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chore: Code style formatting changes

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yakhyo
2025-11-26 00:05:24 +09:00
parent 0771a7959a
commit 84cda5f56c
12 changed files with 172 additions and 77 deletions
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10
scripts/batch_process.py
View File

@@ -33,7 +33,15 @@ def process_image(detector, image_path: Path, output_path: Path, threshold: floa
landmarks = [f["landmarks"] for f in faces]
draw_detections(image, bboxes, scores, landmarks, vis_threshold=threshold)
cv2.putText(image, f"Faces: {len(faces)}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
cv2.putText(
image,
f"Faces: {len(faces)}",
(10, 30),
cv2.FONT_HERSHEY_SIMPLEX,
1,
(0, 255, 0),
2,
)
cv2.imwrite(str(output_path), image)
return len(faces)

18
scripts/run_age_gender.py
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@@ -21,7 +21,13 @@ def draw_age_gender_label(image, bbox, gender: str, age: int):
cv2.putText(image, text, (x1 + 5, y1 - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 0), 2)
def process_image(detector, age_gender, image_path: str, save_dir: str = "outputs", threshold: float = 0.6):
def process_image(
detector,
age_gender,
image_path: str,
save_dir: str = "outputs",
threshold: float = 0.6,
):
image = cv2.imread(image_path)
if image is None:
print(f"Error: Failed to load image from '{image_path}'")
@@ -75,7 +81,15 @@ def run_webcam(detector, age_gender, threshold: float = 0.6):
gender, age = age_gender.predict(frame, face["bbox"]) # predict per face
draw_age_gender_label(frame, face["bbox"], gender, age)
cv2.putText(frame, f"Faces: {len(faces)}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
cv2.putText(
frame,
f"Faces: {len(faces)}",
(10, 30),
cv2.FONT_HERSHEY_SIMPLEX,
1,
(0, 255, 0),
2,
)
cv2.imshow("Age & Gender Detection", frame)
if cv2.waitKey(1) & 0xFF == ord("q"):

10
scripts/run_detection.py
View File

@@ -53,7 +53,15 @@ def run_webcam(detector, threshold: float = 0.6):
landmarks = [f["landmarks"] for f in faces]
draw_detections(frame, bboxes, scores, landmarks, vis_threshold=threshold)
cv2.putText(frame, f"Faces: {len(faces)}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
cv2.putText(
frame,
f"Faces: {len(faces)}",
(10, 30),
cv2.FONT_HERSHEY_SIMPLEX,
1,
(0, 255, 0),
2,
)
cv2.imshow("Face Detection", frame)
if cv2.waitKey(1) & 0xFF == ord("q"):

7
scripts/run_face_search.py
View File

@@ -76,7 +76,12 @@ def main():
parser.add_argument("--image", type=str, required=True, help="Reference face image")
parser.add_argument("--threshold", type=float, default=0.4, help="Match threshold")
parser.add_argument("--detector", type=str, default="scrfd", choices=["retinaface", "scrfd"])
parser.add_argument("--recognizer", type=str, default="arcface", choices=["arcface", "mobileface", "sphereface"])
parser.add_argument(
"--recognizer",
type=str,
default="arcface",
choices=["arcface", "mobileface", "sphereface"],
)
args = parser.parse_args()
detector = RetinaFace() if args.detector == "retinaface" else SCRFD()

20
scripts/run_landmarks.py
View File

@@ -34,7 +34,15 @@ def process_image(detector, landmarker, image_path: str, save_dir: str = "output
for x, y in landmarks.astype(int):
cv2.circle(image, (x, y), 1, (0, 255, 0), -1)
cv2.putText(image, f"Face {i + 1}", (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
cv2.putText(
image,
f"Face {i + 1}",
(x1, y1 - 10),
cv2.FONT_HERSHEY_SIMPLEX,
0.5,
(0, 255, 0),
2,
)
os.makedirs(save_dir, exist_ok=True)
output_path = os.path.join(save_dir, f"{Path(image_path).stem}_landmarks.jpg")
@@ -67,7 +75,15 @@ def run_webcam(detector, landmarker):
for x, y in landmarks.astype(int):
cv2.circle(frame, (x, y), 1, (0, 255, 0), -1)
cv2.putText(frame, f"Faces: {len(faces)}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
cv2.putText(
frame,
f"Faces: {len(faces)}",
(10, 30),
cv2.FONT_HERSHEY_SIMPLEX,
1,
(0, 255, 0),
2,
)
cv2.imshow("106-Point Landmarks", frame)
if cv2.waitKey(1) & 0xFF == ord("q"):

7
scripts/run_recognition.py
View File

@@ -79,7 +79,12 @@ def main():
parser.add_argument("--image2", type=str, help="Second image for comparison")
parser.add_argument("--threshold", type=float, default=0.35, help="Similarity threshold")
parser.add_argument("--detector", type=str, default="retinaface", choices=["retinaface", "scrfd"])
parser.add_argument("--recognizer", type=str, default="arcface", choices=["arcface", "mobileface", "sphereface"])
parser.add_argument(
"--recognizer",
type=str,
default="arcface",
choices=["arcface", "mobileface", "sphereface"],
)
args = parser.parse_args()
detector = RetinaFace() if args.detector == "retinaface" else SCRFD()

18
scripts/run_video_detection.py
View File

@@ -11,7 +11,13 @@ from uniface import SCRFD, RetinaFace
from uniface.visualization import draw_detections
def process_video(detector, input_path: str, output_path: str, threshold: float = 0.6, show_preview: bool = False):
def process_video(
detector,
input_path: str,
output_path: str,
threshold: float = 0.6,
show_preview: bool = False,
):
cap = cv2.VideoCapture(input_path)
if not cap.isOpened():
print(f"Error: Cannot open video file '{input_path}'")
@@ -51,7 +57,15 @@ def process_video(detector, input_path: str, output_path: str, threshold: float
landmarks = [f["landmarks"] for f in faces]
draw_detections(frame, bboxes, scores, landmarks, vis_threshold=threshold)
cv2.putText(frame, f"Faces: {len(faces)}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
cv2.putText(
frame,
f"Faces: {len(faces)}",
(10, 30),
cv2.FONT_HERSHEY_SIMPLEX,
1,
(0, 255, 0),
2,
)
out.write(frame)
if show_preview: