feat: Add yolov5n, update docs and ruff code format

scripts/batch_process.py

@@ -31,7 +31,9 @@ def process_image(detector, image_path: Path, output_path: Path, threshold: floa
     bboxes = [f['bbox'] for f in faces]
     scores = [f['confidence'] for f in faces]
     landmarks = [f['landmarks'] for f in faces]
-    draw_detections(image=image, bboxes=bboxes, scores=scores, landmarks=landmarks, vis_threshold=threshold, fancy_bbox=True)
+    draw_detections(
+        image=image, bboxes=bboxes, scores=scores, landmarks=landmarks, vis_threshold=threshold, fancy_bbox=True
+    )
 
     cv2.putText(
         image,

scripts/run_age_gender.py

@@ -43,7 +43,9 @@ def process_image(
     bboxes = [f['bbox'] for f in faces]
     scores = [f['confidence'] for f in faces]
     landmarks = [f['landmarks'] for f in faces]
-    draw_detections(image=image, bboxes=bboxes, scores=scores, landmarks=landmarks, vis_threshold=threshold, fancy_bbox=True)
+    draw_detections(
+        image=image, bboxes=bboxes, scores=scores, landmarks=landmarks, vis_threshold=threshold, fancy_bbox=True
+    )
 
     for i, face in enumerate(faces):
         gender_id, age = age_gender.predict(image, face['bbox'])

scripts/run_detection.py

@@ -51,7 +51,15 @@ def run_webcam(detector, threshold: float = 0.6):
         bboxes = [f['bbox'] for f in faces]
         scores = [f['confidence'] for f in faces]
         landmarks = [f['landmarks'] for f in faces]
-        draw_detections(image=frame, bboxes=bboxes, scores=scores, landmarks=landmarks, vis_threshold=threshold, draw_score=True, fancy_bbox=True)
+        draw_detections(
+            image=frame,
+            bboxes=bboxes,
+            scores=scores,
+            landmarks=landmarks,
+            vis_threshold=threshold,
+            draw_score=True,
+            fancy_bbox=True,
+        )
 
         cv2.putText(
             frame,
@@ -90,7 +98,7 @@ def main():
     else:
         from uniface.constants import YOLOv5FaceWeights
 
-        detector = YOLOv5Face(model_name=YOLOv5FaceWeights.YOLOV5M)
+        detector = YOLOv5Face(model_name=YOLOv5FaceWeights.YOLOV5N)
 
     if args.webcam:
         run_webcam(detector, args.threshold)

scripts/run_emotion.py

@@ -42,7 +42,9 @@ def process_image(
     bboxes = [f['bbox'] for f in faces]
     scores = [f['confidence'] for f in faces]
     landmarks = [f['landmarks'] for f in faces]
-    draw_detections(image=image, bboxes=bboxes, scores=scores, landmarks=landmarks, vis_threshold=threshold, fancy_bbox=True)
+    draw_detections(
+        image=image, bboxes=bboxes, scores=scores, landmarks=landmarks, vis_threshold=threshold, fancy_bbox=True
+    )
 
     for i, face in enumerate(faces):
         emotion, confidence = emotion_predictor.predict(image, face['landmarks'])

scripts/run_face_analyzer.py

@@ -82,7 +82,7 @@ def process_image(analyzer, image_path: str, save_dir: str = 'outputs', show_sim
     bboxes = [f.bbox for f in faces]
     scores = [f.confidence for f in faces]
     landmarks = [f.landmarks for f in faces]
-    draw_detections(image=image, bboxes=bboxes, scores=scores, landmarks=landmarks,fancy_bbox=True)
+    draw_detections(image=image, bboxes=bboxes, scores=scores, landmarks=landmarks, fancy_bbox=True)
 
     for i, face in enumerate(faces, 1):
         draw_face_info(image, face, i)

scripts/run_video_detection.py

@@ -55,7 +55,9 @@ def process_video(
         bboxes = [f['bbox'] for f in faces]
         scores = [f['confidence'] for f in faces]
         landmarks = [f['landmarks'] for f in faces]
-        draw_detections(image=frame, bboxes=bboxes, scores=scores, landmarks=landmarks, vis_threshold=threshold, fancy_bbox=True)
+        draw_detections(
+            image=frame, bboxes=bboxes, scores=scores, landmarks=landmarks, vis_threshold=threshold, fancy_bbox=True
+        )
 
         cv2.putText(
             frame,