From 7121d24a900ffa559920f211e3e52a273782a7c7 Mon Sep 17 00:00:00 2001 From: PEAandDA <1641300388@qq.com> Date: Mon, 22 Jul 2024 18:18:12 +0800 Subject: [PATCH] =?UTF-8?q?=E6=9B=B4=E6=96=B0Demo?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- demo/core/face_detection.py | 106 +++++++++++++++++++++++----------- demo/requirements.txt | 16 +++++ demo/weights/yolov10s_face.pt | Bin 0 -> 16522171 bytes 3 files changed, 89 insertions(+), 33 deletions(-) create mode 100644 demo/requirements.txt create mode 100644 demo/weights/yolov10s_face.pt diff --git a/demo/core/face_detection.py b/demo/core/face_detection.py index 1d64470..f4a13f1 100644 --- a/demo/core/face_detection.py +++ b/demo/core/face_detection.py @@ -1,58 +1,98 @@ +from ultralytics import YOLO import cv2 +import torch + class FaceDetector: - def __init__(self, cascade_path='haarcascade_frontalface_default.xml'): - self.face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + cascade_path) + def __init__(self, model_path='../weights/yolov10s_face.pt'): + try: + self.model = YOLO(model_path) + except FileNotFoundError: + print("ERROR: Could not load the YOLO model") + exit() + self.class_names_dict = self.model.model.names - def find_faces(self, img, draw=True): - gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) - faces = self.face_cascade.detectMultiScale(gray, 1.3, 5) + def find_faces(self, img): + original_img = img.copy() + + results = self.model(img, verbose=False)[0] + detections = results.boxes.data + + face_detections = [] + other_detections = [] + bboxs = [] + + for detection in detections: + x1, y1, x2, y2, confidence, class_id = detection + x1, y1, x2, y2 = map(int, [x1, y1, x2, y2]) + class_id = int(class_id) + + # Convert to xywh format + w = x2 - x1 + h = y2 - y1 + bboxs.append([class_id, x1, y1, w, h, confidence]) + + if self.class_names_dict[class_id] == 'face': + face_detections.append((x1, y1, x2, y2, confidence)) + else: + other_detections.append((x1, y1, x2, y2, class_id)) bboxs = [] - for i, (x, y, w, h) in enumerate(faces): - bbox = (x, y, w, h) - bboxs.append([i, bbox, None]) # 'None' 用于保持与原代码结构一致,因为OpenCV不提供置信度分数 - if draw: - img = self.fancy_draw(img, bbox) + # Find the largest face + if face_detections: + largest_face = max(face_detections, key=lambda x: (x[2] - x[0]) * (x[3] - x[1])) + bboxs.append(largest_face) + original_img = self.draw_face(original_img, largest_face) - return img, bboxs - def fancy_draw(self, img, bbox, l=30, t=5, rt=1): - x, y, w, h = bbox - x1, y1 = x + w, y + h - # 绘制矩形 - cv2.rectangle(img, bbox, (0, 255, 255), rt) + # Modify pixel values for other facial features + for x1, y1, x2, y2, _ in other_detections: + img[y1:y2, x1:x2] = 125 - # 绘制角落 - # 左上角 - cv2.line(img, (x, y), (x+l, y), (255, 0, 255), t) - cv2.line(img, (x, y), (x, y+l), (255, 0, 255), t) - # 右上角 - cv2.line(img, (x1, y), (x1-l, y), (255, 0, 255), t) - cv2.line(img, (x1, y), (x1, y+l), (255, 0, 255), t) - # 左下角 - cv2.line(img, (x, y1), (x+l, y1), (255, 0, 255), t) - cv2.line(img, (x, y1), (x, y1-l), (255, 0, 255), t) - # 右下角 - cv2.line(img, (x1, y1), (x1-l, y1), (255, 0, 255), t) - cv2.line(img, (x1, y1), (x1, y1-l), (255, 0, 255), t) + return original_img, img, bboxs + + def draw_face(self, img, face, l=30, t=2, rt=1): + x1, y1, x2, y2, confidence = face + + # Draw rectangle + cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 255), rt) + + # Draw label + # label = f"Face {confidence:.2f}" + # cv2.putText(img, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 255), 2) + + # Draw corners + # Top left + cv2.line(img, (x1, y1), (x1 + l, y1), (255, 0, 255), t) + cv2.line(img, (x1, y1), (x1, y1 + l), (255, 0, 255), t) + # Top right + cv2.line(img, (x2, y1), (x2 - l, y1), (255, 0, 255), t) + cv2.line(img, (x2, y1), (x2, y1 + l), (255, 0, 255), t) + # Bottom left + cv2.line(img, (x1, y2), (x1 + l, y2), (255, 0, 255), t) + cv2.line(img, (x1, y2), (x1, y2 - l), (255, 0, 255), t) + # Bottom right + cv2.line(img, (x2, y2), (x2 - l, y2), (255, 0, 255), t) + cv2.line(img, (x2, y2), (x2, y2 - l), (255, 0, 255), t) return img + # 使用示例 if __name__ == "__main__": + print(torch.cuda.is_available()) detector = FaceDetector() cap = cv2.VideoCapture(0) # 使用默认摄像头 while True: - success, img = cap.read() - img, bboxs = detector.find_faces(img) + success, frame = cap.read() + iii, img, bboxs = detector.find_faces(frame) - cv2.imshow("Image", img) + cv2.imshow("Image", iii) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() - cv2.destroyAllWindows() \ No newline at end of file + cv2.destroyAllWindows() diff --git a/demo/requirements.txt b/demo/requirements.txt new file mode 100644 index 0000000..6c49d94 --- /dev/null +++ b/demo/requirements.txt @@ -0,0 +1,16 @@ +PyQt5==5.15.9 +matplotlib==3.8.3 +numpy==1.24.3 +opencv-contrib-python==4.9.0.80 +opencv-python==4.9.0.80 +opencv-python-headless==4.9.0.80 +pillow==10.3.0 +tqdm==4.66.2 +scikit-learn==1.4.1.post1 +scipy==1.12.0 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