Classification Model UI (#18571)

* Setup basic training structure

* Build out route

* Handle model configs

* Add image fetch APIs

* Implement model training screen with dataset selection

* Implement viewing of training images

* Adjust directories

* Implement viewing of images

* Add support for deleting images

* Implement full deletion

* Implement classification model training

* Improve naming

* More renaming

* Improve layout

* Reduce logging

* Cleanup

frigate/api/classification.py

@@ -21,7 +21,7 @@ from frigate.api.defs.request.classification_body import (
 from frigate.api.defs.tags import Tags
 from frigate.config import FrigateConfig
 from frigate.config.camera import DetectConfig
-from frigate.const import FACE_DIR, MODEL_CACHE_DIR
+from frigate.const import CLIPS_DIR, FACE_DIR
 from frigate.embeddings import EmbeddingsContext
 from frigate.models import Event
 from frigate.util.classification import train_classification_model
@@ -431,6 +431,50 @@ def transcribe_audio(request: Request, body: AudioTranscriptionBody):
 # custom classification training
 
 
+@router.get("/classification/{name}/dataset")
+def get_classification_dataset(name: str):
+    dataset_dict: dict[str, list[str]] = {}
+
+    dataset_dir = os.path.join(CLIPS_DIR, sanitize_filename(name), "dataset")
+
+    if not os.path.exists(dataset_dir):
+        return JSONResponse(status_code=200, content={})
+
+    for name in os.listdir(dataset_dir):
+        category_dir = os.path.join(dataset_dir, name)
+
+        if not os.path.isdir(category_dir):
+            continue
+
+        dataset_dict[name] = []
+
+        for file in filter(
+            lambda f: (f.lower().endswith((".webp", ".png", ".jpg", ".jpeg"))),
+            os.listdir(category_dir),
+        ):
+            dataset_dict[name].append(file)
+
+    return JSONResponse(status_code=200, content=dataset_dict)
+
+
+@router.get("/classification/{name}/train")
+def get_classification_images(name: str):
+    train_dir = os.path.join(CLIPS_DIR, sanitize_filename(name), "train")
+
+    if not os.path.exists(train_dir):
+        return JSONResponse(status_code=200, content=[])
+
+    return JSONResponse(
+        status_code=200,
+        content=list(
+            filter(
+                lambda f: (f.lower().endswith((".webp", ".png", ".jpg", ".jpeg"))),
+                os.listdir(train_dir),
+            )
+        ),
+    )
+
+
 @router.post("/classification/{name}/train")
 async def train_configured_model(
     request: Request, name: str, background_tasks: BackgroundTasks
@@ -448,10 +492,131 @@ async def train_configured_model(
             status_code=404,
         )
 
-    background_tasks.add_task(
-        train_classification_model, os.path.join(MODEL_CACHE_DIR, name)
-    )
+    background_tasks.add_task(train_classification_model, name)
     return JSONResponse(
         content={"success": True, "message": "Started classification model training."},
         status_code=200,
     )
+
+
+@router.post(
+    "/classification/{name}/dataset/{category}/delete",
+    dependencies=[Depends(require_role(["admin"]))],
+)
+def delete_classification_dataset_images(
+    request: Request, name: str, category: str, body: dict = None
+):
+    config: FrigateConfig = request.app.frigate_config
+
+    if name not in config.classification.custom:
+        return JSONResponse(
+            content=(
+                {
+                    "success": False,
+                    "message": f"{name} is not a known classification model.",
+                }
+            ),
+            status_code=404,
+        )
+
+    json: dict[str, Any] = body or {}
+    list_of_ids = json.get("ids", "")
+    folder = os.path.join(
+        CLIPS_DIR, sanitize_filename(name), "dataset", sanitize_filename(category)
+    )
+
+    for id in list_of_ids:
+        file_path = os.path.join(folder, id)
+
+        if os.path.isfile(file_path):
+            os.unlink(file_path)
+
+    return JSONResponse(
+        content=({"success": True, "message": "Successfully deleted faces."}),
+        status_code=200,
+    )
+
+
+@router.post(
+    "/classification/{name}/dataset/categorize",
+    dependencies=[Depends(require_role(["admin"]))],
+)
+def categorize_classification_image(request: Request, name: str, body: dict = None):
+    config: FrigateConfig = request.app.frigate_config
+
+    if name not in config.classification.custom:
+        return JSONResponse(
+            content=(
+                {
+                    "success": False,
+                    "message": f"{name} is not a known classification model.",
+                }
+            ),
+            status_code=404,
+        )
+
+    json: dict[str, Any] = body or {}
+    category = sanitize_filename(json.get("category", ""))
+    training_file_name = sanitize_filename(json.get("training_file", ""))
+    training_file = os.path.join(CLIPS_DIR, name, "train", training_file_name)
+
+    if training_file_name and not os.path.isfile(training_file):
+        return JSONResponse(
+            content=(
+                {
+                    "success": False,
+                    "message": f"Invalid filename or no file exists: {training_file_name}",
+                }
+            ),
+            status_code=404,
+        )
+
+    new_name = f"{category}-{datetime.datetime.now().timestamp()}.png"
+    new_file_folder = os.path.join(CLIPS_DIR, name, "dataset", category)
+
+    if not os.path.exists(new_file_folder):
+        os.mkdir(new_file_folder)
+
+    # use opencv because webp images can not be used to train
+    img = cv2.imread(training_file)
+    cv2.imwrite(os.path.join(new_file_folder, new_name), img)
+    os.unlink(training_file)
+
+    return JSONResponse(
+        content=({"success": True, "message": "Successfully deleted faces."}),
+        status_code=200,
+    )
+
+
+@router.post(
+    "/classification/{name}/train/delete",
+    dependencies=[Depends(require_role(["admin"]))],
+)
+def delete_classification_train_images(request: Request, name: str, body: dict = None):
+    config: FrigateConfig = request.app.frigate_config
+
+    if name not in config.classification.custom:
+        return JSONResponse(
+            content=(
+                {
+                    "success": False,
+                    "message": f"{name} is not a known classification model.",
+                }
+            ),
+            status_code=404,
+        )
+
+    json: dict[str, Any] = body or {}
+    list_of_ids = json.get("ids", "")
+    folder = os.path.join(CLIPS_DIR, sanitize_filename(name), "train")
+
+    for id in list_of_ids:
+        file_path = os.path.join(folder, id)
+
+        if os.path.isfile(file_path):
+            os.unlink(file_path)
+
+    return JSONResponse(
+        content=({"success": True, "message": "Successfully deleted faces."}),
+        status_code=200,
+    )

frigate/data_processing/real_time/custom_classification.py

@@ -42,7 +42,7 @@ class CustomStateClassificationProcessor(RealTimeProcessorApi):
         self.model_config = model_config
         self.requestor = requestor
         self.model_dir = os.path.join(MODEL_CACHE_DIR, self.model_config.name)
-        self.train_dir = os.path.join(CLIPS_DIR, self.model_config.name)
+        self.train_dir = os.path.join(CLIPS_DIR, self.model_config.name, "train")
         self.interpreter: Interpreter = None
         self.tensor_input_details: dict[str, Any] = None
         self.tensor_output_details: dict[str, Any] = None

frigate/util/classification.py

@@ -1,5 +1,6 @@
 """Util for classification models."""
 
+import logging
 import os
 
 import cv2
@@ -9,6 +10,8 @@ from tensorflow.keras import layers, models, optimizers
 from tensorflow.keras.applications import MobileNetV2
 from tensorflow.keras.preprocessing.image import ImageDataGenerator
 
+from frigate.const import CLIPS_DIR, MODEL_CACHE_DIR
+
 BATCH_SIZE = 16
 EPOCHS = 50
 LEARNING_RATE = 0.001
@@ -35,9 +38,10 @@ def generate_representative_dataset_factory(dataset_dir: str):
 
 
 @staticmethod
-def train_classification_model(model_dir: str) -> bool:
+def train_classification_model(model_name: str) -> bool:
     """Train a classification model."""
-    dataset_dir = os.path.join(model_dir, "dataset")
+    dataset_dir = os.path.join(CLIPS_DIR, model_name, "dataset")
+    model_dir = os.path.join(MODEL_CACHE_DIR, model_name)
     num_classes = len(
         [
             d
@@ -46,6 +50,8 @@ def train_classification_model(model_dir: str) -> bool:
         ]
     )
 
+    tf.get_logger().setLevel(logging.ERROR)
+
     # Start with imagenet base model with 35% of channels in each layer
     base_model = MobileNetV2(
         input_shape=(224, 224, 3),

web/public/locales/en/views/classificationModel.json

@@ -0,0 +1,49 @@
+{
+  "button": {
+    "deleteClassificationAttempts": "Delete Classification Images",
+    "renameCategory": "Rename Class",
+    "deleteCategory": "Delete Class",
+    "deleteImages": "Delete Images"
+  },
+  "toast": {
+    "success": {
+      "deletedCategory": "Deleted Class",
+      "deletedImage": "Deleted Images",
+      "categorizedImage": "Successfully Classified Image"
+    },
+    "error": {
+      "deleteImageFailed": "Failed to delete: {{errorMessage}}",
+      "deleteCategoryFailed": "Failed to delete class: {{errorMessage}}",
+      "categorizeFailed": "Failed to categorize image: {{errorMessage}}"
+    }
+  },
+  "deleteCategory": {
+    "title": "Delete Class",
+    "desc": "Are you sure you want to delete the class {{name}}? This will permanently delete all associated images and require re-training the model."
+  },
+  "deleteDatasetImages": {
+    "title": "Delete Dataset Images",
+    "desc": "Are you sure you want to delete {{count}} images from {{dataset}}? This action cannot be undone and will require re-training the model."
+  },
+  "deleteTrainImages": {
+    "title": "Delete Train Images",
+    "desc": "Are you sure you want to delete {{count}} images? This action cannot be undone."
+  },
+  "renameCategory": {
+    "title": "Rename Class",
+    "desc": "Enter a new name for {{name}}. You will be required to retrain the model for the name change to take affect."
+  },
+  "description": {
+    "invalidName": "Invalid name. Names can only include letters, numbers, spaces, apostrophes, underscores, and hyphens."
+  },
+  "train": {
+    "title": "Train",
+    "aria": "Select Train"
+  },
+  "categories": "Classes",
+  "createCategory": {
+    "new": "Create New Class"
+  },
+  "categorizeImageAs": "Classify Image As:",
+  "categorizeImage": "Classify Image"
+}

web/src/App.tsx

@@ -24,6 +24,7 @@ const System = lazy(() => import("@/pages/System"));
 const Settings = lazy(() => import("@/pages/Settings"));
 const UIPlayground = lazy(() => import("@/pages/UIPlayground"));
 const FaceLibrary = lazy(() => import("@/pages/FaceLibrary"));
+const Classification = lazy(() => import("@/pages/ClassificationModel"));
 const Logs = lazy(() => import("@/pages/Logs"));
 const AccessDenied = lazy(() => import("@/pages/AccessDenied"));
 
@@ -76,6 +77,7 @@ function DefaultAppView() {
               <Route path="/config" element={<ConfigEditor />} />
               <Route path="/logs" element={<Logs />} />
               <Route path="/faces" element={<FaceLibrary />} />
+              <Route path="/classification" element={<Classification />} />
               <Route path="/playground" element={<UIPlayground />} />
             </Route>
             <Route path="/unauthorized" element={<AccessDenied />} />

web/src/components/overlay/ClassificationSelectionDialog.tsx

@@ -0,0 +1,155 @@
+import {
+  Drawer,
+  DrawerClose,
+  DrawerContent,
+  DrawerDescription,
+  DrawerHeader,
+  DrawerTitle,
+  DrawerTrigger,
+} from "@/components/ui/drawer";
+import {
+  DropdownMenu,
+  DropdownMenuContent,
+  DropdownMenuItem,
+  DropdownMenuLabel,
+  DropdownMenuTrigger,
+} from "@/components/ui/dropdown-menu";
+import {
+  Tooltip,
+  TooltipContent,
+  TooltipTrigger,
+} from "@/components/ui/tooltip";
+import { isDesktop, isMobile } from "react-device-detect";
+import { LuPlus } from "react-icons/lu";
+import { useTranslation } from "react-i18next";
+import { cn } from "@/lib/utils";
+import React, { ReactNode, useCallback, useMemo, useState } from "react";
+import TextEntryDialog from "./dialog/TextEntryDialog";
+import { Button } from "../ui/button";
+import { MdCategory } from "react-icons/md";
+import axios from "axios";
+import { toast } from "sonner";
+
+type ClassificationSelectionDialogProps = {
+  className?: string;
+  classes: string[];
+  modelName: string;
+  image: string;
+  onRefresh: () => void;
+  children: ReactNode;
+};
+export default function ClassificationSelectionDialog({
+  className,
+  classes,
+  modelName,
+  image,
+  onRefresh,
+  children,
+}: ClassificationSelectionDialogProps) {
+  const { t } = useTranslation(["views/classificationModel"]);
+
+  const onCategorizeImage = useCallback(
+    (category: string) => {
+      axios
+        .post(`/classification/${modelName}/dataset/categorize`, {
+          category,
+          training_file: image,
+        })
+        .then((resp) => {
+          if (resp.status == 200) {
+            toast.success(t("toast.success.categorizedImage"), {
+              position: "top-center",
+            });
+            onRefresh();
+          }
+        })
+        .catch((error) => {
+          const errorMessage =
+            error.response?.data?.message ||
+            error.response?.data?.detail ||
+            "Unknown error";
+          toast.error(t("toast.error.categorizeFailed", { errorMessage }), {
+            position: "top-center",
+          });
+        });
+    },
+    [modelName, image, onRefresh, t],
+  );
+
+  const isChildButton = useMemo(
+    () => React.isValidElement(children) && children.type === Button,
+    [children],
+  );
+
+  // control
+  const [newFace, setNewFace] = useState(false);
+
+  // components
+  const Selector = isDesktop ? DropdownMenu : Drawer;
+  const SelectorTrigger = isDesktop ? DropdownMenuTrigger : DrawerTrigger;
+  const SelectorContent = isDesktop ? DropdownMenuContent : DrawerContent;
+  const SelectorItem = isDesktop
+    ? DropdownMenuItem
+    : (props: React.HTMLAttributes<HTMLDivElement>) => (
+        <DrawerClose asChild>
+          <div {...props} className={cn(props.className, "my-2")} />
+        </DrawerClose>
+      );
+
+  return (
+    <div className={className ?? ""}>
+      {newFace && (
+        <TextEntryDialog
+          open={true}
+          setOpen={setNewFace}
+          title={t("createCategory.new")}
+          onSave={(newCat) => onCategorizeImage(newCat)}
+        />
+      )}
+
+      <Tooltip>
+        <Selector>
+          <SelectorTrigger asChild>
+            <TooltipTrigger asChild={isChildButton}>{children}</TooltipTrigger>
+          </SelectorTrigger>
+          <SelectorContent
+            className={cn("", isMobile && "mx-1 gap-2 rounded-t-2xl px-4")}
+          >
+            {isMobile && (
+              <DrawerHeader className="sr-only">
+                <DrawerTitle>Details</DrawerTitle>
+                <DrawerDescription>Details</DrawerDescription>
+              </DrawerHeader>
+            )}
+            <DropdownMenuLabel>{t("categorizeImageAs")}</DropdownMenuLabel>
+            <div
+              className={cn(
+                "flex max-h-[40dvh] flex-col overflow-y-auto",
+                isMobile && "gap-2 pb-4",
+              )}
+            >
+              <SelectorItem
+                className="flex cursor-pointer gap-2 smart-capitalize"
+                onClick={() => setNewFace(true)}
+              >
+                <LuPlus />
+                {t("createCategory.new")}
+              </SelectorItem>
+              {classes.sort().map((category) => (
+                <SelectorItem
+                  key={category}
+                  className="flex cursor-pointer gap-2 smart-capitalize"
+                  onClick={() => onCategorizeImage(category)}
+                >
+                  <MdCategory />
+                  {category}
+                </SelectorItem>
+              ))}
+            </div>
+          </SelectorContent>
+        </Selector>
+        <TooltipContent>{t("categorizeImage")}</TooltipContent>
+      </Tooltip>
+    </div>
+  );
+}

web/src/hooks/use-navigation.ts

@@ -6,7 +6,7 @@ import { isDesktop } from "react-device-detect";
 import { FaCompactDisc, FaVideo } from "react-icons/fa";
 import { IoSearch } from "react-icons/io5";
 import { LuConstruction } from "react-icons/lu";
-import { MdVideoLibrary } from "react-icons/md";
+import { MdCategory, MdVideoLibrary } from "react-icons/md";
 import { TbFaceId } from "react-icons/tb";
 import useSWR from "swr";
 
@@ -16,6 +16,7 @@ export const ID_EXPLORE = 3;
 export const ID_EXPORT = 4;
 export const ID_PLAYGROUND = 5;
 export const ID_FACE_LIBRARY = 6;
+export const ID_CLASSIFICATION = 7;
 
 export default function useNavigation(
   variant: "primary" | "secondary" = "primary",
@@ -71,6 +72,14 @@ export default function useNavigation(
           url: "/faces",
           enabled: isDesktop && config?.face_recognition.enabled,
         },
+        {
+          id: ID_CLASSIFICATION,
+          variant,
+          icon: MdCategory,
+          title: "menu.classification",
+          url: "/classification",
+          enabled: isDesktop,
+        },
       ] as NavData[],
     [config?.face_recognition?.enabled, variant],
   );

web/src/pages/ClassificationModel.tsx

@@ -0,0 +1,18 @@
+import { useOverlayState } from "@/hooks/use-overlay-state";
+import { CustomClassificationModelConfig } from "@/types/frigateConfig";
+import ModelSelectionView from "@/views/classification/ModelSelectionView";
+import ModelTrainingView from "@/views/classification/ModelTrainingView";
+
+export default function ClassificationModelPage() {
+  // training
+
+  const [model, setModel] = useOverlayState<CustomClassificationModelConfig>(
+    "classificationModel",
+  );
+
+  if (model == undefined) {
+    return <ModelSelectionView onClick={setModel} />;
+  }
+
+  return <ModelTrainingView model={model} />;
+}

web/src/types/frigateConfig.ts

@@ -279,6 +279,23 @@ export type CameraStreamingSettings = {
   volume: number;
 };
 
+export type CustomClassificationModelConfig = {
+  enabled: boolean;
+  name: string;
+  object_config: null | {
+    objects: string[];
+  };
+  state_config: null | {
+    cameras: {
+      [cameraName: string]: {
+        crop: [number, number, number, number];
+        threshold: number;
+      };
+    };
+    motion: boolean;
+  };
+};
+
 export type GroupStreamingSettings = {
   [cameraName: string]: CameraStreamingSettings;
 };
@@ -316,6 +333,9 @@ export interface FrigateConfig {
       enabled: boolean;
       threshold: number;
     };
+    custom: {
+      [modelKey: string]: CustomClassificationModelConfig;
+    };
   };
 
   database: {

web/src/views/classification/ModelSelectionView.tsx

@@ -0,0 +1,63 @@
+import ActivityIndicator from "@/components/indicators/activity-indicator";
+import { cn } from "@/lib/utils";
+import {
+  CustomClassificationModelConfig,
+  FrigateConfig,
+} from "@/types/frigateConfig";
+import { useMemo } from "react";
+import { isMobile } from "react-device-detect";
+import useSWR from "swr";
+
+type ModelSelectionViewProps = {
+  onClick: (model: CustomClassificationModelConfig) => void;
+};
+export default function ModelSelectionView({
+  onClick,
+}: ModelSelectionViewProps) {
+  const { data: config } = useSWR<FrigateConfig>("config", {
+    revalidateOnFocus: false,
+  });
+
+  const classificationConfigs = useMemo(() => {
+    if (!config) {
+      return [];
+    }
+
+    return Object.values(config.classification.custom);
+  }, [config]);
+
+  if (!config) {
+    return <ActivityIndicator />;
+  }
+
+  if (classificationConfigs.length == 0) {
+    return <div>You need to setup a custom model configuration.</div>;
+  }
+
+  return (
+    <div className="flex size-full gap-2 p-2">
+      {classificationConfigs.map((config) => (
+        <div
+          key={config.name}
+          className={cn(
+            "flex h-52 cursor-pointer flex-col gap-2 rounded-lg bg-card p-2 outline outline-[3px]",
+            "outline-transparent duration-500",
+            isMobile && "w-full",
+          )}
+          onClick={() => onClick(config)}
+          onContextMenu={() => {
+            // e.stopPropagation();
+            // e.preventDefault();
+            // handleClickEvent(true);
+          }}
+        >
+          <div className="size-48"></div>
+          <div className="smart-capitalize">
+            {config.name} ({config.state_config != null ? "State" : "Object"}{" "}
+            Classification)
+          </div>
+        </div>
+      ))}
+    </div>
+  );
+}

web/src/views/classification/ModelTrainingView.tsx

@@ -0,0 +1,661 @@
+import { baseUrl } from "@/api/baseUrl";
+import TextEntryDialog from "@/components/overlay/dialog/TextEntryDialog";
+import { Button, buttonVariants } from "@/components/ui/button";
+import {
+  AlertDialog,
+  AlertDialogAction,
+  AlertDialogCancel,
+  AlertDialogContent,
+  AlertDialogDescription,
+  AlertDialogFooter,
+  AlertDialogHeader,
+  AlertDialogTitle,
+} from "@/components/ui/alert-dialog";
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogHeader,
+  DialogTitle,
+} from "@/components/ui/dialog";
+import {
+  DropdownMenu,
+  DropdownMenuContent,
+  DropdownMenuItem,
+  DropdownMenuSeparator,
+  DropdownMenuTrigger,
+} from "@/components/ui/dropdown-menu";
+import { Toaster } from "@/components/ui/sonner";
+import {
+  Tooltip,
+  TooltipContent,
+  TooltipTrigger,
+} from "@/components/ui/tooltip";
+import useKeyboardListener from "@/hooks/use-keyboard-listener";
+import useOptimisticState from "@/hooks/use-optimistic-state";
+import { cn } from "@/lib/utils";
+import { CustomClassificationModelConfig } from "@/types/frigateConfig";
+import { TooltipPortal } from "@radix-ui/react-tooltip";
+import axios from "axios";
+import { useCallback, useEffect, useMemo, useState } from "react";
+import { isDesktop, isMobile } from "react-device-detect";
+import { Trans, useTranslation } from "react-i18next";
+import { LuPencil, LuTrash2 } from "react-icons/lu";
+import { toast } from "sonner";
+import useSWR from "swr";
+import ClassificationSelectionDialog from "@/components/overlay/ClassificationSelectionDialog";
+import { TbCategoryPlus } from "react-icons/tb";
+
+type ModelTrainingViewProps = {
+  model: CustomClassificationModelConfig;
+};
+export default function ModelTrainingView({ model }: ModelTrainingViewProps) {
+  const { t } = useTranslation(["views/classificationModel"]);
+  const [page, setPage] = useState<string>("train");
+  const [pageToggle, setPageToggle] = useOptimisticState(page, setPage, 100);
+
+  // dataset
+
+  const { data: trainImages, mutate: refreshTrain } = useSWR<string[]>(
+    `classification/${model.name}/train`,
+  );
+  const { data: dataset, mutate: refreshDataset } = useSWR<{
+    [id: string]: string[];
+  }>(`classification/${model.name}/dataset`);
+
+  // image multiselect
+
+  const [selectedImages, setSelectedImages] = useState<string[]>([]);
+
+  const onClickImages = useCallback(
+    (images: string[], ctrl: boolean) => {
+      if (selectedImages.length == 0 && !ctrl) {
+        return;
+      }
+
+      let newSelectedImages = [...selectedImages];
+
+      images.forEach((imageId) => {
+        const index = newSelectedImages.indexOf(imageId);
+
+        if (index != -1) {
+          if (selectedImages.length == 1) {
+            newSelectedImages = [];
+          } else {
+            const copy = [
+              ...newSelectedImages.slice(0, index),
+              ...newSelectedImages.slice(index + 1),
+            ];
+            newSelectedImages = copy;
+          }
+        } else {
+          newSelectedImages.push(imageId);
+        }
+      });
+
+      setSelectedImages(newSelectedImages);
+    },
+    [selectedImages, setSelectedImages],
+  );
+
+  // actions
+
+  const trainModel = useCallback(() => {
+    axios.post(`classification/${model.name}/train`);
+  }, [model]);
+
+  const [deleteDialogOpen, setDeleteDialogOpen] = useState<string[] | null>(
+    null,
+  );
+
+  const onDelete = useCallback(
+    (ids: string[], isName: boolean = false) => {
+      const api =
+        pageToggle == "train"
+          ? `/classification/${model.name}/train/delete`
+          : `/classification/${model.name}/dataset/${pageToggle}/delete`;
+
+      axios
+        .post(api, { ids })
+        .then((resp) => {
+          setSelectedImages([]);
+
+          if (resp.status == 200) {
+            if (isName) {
+              toast.success(
+                t("toast.success.deletedCategory", { count: ids.length }),
+                {
+                  position: "top-center",
+                },
+              );
+            } else {
+              toast.success(
+                t("toast.success.deletedImage", { count: ids.length }),
+                {
+                  position: "top-center",
+                },
+              );
+            }
+
+            if (pageToggle == "train") {
+              refreshTrain();
+            } else {
+              refreshDataset();
+            }
+          }
+        })
+        .catch((error) => {
+          const errorMessage =
+            error.response?.data?.message ||
+            error.response?.data?.detail ||
+            "Unknown error";
+          if (isName) {
+            toast.error(
+              t("toast.error.deleteCategoryFailed", { errorMessage }),
+              {
+                position: "top-center",
+              },
+            );
+          } else {
+            toast.error(t("toast.error.deleteImageFailed", { errorMessage }), {
+              position: "top-center",
+            });
+          }
+        });
+    },
+    [pageToggle, model, refreshTrain, refreshDataset, t],
+  );
+
+  // keyboard
+
+  useKeyboardListener(["a", "Escape"], (key, modifiers) => {
+    if (modifiers.repeat || !modifiers.down) {
+      return;
+    }
+
+    switch (key) {
+      case "a":
+        if (modifiers.ctrl) {
+          if (selectedImages.length) {
+            setSelectedImages([]);
+          } else {
+            setSelectedImages([
+              ...(pageToggle === "train"
+                ? trainImages || []
+                : dataset?.[pageToggle] || []),
+            ]);
+          }
+        }
+        break;
+      case "Escape":
+        setSelectedImages([]);
+        break;
+    }
+  });
+
+  useEffect(() => {
+    setSelectedImages([]);
+  }, [pageToggle]);
+
+  return (
+    <div className="flex size-full flex-col overflow-hidden">
+      <Toaster />
+
+      <AlertDialog
+        open={!!deleteDialogOpen}
+        onOpenChange={() => setDeleteDialogOpen(null)}
+      >
+        <AlertDialogContent>
+          <AlertDialogHeader>
+            <AlertDialogTitle>
+              {t(
+                pageToggle == "train"
+                  ? "deleteTrainImages.title"
+                  : "deleteDatasetImages.title",
+              )}
+            </AlertDialogTitle>
+          </AlertDialogHeader>
+          <AlertDialogDescription>
+            <Trans
+              ns="views/classificationModel"
+              values={{ count: deleteDialogOpen?.length, dataset: pageToggle }}
+            >
+              {pageToggle == "train"
+                ? "deleteTrainImages.desc"
+                : "deleteDatasetImages.desc"}
+            </Trans>
+          </AlertDialogDescription>
+          <AlertDialogFooter>
+            <AlertDialogCancel>
+              {t("button.cancel", { ns: "common" })}
+            </AlertDialogCancel>
+            <AlertDialogAction
+              className={buttonVariants({ variant: "destructive" })}
+              onClick={() => {
+                if (deleteDialogOpen) {
+                  onDelete(deleteDialogOpen);
+                  setDeleteDialogOpen(null);
+                }
+              }}
+            >
+              {t("button.delete", { ns: "common" })}
+            </AlertDialogAction>
+          </AlertDialogFooter>
+        </AlertDialogContent>
+      </AlertDialog>
+
+      <div className="flex flex-row justify-between gap-2 p-2 align-middle">
+        <LibrarySelector
+          pageToggle={pageToggle}
+          dataset={dataset || {}}
+          trainImages={trainImages || []}
+          setPageToggle={setPageToggle}
+          onDelete={onDelete}
+          onRename={() => {}}
+        />
+        {selectedImages?.length > 0 ? (
+          <div className="flex items-center justify-center gap-2">
+            <div className="mx-1 flex w-48 items-center justify-center text-sm text-muted-foreground">
+              <div className="p-1">{`${selectedImages.length} selected`}</div>
+              <div className="p-1">{"|"}</div>
+              <div
+                className="cursor-pointer p-2 text-primary hover:rounded-lg hover:bg-secondary"
+                onClick={() => setSelectedImages([])}
+              >
+                {t("button.unselect", { ns: "common" })}
+              </div>
+            </div>
+            <Button
+              className="flex gap-2"
+              onClick={() => setDeleteDialogOpen(selectedImages)}
+            >
+              <LuTrash2 className="size-7 rounded-md p-1 text-secondary-foreground" />
+              {isDesktop && t("button.deleteImages")}
+            </Button>
+          </div>
+        ) : (
+          <Button onClick={trainModel}>Train Model</Button>
+        )}
+      </div>
+      {pageToggle == "train" ? (
+        <TrainGrid
+          model={model}
+          classes={Object.keys(dataset || {})}
+          trainImages={trainImages || []}
+          selectedImages={selectedImages}
+          onRefresh={refreshTrain}
+          onClickImages={onClickImages}
+          onDelete={onDelete}
+        />
+      ) : (
+        <DatasetGrid
+          modelName={model.name}
+          categoryName={pageToggle}
+          images={dataset?.[pageToggle] || []}
+          selectedImages={selectedImages}
+          onClickImages={onClickImages}
+          onDelete={onDelete}
+        />
+      )}
+    </div>
+  );
+}
+
+type LibrarySelectorProps = {
+  pageToggle: string | undefined;
+  dataset: { [id: string]: string[] };
+  trainImages: string[];
+  setPageToggle: (toggle: string) => void;
+  onDelete: (ids: string[], isName: boolean) => void;
+  onRename: (old_name: string, new_name: string) => void;
+};
+function LibrarySelector({
+  pageToggle,
+  dataset,
+  trainImages,
+  setPageToggle,
+  onDelete,
+  onRename,
+}: LibrarySelectorProps) {
+  const { t } = useTranslation(["views/classificationModel"]);
+  const [confirmDelete, setConfirmDelete] = useState<string | null>(null);
+  const [renameFace, setRenameFace] = useState<string | null>(null);
+
+  const handleDeleteFace = useCallback(
+    (name: string) => {
+      // Get all image IDs for this face
+      const imageIds = dataset?.[name] || [];
+
+      onDelete(imageIds, true);
+      setPageToggle("train");
+    },
+    [dataset, onDelete, setPageToggle],
+  );
+
+  const handleSetOpen = useCallback(
+    (open: boolean) => {
+      setRenameFace(open ? renameFace : null);
+    },
+    [renameFace],
+  );
+
+  return (
+    <>
+      <Dialog
+        open={!!confirmDelete}
+        onOpenChange={(open) => !open && setConfirmDelete(null)}
+      >
+        <DialogContent>
+          <DialogHeader>
+            <DialogTitle>{t("deleteCategory.title")}</DialogTitle>
+            <DialogDescription>
+              {t("deleteCategory.desc", { name: confirmDelete })}
+            </DialogDescription>
+          </DialogHeader>
+          <div className="flex justify-end gap-2">
+            <Button variant="outline" onClick={() => setConfirmDelete(null)}>
+              {t("button.cancel", { ns: "common" })}
+            </Button>
+            <Button
+              variant="destructive"
+              onClick={() => {
+                if (confirmDelete) {
+                  handleDeleteFace(confirmDelete);
+                  setConfirmDelete(null);
+                }
+              }}
+            >
+              {t("button.delete", { ns: "common" })}
+            </Button>
+          </div>
+        </DialogContent>
+      </Dialog>
+
+      <TextEntryDialog
+        open={!!renameFace}
+        setOpen={handleSetOpen}
+        title={t("renameCategory.title")}
+        description={t("renameCategory.desc", { name: renameFace })}
+        onSave={(newName) => {
+          onRename(renameFace!, newName);
+          setRenameFace(null);
+        }}
+        defaultValue={renameFace || ""}
+        regexPattern={/^[\p{L}\p{N}\s'_-]{1,50}$/u}
+        regexErrorMessage={t("description.invalidName")}
+      />
+
+      <DropdownMenu>
+        <DropdownMenuTrigger asChild>
+          <Button className="flex justify-between smart-capitalize">
+            {pageToggle == "train" ? t("train.title") : pageToggle}
+            <span className="ml-2 text-primary-variant">
+              (
+              {(pageToggle &&
+                (pageToggle == "train"
+                  ? trainImages.length
+                  : dataset?.[pageToggle]?.length)) ||
+                0}
+              )
+            </span>
+          </Button>
+        </DropdownMenuTrigger>
+        <DropdownMenuContent
+          className="scrollbar-container max-h-[40dvh] min-w-[220px] overflow-y-auto"
+          align="start"
+        >
+          <DropdownMenuItem
+            className="flex cursor-pointer items-center justify-start gap-2"
+            aria-label={t("train.aria")}
+            onClick={() => setPageToggle("train")}
+          >
+            <div>{t("train.title")}</div>
+            <div className="text-secondary-foreground">
+              ({trainImages.length})
+            </div>
+          </DropdownMenuItem>
+          {trainImages.length > 0 && Object.keys(dataset).length > 0 && (
+            <>
+              <DropdownMenuSeparator />
+              <div className="mb-1 ml-1.5 text-xs text-secondary-foreground">
+                {t("categories")}
+              </div>
+            </>
+          )}
+          {Object.keys(dataset).map((id) => (
+            <DropdownMenuItem
+              key={id}
+              className="group flex items-center justify-between"
+            >
+              <div
+                className="flex-grow cursor-pointer"
+                onClick={() => setPageToggle(id)}
+              >
+                {id}
+                <span className="ml-2 text-muted-foreground">
+                  ({dataset?.[id].length})
+                </span>
+              </div>
+              <div className="flex gap-0.5">
+                <Tooltip>
+                  <TooltipTrigger asChild>
+                    <Button
+                      variant="ghost"
+                      size="icon"
+                      className="size-7 lg:opacity-0 lg:transition-opacity lg:group-hover:opacity-100"
+                      onClick={(e) => {
+                        e.stopPropagation();
+                        setRenameFace(id);
+                      }}
+                    >
+                      <LuPencil className="size-4 text-primary" />
+                    </Button>
+                  </TooltipTrigger>
+                  <TooltipPortal>
+                    <TooltipContent>
+                      {t("button.renameCategory")}
+                    </TooltipContent>
+                  </TooltipPortal>
+                </Tooltip>
+                <Tooltip>
+                  <TooltipTrigger asChild>
+                    <Button
+                      variant="ghost"
+                      size="icon"
+                      className="size-7 lg:opacity-0 lg:transition-opacity lg:group-hover:opacity-100"
+                      onClick={(e) => {
+                        e.stopPropagation();
+                        setConfirmDelete(id);
+                      }}
+                    >
+                      <LuTrash2 className="size-4 text-destructive" />
+                    </Button>
+                  </TooltipTrigger>
+                  <TooltipPortal>
+                    <TooltipContent>
+                      {t("button.deleteCategory")}
+                    </TooltipContent>
+                  </TooltipPortal>
+                </Tooltip>
+              </div>
+            </DropdownMenuItem>
+          ))}
+        </DropdownMenuContent>
+      </DropdownMenu>
+    </>
+  );
+}
+
+type DatasetGridProps = {
+  modelName: string;
+  categoryName: string;
+  images: string[];
+  selectedImages: string[];
+  onClickImages: (images: string[], ctrl: boolean) => void;
+  onDelete: (ids: string[]) => void;
+};
+function DatasetGrid({
+  modelName,
+  categoryName,
+  images,
+  selectedImages,
+  onClickImages,
+  onDelete,
+}: DatasetGridProps) {
+  const { t } = useTranslation(["views/classificationModel"]);
+
+  return (
+    <div className="flex flex-wrap gap-2 overflow-y-auto p-2">
+      {images.map((image) => (
+        <div
+          className={cn(
+            "flex w-60 cursor-pointer flex-col gap-2 rounded-lg bg-card outline outline-[3px]",
+            selectedImages.includes(image)
+              ? "shadow-selected outline-selected"
+              : "outline-transparent duration-500",
+          )}
+          onClick={(e) => {
+            e.stopPropagation();
+
+            if (e.ctrlKey || e.metaKey) {
+              onClickImages([image], true);
+            }
+          }}
+        >
+          <div
+            className={cn(
+              "w-full overflow-hidden p-2 *:text-card-foreground",
+              isMobile && "flex justify-center",
+            )}
+          >
+            <img
+              className="rounded-lg"
+              src={`${baseUrl}clips/${modelName}/dataset/${categoryName}/${image}`}
+            />
+          </div>
+          <div className="rounded-b-lg bg-card p-3">
+            <div className="flex w-full flex-row items-center justify-between gap-2">
+              <div className="flex w-full flex-row items-start justify-end gap-5 md:gap-4">
+                <Tooltip>
+                  <TooltipTrigger>
+                    <LuTrash2
+                      className="size-5 cursor-pointer text-primary-variant hover:text-primary"
+                      onClick={(e) => {
+                        e.stopPropagation();
+                        onDelete([image]);
+                      }}
+                    />
+                  </TooltipTrigger>
+                  <TooltipContent>
+                    {t("button.deleteClassificationAttempts")}
+                  </TooltipContent>
+                </Tooltip>
+              </div>
+            </div>
+          </div>
+        </div>
+      ))}
+    </div>
+  );
+}
+
+type TrainGridProps = {
+  model: CustomClassificationModelConfig;
+  classes: string[];
+  trainImages: string[];
+  selectedImages: string[];
+  onClickImages: (images: string[], ctrl: boolean) => void;
+  onRefresh: () => void;
+  onDelete: (ids: string[]) => void;
+};
+function TrainGrid({
+  model,
+  classes,
+  trainImages,
+  selectedImages,
+  onClickImages,
+  onRefresh,
+  onDelete,
+}: TrainGridProps) {
+  const { t } = useTranslation(["views/classificationModel"]);
+
+  const trainData = useMemo(
+    () =>
+      trainImages
+        .map((raw) => {
+          const parts = raw.replaceAll(".webp", "").split("-");
+          return {
+            raw,
+            timestamp: parts[0],
+            label: parts[1],
+            score: Number.parseFloat(parts[2]) * 100,
+          };
+        })
+        .sort((a, b) => b.timestamp.localeCompare(a.timestamp)),
+    [trainImages],
+  );
+
+  return (
+    <div className="flex flex-wrap gap-2 overflow-y-auto p-2">
+      {trainData?.map((data) => (
+        <div
+          key={data.timestamp}
+          className={cn(
+            "flex w-56 cursor-pointer flex-col gap-2 rounded-lg bg-card outline outline-[3px]",
+            selectedImages.includes(data.raw)
+              ? "shadow-selected outline-selected"
+              : "outline-transparent duration-500",
+          )}
+          onClick={(e) => {
+            e.stopPropagation();
+            onClickImages([data.raw], e.ctrlKey || e.metaKey);
+          }}
+        >
+          <div
+            className={cn(
+              "w-full overflow-hidden p-2 *:text-card-foreground",
+              isMobile && "flex justify-center",
+            )}
+          >
+            <img
+              className="w-56 rounded-lg"
+              src={`${baseUrl}clips/${model.name}/train/${data.raw}`}
+            />
+          </div>
+          <div className="rounded-b-lg bg-card p-3">
+            <div className="flex w-full flex-row items-center justify-between gap-2">
+              <div className="flex flex-col items-start text-xs text-primary-variant">
+                <div className="smart-capitalize">{data.label}</div>
+                <div>{data.score}%</div>
+              </div>
+              <div className="flex flex-row items-start justify-end gap-5 md:gap-4">
+                <ClassificationSelectionDialog
+                  classes={classes}
+                  modelName={model.name}
+                  image={data.raw}
+                  onRefresh={onRefresh}
+                >
+                  <TbCategoryPlus className="size-5 cursor-pointer text-primary-variant hover:text-primary" />
+                </ClassificationSelectionDialog>
+                <Tooltip>
+                  <TooltipTrigger>
+                    <LuTrash2
+                      className="size-5 cursor-pointer text-primary-variant hover:text-primary"
+                      onClick={(e) => {
+                        e.stopPropagation();
+                        onDelete([data.raw]);
+                      }}
+                    />
+                  </TooltipTrigger>
+                  <TooltipContent>
+                    {t("button.deleteClassificationAttempts")}
+                  </TooltipContent>
+                </Tooltip>
+              </div>
+            </div>
+          </div>
+        </div>
+      ))}
+    </div>
+  );
+}