diff --git a/web/apps/photos/src/services/machineLearning/yoloFaceDetectionService.ts b/web/apps/photos/src/services/machineLearning/yoloFaceDetectionService.ts
index 6ed3e1205..699d53cfe 100644
--- a/web/apps/photos/src/services/machineLearning/yoloFaceDetectionService.ts
+++ b/web/apps/photos/src/services/machineLearning/yoloFaceDetectionService.ts
@@ -12,7 +12,6 @@ import {
     normalizePixelBetween0And1,
 } from "utils/image";
 import { newBox } from "utils/machineLearning";
-import { removeDuplicateDetections } from "utils/machineLearning/faceDetection";
 import {
     computeTransformToBox,
     transformBox,
@@ -324,3 +323,65 @@ class YoloFaceDetectionService implements FaceDetectionService {
 }
 
 export default new YoloFaceDetectionService();
+
+import { euclidean } from "hdbscan";
+
+/**
+ * Removes duplicate face detections from an array of detections.
+ *
+ * This function sorts the detections by their probability in descending order, then iterates over them.
+ * For each detection, it calculates the Euclidean distance to all other detections.
+ * If the distance is less than or equal to the specified threshold (`withinDistance`), the other detection is considered a duplicate and is removed.
+ *
+ * @param detections - An array of face detections to remove duplicates from.
+ * @param withinDistance - The maximum Euclidean distance between two detections for them to be considered duplicates.
+ *
+ * @returns An array of face detections with duplicates removed.
+ */
+function removeDuplicateDetections(
+    detections: Array<FaceDetection>,
+    withinDistance: number,
+) {
+    // console.time('removeDuplicates');
+    detections.sort((a, b) => b.probability - a.probability);
+    const isSelected = new Map<number, boolean>();
+    for (let i = 0; i < detections.length; i++) {
+        if (isSelected.get(i) === false) {
+            continue;
+        }
+        isSelected.set(i, true);
+        for (let j = i + 1; j < detections.length; j++) {
+            if (isSelected.get(j) === false) {
+                continue;
+            }
+            const centeri = getDetectionCenter(detections[i]);
+            const centerj = getDetectionCenter(detections[j]);
+            const dist = euclidean(
+                [centeri.x, centeri.y],
+                [centerj.x, centerj.y],
+            );
+            if (dist <= withinDistance) {
+                isSelected.set(j, false);
+            }
+        }
+    }
+
+    const uniques: Array<FaceDetection> = [];
+    for (let i = 0; i < detections.length; i++) {
+        isSelected.get(i) && uniques.push(detections[i]);
+    }
+    // console.timeEnd('removeDuplicates');
+    return uniques;
+}
+
+function getDetectionCenter(detection: FaceDetection) {
+    const center = new Point(0, 0);
+    // TODO: first 4 landmarks is applicable to blazeface only
+    // this needs to consider eyes, nose and mouth landmarks to take center
+    detection.landmarks?.slice(0, 4).forEach((p) => {
+        center.x += p.x;
+        center.y += p.y;
+    });
+
+    return center.div({ x: 4, y: 4 });
+}
diff --git a/web/apps/photos/src/utils/machineLearning/faceDetection.ts b/web/apps/photos/src/utils/machineLearning/faceDetection.ts
deleted file mode 100644
index 6a0402dcf..000000000
--- a/web/apps/photos/src/utils/machineLearning/faceDetection.ts
+++ /dev/null
@@ -1,63 +0,0 @@
-import { euclidean } from "hdbscan";
-import { FaceDetection } from "types/machineLearning";
-import { Point } from "../../../thirdparty/face-api/classes";
-
-export function getDetectionCenter(detection: FaceDetection) {
-    const center = new Point(0, 0);
-    // TODO: first 4 landmarks is applicable to blazeface only
-    // this needs to consider eyes, nose and mouth landmarks to take center
-    detection.landmarks?.slice(0, 4).forEach((p) => {
-        center.x += p.x;
-        center.y += p.y;
-    });
-
-    return center.div({ x: 4, y: 4 });
-}
-
-/**
- * Removes duplicate face detections from an array of detections.
- *
- * This function sorts the detections by their probability in descending order, then iterates over them.
- * For each detection, it calculates the Euclidean distance to all other detections.
- * If the distance is less than or equal to the specified threshold (`withinDistance`), the other detection is considered a duplicate and is removed.
- *
- * @param detections - An array of face detections to remove duplicates from.
- * @param withinDistance - The maximum Euclidean distance between two detections for them to be considered duplicates.
- *
- * @returns An array of face detections with duplicates removed.
- */
-export function removeDuplicateDetections(
-    detections: Array<FaceDetection>,
-    withinDistance: number,
-) {
-    // console.time('removeDuplicates');
-    detections.sort((a, b) => b.probability - a.probability);
-    const isSelected = new Map<number, boolean>();
-    for (let i = 0; i < detections.length; i++) {
-        if (isSelected.get(i) === false) {
-            continue;
-        }
-        isSelected.set(i, true);
-        for (let j = i + 1; j < detections.length; j++) {
-            if (isSelected.get(j) === false) {
-                continue;
-            }
-            const centeri = getDetectionCenter(detections[i]);
-            const centerj = getDetectionCenter(detections[j]);
-            const dist = euclidean(
-                [centeri.x, centeri.y],
-                [centerj.x, centerj.y],
-            );
-            if (dist <= withinDistance) {
-                isSelected.set(j, false);
-            }
-        }
-    }
-
-    const uniques: Array<FaceDetection> = [];
-    for (let i = 0; i < detections.length; i++) {
-        isSelected.get(i) && uniques.push(detections[i]);
-    }
-    // console.timeEnd('removeDuplicates');
-    return uniques;
-}