ -740,7 +744,18 @@ function TrainGrid({
     );
   }
 
-  return <div />;
+  return (
+    <ObjectTrainGrid
+      model={model}
+      contentRef={contentRef}
+      classes={classes}
+      trainData={trainData}
+      selectedImages={selectedImages}
+      onClickImages={onClickImages}
+      onRefresh={onRefresh}
+      onDelete={onDelete}
+    />
+  );
 }
 
 type StateTrainGridProps = {
@@ -841,6 +856,32 @@ function ObjectTrainGrid({
 }: ObjectTrainGridProps) {
   const { t } = useTranslation(["views/classificationModel"]);
 
+  // item data
+
+  const groups = useMemo(() => {
+    const groups: { [eventId: string]: ClassificationItemData[] } = {};
+
+    trainData
+      ?.sort((a, b) => a.eventId!.localeCompare(b.eventId!))
+      .reverse()
+      .forEach((data) => {
+        if (groups[data.eventId!]) {
+          groups[data.eventId!].push(data);
+        } else {
+          groups[data.eventId!] = [data];
+        }
+      });
+
+    return groups;
+  }, [trainData]);
+
+  const eventIdsQuery = useMemo(() => Object.keys(groups).join(","), [groups]);
+
+  const { data: events } = useSWR<Event[]>([
+    "event_ids",
+    { ids: eventIdsQuery },
+  ]);
+
   const threshold = useMemo(() => {
     return {
       recognition: model.threshold,
@@ -851,22 +892,23 @@ function ObjectTrainGrid({
   return (
     <div
       ref={contentRef}
-      className={cn(
+      className="scrollbar-container flex flex-wrap gap-2 overflow-y-scroll p-1"
-        "scrollbar-container flex flex-wrap gap-2 overflow-y-auto p-2",
-        isMobile && "justify-center",
-      )}
     >
-      {trainData?.map((data) => (
+      {Object.entries(groups).map(([key, group]) => {
-        <ClassificationCard
+        const event = events?.find((ev) => ev.id == key);
-          className="w-60 gap-2 rounded-lg bg-card p-2"
+        return (
-          imgClassName="size-auto"
+          <GroupedClassificationCard
-          data={data}
+            key={key}
+            group={group}
+            event={event}
             threshold={threshold}
-          selected={selectedImages.includes(data.filename)}
+            selectedItems={selectedImages}
             i18nLibrary="views/classificationModel"
-          showArea={false}
+            onClick={() => {}}
-          onClick={(data, meta) => onClickImages([data.filename], meta)}
+            onSelectEvent={() => {}}
           >
+            {(data) => (
+              <>
                 <ClassificationSelectionDialog
                   classes={classes}
                   modelName={model.name}
@@ -889,8 +931,11 @@ function ObjectTrainGrid({
                     {t("button.deleteClassificationAttempts")}
                   </TooltipContent>
                 </Tooltip>
-        </ClassificationCard>
+              </>
-      ))}
+            )}
+          </GroupedClassificationCard>
+        );
+      })}
     </div>
   );
 }