Cleanup model running

frigate/api/classification.py

@@ -25,7 +25,13 @@ def get_faces():
 
     for name in os.listdir(FACE_DIR):
         face_dict[name] = []
-        for file in os.listdir(os.path.join(FACE_DIR, name)):
+
+        face_dir = os.path.join(FACE_DIR, name)
+
+        if not os.path.isdir(face_dir):
+            continue
+
+        for file in os.listdir(face_dir):
             face_dict[name].append(file)
 
     return JSONResponse(status_code=200, content=face_dict)
@@ -41,18 +47,17 @@ async def register_face(request: Request, name: str, file: UploadFile):
     )
 
 
-@router.post("/faces/{name}/train")
+@router.post("/faces/train/{name}/classify")
 def train_face(name: str, body: dict = None):
     json: dict[str, any] = body or {}
-    file_name = sanitize_filename(json.get("training_file", ""))
+    training_file = os.path.join(FACE_DIR, f"train/{sanitize_filename(json.get("training_file", ""))}")
-    training_file = os.path.join(FACE_DIR, f"train/{file_name}")
 
-    if not file_name or not os.path.isfile(training_file):
+    if not training_file or not os.path.isfile(training_file):
         return JSONResponse(
             content=(
                 {
                     "success": False,
-                    "message": f"Invalid filename or no file exists: {file_name}",
+                    "message": f"Invalid filename or no file exists: {training_file}",
                 }
             ),
             status_code=404,
@@ -66,7 +71,7 @@ def train_face(name: str, body: dict = None):
         content=(
             {
                 "success": True,
-                "message": f"Successfully saved {file_name} as {new_name}.",
+                "message": f"Successfully saved {training_file} as {new_name}.",
             }
         ),
         status_code=200,

frigate/util/model.py

@@ -163,7 +163,10 @@ class FaceClassificationModel:
         self.config = config
         self.db = db
         self.landmark_detector = cv2.face.createFacemarkLBF()
+
+        if os.path.isfile("/config/model_cache/facedet/landmarkdet.yaml"):
             self.landmark_detector.loadModel("/config/model_cache/facedet/landmarkdet.yaml")
+
         self.recognizer: cv2.face.LBPHFaceRecognizer = (
             cv2.face.LBPHFaceRecognizer_create(
                 radius=2, threshold=(1 - config.min_score) * 1000
@@ -178,13 +181,21 @@ class FaceClassificationModel:
 
         dir = "/media/frigate/clips/faces"
         for idx, name in enumerate(os.listdir(dir)):
-            if name == "debug":
+            if name == "train":
+                continue
+
+            face_folder = os.path.join(dir, name)
+
+            if not os.path.isdir(face_folder):
                 continue
 
             self.label_map[idx] = name
-            face_folder = os.path.join(dir, name)
             for image in os.listdir(face_folder):
                 img = cv2.imread(os.path.join(face_folder, image))
+
+                if img is None:
+                    continue
+
                 img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
                 img = self.__align_face(img, img.shape[1], img.shape[0])
                 faces.append(img)

web/src/components/icons/AddFaceIcon.tsx

@@ -0,0 +1,25 @@
+import { forwardRef } from "react";
+import { LuPlus, LuScanFace } from "react-icons/lu";
+import { cn } from "@/lib/utils";
+
+type AddFaceIconProps = {
+  className?: string;
+  onClick?: () => void;
+};
+
+const AddFaceIcon = forwardRef<HTMLDivElement, AddFaceIconProps>(
+  ({ className, onClick }, ref) => {
+    return (
+      <div
+        ref={ref}
+        className={cn("relative flex items-center", className)}
+        onClick={onClick}
+      >
+        <LuScanFace className="size-full" />
+        <LuPlus className="absolute size-4 translate-x-3 translate-y-3" />
+      </div>
+    );
+  },
+);
+
+export default AddFaceIcon;

web/src/pages/FaceLibrary.tsx

@@ -1,7 +1,14 @@
 import { baseUrl } from "@/api/baseUrl";
-import Chip from "@/components/indicators/Chip";
+import AddFaceIcon from "@/components/icons/AddFaceIcon";
 import UploadImageDialog from "@/components/overlay/dialog/UploadImageDialog";
 import { Button } from "@/components/ui/button";
+import {
+  DropdownMenu,
+  DropdownMenuContent,
+  DropdownMenuItem,
+  DropdownMenuLabel,
+  DropdownMenuTrigger,
+} from "@/components/ui/dropdown-menu";
 import { ScrollArea, ScrollBar } from "@/components/ui/scroll-area";
 import { Toaster } from "@/components/ui/sonner";
 import { ToggleGroup, ToggleGroupItem } from "@/components/ui/toggle-group";
@@ -13,8 +20,7 @@ import {
 import useOptimisticState from "@/hooks/use-optimistic-state";
 import axios from "axios";
 import { useCallback, useEffect, useMemo, useRef, useState } from "react";
-import { isDesktop } from "react-device-detect";
+import { LuImagePlus, LuTrash2 } from "react-icons/lu";
-import { LuImagePlus, LuTrash, LuTrash2 } from "react-icons/lu";
 import { toast } from "sonner";
 import useSWR from "swr";
 
@@ -154,7 +160,11 @@ export default function FaceLibrary() {
       </div>
       {pageToggle &&
         (pageToggle == "train" ? (
-          <TrainingGrid attemptImages={trainImages} onRefresh={refreshFaces} />
+          <TrainingGrid
+            attemptImages={trainImages}
+            faceNames={faces}
+            onRefresh={refreshFaces}
+          />
         ) : (
           <FaceGrid
             faceImages={faceImages}
@@ -169,13 +179,23 @@ export default function FaceLibrary() {
 
 type TrainingGridProps = {
   attemptImages: string[];
+  faceNames: string[];
   onRefresh: () => void;
 };
-function TrainingGrid({ attemptImages, onRefresh }: TrainingGridProps) {
+function TrainingGrid({
+  attemptImages,
+  faceNames,
+  onRefresh,
+}: TrainingGridProps) {
   return (
     <div className="scrollbar-container flex flex-wrap gap-2 overflow-y-scroll">
       {attemptImages.map((image: string) => (
-        <FaceAttempt key={image} image={image} onRefresh={onRefresh} />
+        <FaceAttempt
+          key={image}
+          image={image}
+          faceNames={faceNames}
+          onRefresh={onRefresh}
+        />
       ))}
     </div>
   );
@@ -183,9 +203,10 @@ function TrainingGrid({ attemptImages, onRefresh }: TrainingGridProps) {
 
 type FaceAttemptProps = {
   image: string;
+  faceNames: string[];
   onRefresh: () => void;
 };
-function FaceAttempt({ image, onRefresh }: FaceAttemptProps) {
+function FaceAttempt({ image, faceNames, onRefresh }: FaceAttemptProps) {
   const data = useMemo(() => {
     const parts = image.split("-");
 
@@ -196,6 +217,33 @@ function FaceAttempt({ image, onRefresh }: FaceAttemptProps) {
     };
   }, [image]);
 
+  const onTrainAttempt = useCallback(
+    (trainName: string) => {
+      axios
+        .post(`/faces/train/${trainName}/classify`, { training_file: image })
+        .then((resp) => {
+          if (resp.status == 200) {
+            toast.success(`Successfully trained face.`, {
+              position: "top-center",
+            });
+            onRefresh();
+          }
+        })
+        .catch((error) => {
+          if (error.response?.data?.message) {
+            toast.error(`Failed to train: ${error.response.data.message}`, {
+              position: "top-center",
+            });
+          } else {
+            toast.error(`Failed to train: ${error.message}`, {
+              position: "top-center",
+            });
+          }
+        });
+    },
+    [image, onRefresh],
+  );
+
   const onDelete = useCallback(() => {
     axios
       .post(`/faces/train/delete`, { ids: [image] })
@@ -232,6 +280,28 @@ function FaceAttempt({ image, onRefresh }: FaceAttemptProps) {
             <div>{Number.parseFloat(data.score) * 100}%</div>
           </div>
           <div className="flex flex-row items-start justify-end gap-5 md:gap-4">
+            <Tooltip>
+              <DropdownMenu>
+                <DropdownMenuTrigger>
+                  <TooltipTrigger>
+                    <AddFaceIcon className="size-5 cursor-pointer text-primary-variant hover:text-primary" />
+                  </TooltipTrigger>
+                </DropdownMenuTrigger>
+                <DropdownMenuContent>
+                  <DropdownMenuLabel>Train Face as:</DropdownMenuLabel>
+                  {faceNames.map((faceName) => (
+                    <DropdownMenuItem
+                      key={faceName}
+                      className="cursor-pointer capitalize"
+                      onClick={() => onTrainAttempt(faceName)}
+                    >
+                      {faceName}
+                    </DropdownMenuItem>
+                  ))}
+                </DropdownMenuContent>
+              </DropdownMenu>
+              <TooltipContent>Train Face as Person</TooltipContent>
+            </Tooltip>
             <Tooltip>
               <TooltipTrigger>
                 <LuTrash2