servius/face-detector
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refactor(gui): set fixed input dimensions for face detection

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uttarayan21
2025-08-21 18:52:58 +05:30
parent 3e14a16739
commit 0a5dbaaadc
1 changed files with 6 additions and 7 deletions
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13
src/gui/bridge.rs
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@@ -85,7 +85,6 @@ impl FaceDetectionBridge {
// Load the image // Load the image
let img = image::open(&image_path)?; let img = image::open(&image_path)?;
let img_rgb = img.to_rgb8(); let img_rgb = img.to_rgb8();
let (width, height) = img_rgb.dimensions();
// Convert to ndarray format // Convert to ndarray format
let image_array = img_rgb.as_ndarray()?; let image_array = img_rgb.as_ndarray()?;
@@ -94,8 +93,8 @@ impl FaceDetectionBridge {
let config = FaceDetectionConfig::default() let config = FaceDetectionConfig::default()
.with_threshold(threshold) .with_threshold(threshold)
.with_nms_threshold(nms_threshold) .with_nms_threshold(nms_threshold)
.with_input_width(width as usize) .with_input_width(1024)
.with_input_height(height as usize); .with_input_height(1024);
// Create detector and detect faces // Create detector and detect faces
let faces = match executor_type { let faces = match executor_type {
@@ -186,14 +185,14 @@ impl FaceDetectionBridge {
let config1 = FaceDetectionConfig::default() let config1 = FaceDetectionConfig::default()
.with_threshold(threshold) .with_threshold(threshold)
.with_nms_threshold(nms_threshold) .with_nms_threshold(nms_threshold)
.with_input_width(img1.width() as usize) .with_input_width(1024)
.with_input_height(img1.height() as usize); .with_input_height(1024);
let config2 = FaceDetectionConfig::default() let config2 = FaceDetectionConfig::default()
.with_threshold(threshold) .with_threshold(threshold)
.with_nms_threshold(nms_threshold) .with_nms_threshold(nms_threshold)
.with_input_width(img2.width() as usize) .with_input_width(1024)
.with_input_height(img2.height() as usize); .with_input_height(1024);
// Create detector and embedder, detect faces and generate embeddings // Create detector and embedder, detect faces and generate embeddings
let (faces1, faces2, best_similarity) = match executor_type { let (faces1, faces2, best_similarity) = match executor_type {