diff --git a/src/gui/app.rs b/src/gui/app.rs
index a537192..642800c 100644
--- a/src/gui/app.rs
+++ b/src/gui/app.rs
@@ -76,6 +76,8 @@ pub enum ComparisonResult {
     Success {
         image1_faces: usize,
         image2_faces: usize,
+        image1_face_rois: Vec<ndarray::Array3<u8>>,
+        image2_face_rois: Vec<ndarray::Array3<u8>>,
         best_similarity: f32,
         processing_time: f64,
     },
@@ -765,6 +767,8 @@ impl FaceDetectorApp {
                 ComparisonResult::Success {
                     image1_faces,
                     image2_faces,
+                    image1_face_rois: _,
+                    image2_face_rois: _,
                     best_similarity,
                     processing_time,
                 } => {
diff --git a/src/gui/bridge.rs b/src/gui/bridge.rs
index beece2e..5b28770 100644
--- a/src/gui/bridge.rs
+++ b/src/gui/bridge.rs
@@ -2,7 +2,7 @@ use std::path::PathBuf;
 
 use crate::errors;
 use crate::facedet::{FaceDetectionConfig, FaceDetector, retinaface};
-use crate::faceembed::{FaceNetEmbedder, facenet};
+use crate::faceembed::facenet;
 use crate::gui::app::{ComparisonResult, DetectionResult, ExecutorType};
 use bounding_box::Aabb2;
 use bounding_box::roi::MultiRoi as _;
@@ -70,11 +70,19 @@ impl FaceDetectionBridge {
         )
         .await
         {
-            Ok((image1_faces, image2_faces, best_similarity)) => {
+            Ok((
+                image1_faces,
+                image2_faces,
+                image1_face_rois,
+                image2_face_rois,
+                best_similarity,
+            )) => {
                 let processing_time = start_time.elapsed().as_secs_f64();
                 ComparisonResult::Success {
                     image1_faces,
                     image2_faces,
+                    image1_face_rois,
+                    image2_face_rois,
                     best_similarity,
                     processing_time,
                 }
@@ -180,53 +188,75 @@ impl FaceDetectionBridge {
         threshold: f32,
         nms_threshold: f32,
         executor_type: ExecutorType,
-    ) -> Result<(usize, usize, f32), Box<dyn std::error::Error + Send + Sync>> {
+    ) -> Result<
+        (usize, usize, Vec<Array3<u8>>, Vec<Array3<u8>>, f32),
+        Box<dyn std::error::Error + Send + Sync>,
+    > {
         // Create detector and embedder, detect faces and generate embeddings
-        let (faces1, faces2, best_similarity) = match executor_type {
-            ExecutorType::MnnCpu | ExecutorType::MnnMetal | ExecutorType::MnnCoreML => {
-                let forward_type = match executor_type {
-                    ExecutorType::MnnCpu => mnn::ForwardType::CPU,
-                    ExecutorType::MnnMetal => mnn::ForwardType::Metal,
-                    ExecutorType::MnnCoreML => mnn::ForwardType::CoreML,
-                    _ => unreachable!(),
-                };
+        let (image1_faces, image2_faces, image1_rois, image2_rois, best_similarity) =
+            match executor_type {
+                ExecutorType::MnnCpu | ExecutorType::MnnMetal | ExecutorType::MnnCoreML => {
+                    let forward_type = match executor_type {
+                        ExecutorType::MnnCpu => mnn::ForwardType::CPU,
+                        ExecutorType::MnnMetal => mnn::ForwardType::Metal,
+                        ExecutorType::MnnCoreML => mnn::ForwardType::CoreML,
+                        _ => unreachable!(),
+                    };
 
-                let mut detector = retinaface::mnn::FaceDetection::builder(RETINAFACE_MODEL_MNN)
-                    .map_err(|e| format!("Failed to create MNN detector: {}", e))?
-                    .with_forward_type(forward_type.clone())
-                    .build()
-                    .map_err(|e| format!("Failed to build MNN detector: {}", e))?;
+                    let mut detector =
+                        retinaface::mnn::FaceDetection::builder(RETINAFACE_MODEL_MNN)
+                            .map_err(|e| format!("Failed to create MNN detector: {}", e))?
+                            .with_forward_type(forward_type.clone())
+                            .build()
+                            .map_err(|e| format!("Failed to build MNN detector: {}", e))?;
 
-                let mut embedder = facenet::mnn::EmbeddingGenerator::builder(FACENET_MODEL_MNN)
-                    .map_err(|e| format!("Failed to create MNN embedder: {}", e))?
-                    .with_forward_type(forward_type)
-                    .build()
-                    .map_err(|e| format!("Failed to build MNN embedder: {}", e))?;
+                    let mut embedder = facenet::mnn::EmbeddingGenerator::builder(FACENET_MODEL_MNN)
+                        .map_err(|e| format!("Failed to create MNN embedder: {}", e))?
+                        .with_forward_type(forward_type)
+                        .build()
+                        .map_err(|e| format!("Failed to build MNN embedder: {}", e))?;
 
-                let img_1 = run_detection(
-                    image1_path,
-                    &mut detector,
-                    &mut embedder,
-                    threshold,
-                    nms_threshold,
-                    2,
-                )?;
-                let img_2 = run_detection(
-                    image2_path,
-                    &mut detector,
-                    &mut embedder,
-                    threshold,
-                    nms_threshold,
-                    2,
-                )?;
+                    let img_1 = run_detection(
+                        image1_path,
+                        &mut detector,
+                        &mut embedder,
+                        threshold,
+                        nms_threshold,
+                        2,
+                    )?;
+                    let img_2 = run_detection(
+                        image2_path,
+                        &mut detector,
+                        &mut embedder,
+                        threshold,
+                        nms_threshold,
+                        2,
+                    )?;
 
-                let best_similarity = compare_faces(&img_1.embeddings, &img_2.embeddings)?;
-                (img_1, img_2, best_similarity)
-            }
-            ExecutorType::OnnxCpu => unimplemented!(),
-        };
+                    let image1_rois = img_1.rois;
+                    let image2_rois = img_2.rois;
+                    let image1_bbox_len = img_1.bbox.len();
+                    let image2_bbox_len = img_2.bbox.len();
+                    let best_similarity = compare_faces(&img_1.embeddings, &img_2.embeddings)?;
 
-        Ok((faces1.bbox.len(), faces2.bbox.len(), best_similarity))
+                    (
+                        image1_bbox_len,
+                        image2_bbox_len,
+                        image1_rois,
+                        image2_rois,
+                        best_similarity,
+                    )
+                }
+                ExecutorType::OnnxCpu => unimplemented!(),
+            };
+
+        Ok((
+            image1_faces,
+            image2_faces,
+            image1_rois,
+            image2_rois,
+            best_similarity,
+        ))
     }
 }
 
@@ -308,7 +338,7 @@ where
         .into_iter()
         .map(|roi| {
             roi.as_standard_layout()
-                .fast_resize(320, 320, &ResizeOptions::default())
+                .fast_resize(224, 224, &ResizeOptions::default())
                 .change_context(Error)
         })
         .collect::<Result<Vec<_>>>()?;
@@ -322,7 +352,7 @@ where
             let og_size = chunk.len();
             if chunk.len() < chunk_size {
                 tracing::warn!("Chunk size is less than 8, padding with zeros");
-                let zeros = Array3::zeros((320, 320, 3));
+                let zeros = Array3::zeros((224, 224, 3));
                 let chunk: Vec<_> = chunk
                     .iter()
                     .map(|arr| arr.reborrow())