Prepare public release v0.1.0

linux-hello-daemon/tests/onnx_integration.rs

@@ -19,7 +19,7 @@ use linux_hello_daemon::onnx::{
     FaceAligner, OnnxEmbeddingExtractor, OnnxFaceDetector, OnnxModelConfig, OnnxPipeline,
     REFERENCE_LANDMARKS_112,
 };
-use linux_hello_daemon::{FaceDetect, EmbeddingExtractor};
+use linux_hello_daemon::{EmbeddingExtractor, FaceDetect};
 use std::path::Path;
 
 /// Model directory path
@@ -118,10 +118,10 @@ mod alignment_tests {
             &image,
             TEST_WIDTH,
             TEST_HEIGHT,
-            100,  // face_x
-            100,  // face_y
-            200,  // face_width
-            200,  // face_height
+            100, // face_x
+            100, // face_y
+            200, // face_width
+            200, // face_height
         );
 
         assert!(result.is_ok());
@@ -251,7 +251,11 @@ mod integration_with_models {
         }
 
         let result = OnnxFaceDetector::load(model_path("retinaface.onnx"));
-        assert!(result.is_ok(), "Failed to load detection model: {:?}", result.err());
+        assert!(
+            result.is_ok(),
+            "Failed to load detection model: {:?}",
+            result.err()
+        );
     }
 
     #[test]
@@ -263,7 +267,11 @@ mod integration_with_models {
         }
 
         let result = OnnxEmbeddingExtractor::load(model_path("mobilefacenet.onnx"));
-        assert!(result.is_ok(), "Failed to load embedding model: {:?}", result.err());
+        assert!(
+            result.is_ok(),
+            "Failed to load embedding model: {:?}",
+            result.err()
+        );
     }
 
     #[test]
@@ -274,13 +282,17 @@ mod integration_with_models {
             return;
         }
 
-        let detector = OnnxFaceDetector::load(model_path("retinaface.onnx"))
-            .expect("Failed to load detector");
+        let detector =
+            OnnxFaceDetector::load(model_path("retinaface.onnx")).expect("Failed to load detector");
 
         let image = create_test_image(TEST_WIDTH, TEST_HEIGHT);
         let detections = detector.detect(&image, TEST_WIDTH, TEST_HEIGHT);
 
-        assert!(detections.is_ok(), "Detection failed: {:?}", detections.err());
+        assert!(
+            detections.is_ok(),
+            "Detection failed: {:?}",
+            detections.err()
+        );
         // Note: synthetic image may or may not trigger detections
     }
 
@@ -299,14 +311,22 @@ mod integration_with_models {
         let face_data = vec![128u8; 112 * 112];
         let result = extractor.extract_from_bytes(&face_data, 112, 112);
 
-        assert!(result.is_ok(), "Embedding extraction failed: {:?}", result.err());
+        assert!(
+            result.is_ok(),
+            "Embedding extraction failed: {:?}",
+            result.err()
+        );
 
         let embedding = result.unwrap();
         assert_eq!(embedding.len(), extractor.embedding_dimension());
 
         // Check embedding is normalized (L2 norm should be ~1)
         let norm: f32 = embedding.iter().map(|x| x * x).sum::<f32>().sqrt();
-        assert!((norm - 1.0).abs() < 0.1, "Embedding not normalized: norm = {}", norm);
+        assert!(
+            (norm - 1.0).abs() < 0.1,
+            "Embedding not normalized: norm = {}",
+            norm
+        );
     }
 
     #[test]
@@ -326,7 +346,11 @@ mod integration_with_models {
         let image = create_test_image(TEST_WIDTH, TEST_HEIGHT);
         let results = pipeline.process_frame(&image, TEST_WIDTH, TEST_HEIGHT);
 
-        assert!(results.is_ok(), "Pipeline processing failed: {:?}", results.err());
+        assert!(
+            results.is_ok(),
+            "Pipeline processing failed: {:?}",
+            results.err()
+        );
     }
 
     #[test]
@@ -343,9 +367,11 @@ mod integration_with_models {
         // Same face should produce similar embeddings
         let face_data = vec![128u8; 112 * 112];
 
-        let embedding1 = extractor.extract_from_bytes(&face_data, 112, 112)
+        let embedding1 = extractor
+            .extract_from_bytes(&face_data, 112, 112)
             .expect("First extraction failed");
-        let embedding2 = extractor.extract_from_bytes(&face_data, 112, 112)
+        let embedding2 = extractor
+            .extract_from_bytes(&face_data, 112, 112)
             .expect("Second extraction failed");
 
         // Compute cosine similarity
@@ -377,9 +403,11 @@ mod integration_with_models {
         let face1 = vec![100u8; 112 * 112];
         let face2 = vec![200u8; 112 * 112];
 
-        let embedding1 = extractor.extract_from_bytes(&face1, 112, 112)
+        let embedding1 = extractor
+            .extract_from_bytes(&face1, 112, 112)
             .expect("First extraction failed");
-        let embedding2 = extractor.extract_from_bytes(&face2, 112, 112)
+        let embedding2 = extractor
+            .extract_from_bytes(&face2, 112, 112)
             .expect("Second extraction failed");
 
         // Compute cosine similarity