diff --git a/res/eyes_svm_burns_model.json b/res/eyes_svm_burns_model.json
index 48be182..e05a29e 100644
Binary files a/res/eyes_svm_burns_model.json and b/res/eyes_svm_burns_model.json differ
diff --git a/src/classifier/svm.rs b/src/classifier/svm.rs
index 15d397e..931b1ce 100644
--- a/src/classifier/svm.rs
+++ b/src/classifier/svm.rs
@@ -5,7 +5,7 @@ use object_detector_rust::{
     classifier::Classifier, predictable::Predictable, trainable::Trainable,
     window_generator::PyramidWindow,
 };
-use serde::{Serialize, Deserialize};
+use serde::{Deserialize, Serialize};
 use svm_burns::{svm::SVM, Parameters, RBFKernel, SVC};
 
 use crate::HogDetector;
@@ -50,7 +50,10 @@ impl Trainable<f32, usize> for SVMClassifier {
             .map(|row| row.iter().map(|&elem| elem as f64).collect())
             .collect();
 
-        let y_vec: Vec<i32> = y.iter().map(|&elem| elem as i32).collect();
+        let y_vec: Vec<i32> = y
+            .iter()
+            .map(|&elem| if elem > 0 { 1 } else { -1 })
+            .collect();
 
         let mut parameters = Parameters::default();
         parameters.with_kernel(Box::new(RBFKernel::new(0.7)));
diff --git a/src/wasm/hogdetector_js.rs b/src/wasm/hogdetector_js.rs
index 6958e93..3a3c282 100644
--- a/src/wasm/hogdetector_js.rs
+++ b/src/wasm/hogdetector_js.rs
@@ -1,5 +1,5 @@
-use crate::classifier::BayesClassifier;
 use crate::classifier::svm::SVMClassifier;
+use crate::classifier::BayesClassifier;
 use crate::detection_filter::{DetectionFilter, TrackerFilter};
 use crate::detector::visualize_detections;
 use crate::hogdetector::HogDetectorTrait;
@@ -98,8 +98,7 @@ impl HogDetectorJS {
 
     pub fn init_svm_classifier(&self) {
         let hog = {
-            let mut model: HogDetector<f32, usize, SVMClassifier, _> =
-                HogDetector::default();
+            let mut model: HogDetector<f32, usize, SVMClassifier, _> = HogDetector::default();
             let file = Cursor::new(include_bytes!("../../res/eyes_svm_burns_model.json"));
             model.load(file).unwrap();
             model