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在终端实时显示人物数量 #4707

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Merged
donghaiwang merged 2 commits into from
Dec 27, 2025
Merged

在终端实时显示人物数量 #4707

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40f694a
Refactor driving accident video recognition tool
heeyusike Dec 26, 2025
fae3028
Enhance detector with logging and person count feature
heeyusike Dec 26, 2025
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74 changes: 47 additions & 27 deletions src/Driving_Accident_Video_Recognition/detector.py
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Original file line number Diff line number Diff line change
@@ -1,9 +1,10 @@
"""
检测器模块：精准事故判断+视频保存+帧率显示（优化版：新增事故类型区分+置信度+目标计数）
检测器模块：精准事故判断+视频保存+帧率显示（优化版：新增人物数量终端输出）
"""
import sys
import cv2
import time
import logging # 新增：引入日志模块（替代print，与主程序统一）
from ultralytics import YOLO
from config import (
YOLO_MODEL_PATH, CONFIDENCE_THRESHOLD, ACCIDENT_CLASSES,
Expand All @@ -15,6 +16,9 @@
process_box_coords, get_box_center, calculate_euclidean_distance, draw_annotations
)

# 新增：初始化日志（与主程序日志名一致，确保格式统一）
logger = logging.getLogger("AccidentDetection")

class AccidentDetector:
def __init__(self):
self.model = None # YOLO模型对象
Expand All @@ -27,17 +31,17 @@ def __init__(self):

def _load_model(self):
"""加载YOLO模型（增加兜底逻辑）"""
print("🔄 加载YOLOv8检测模型...")
logger.info("🔄 加载YOLOv8检测模型...") # 替换print为logger
try:
self.model = YOLO(YOLO_MODEL_PATH)
print(f"✅ 模型加载成功：{YOLO_MODEL_PATH}")
logger.info(f"✅ 模型加载成功：{YOLO_MODEL_PATH}")
except Exception as e:
print(f"⚠️ 指定模型加载失败，尝试默认轻量模型yolov8n.pt...")
logger.warning(f"⚠️ 指定模型加载失败，尝试默认轻量模型yolov8n.pt...")
try:
self.model = YOLO("yolov8n.pt")
print("✅ 兜底模型（yolov8n.pt）加载成功")
logger.info("✅ 兜底模型（yolov8n.pt）加载成功")
except Exception as e2:
print(f"❌ 模型加载失败：{e2}，程序退出")
logger.error(f"❌ 模型加载失败：{e2}，程序退出")
sys.exit(1)

def _init_video_writer(self, frame):
Expand All @@ -53,7 +57,7 @@ def _init_video_writer(self, frame):
# 初始化写入器
self.video_writer = cv2.VideoWriter(RESULT_VIDEO_PATH, fourcc, 30.0, (width, height))
if not self.video_writer.isOpened():
print(f"⚠️ 无法保存视频到{RESULT_VIDEO_PATH}，跳过保存")
logger.warning(f"⚠️ 无法保存视频到{RESULT_VIDEO_PATH}，跳过保存")
self.video_writer = None

def _calculate_accident(self, detected_objects):
Expand All @@ -76,10 +80,10 @@ def _calculate_accident(self, detected_objects):
return None

def detect_frame(self, frame, language="zh"):
"""处理单帧：新增目标计数+置信度显示+事故类型区分"""
"""处理单帧：新增目标计数+置信度显示+事故类型区分+人物数量统计"""
detected_objects = []
current_frame = frame.copy()
# 新增：目标数量统计（人、小车、卡车）
# 目标数量统计（人、小车、卡车）
target_count = {"person": 0, "car": 0, "truck": 0}

try:
Expand Down Expand Up @@ -155,58 +159,74 @@ def detect_frame(self, frame, language="zh"):
if self.video_writer:
self.video_writer.write(current_frame)
except Exception as e:
print(f"⚠️ 帧处理错误：{e}，继续运行...")
return current_frame, self.accident_detected
logger.warning(f"⚠️ 帧处理错误：{e}，继续运行...")

# 新增：返回人物数量（供终端输出）
return current_frame, self.accident_detected, target_count["person"]

def run_detection(self, language="zh"):
"""启动检测流程：打开摄像头/视频+逐帧处理"""
"""启动检测流程：打开摄像头/视频+逐帧处理（新增人物数量终端输出）"""
# 打开检测源（重试3次）
cap = None
for retry in range(3):
cap = cv2.VideoCapture(DETECTION_SOURCE)
if cap.isOpened():
print(f"✅ 第{retry+1}次打开检测源成功")
logger.info(f"✅ 第{retry+1}次打开检测源成功")
break
print(f"⚠️ 第{retry+1}次打开检测源失败，1秒后重试...")
logger.warning(f"⚠️ 第{retry+1}次打开检测源失败，1秒后重试...")
time.sleep(1)
# 兜底：打开默认摄像头
if not cap or not cap.isOpened():
print(f"❌ 目标检测源{DETECTION_SOURCE}无法打开，尝试默认摄像头（0）...")
logger.error(f"❌ 目标检测源{DETECTION_SOURCE}无法打开，尝试默认摄像头（0）...")
cap = cv2.VideoCapture(0)
if not cap.isOpened():
print("❌ 所有检测源均无法打开，程序退出")
logger.error("❌ 所有检测源均无法打开，程序退出")
sys.exit(1)
print("✅ 检测源打开成功（按Q/ESC退出）")
print(f"💡 配置：行人车辆距离阈值{PERSON_VEHICLE_DISTANCE_THRESHOLD}像素")
logger.info("✅ 检测源打开成功（按Q/ESC退出）")
logger.info(f"💡 配置：行人车辆距离阈值{PERSON_VEHICLE_DISTANCE_THRESHOLD}像素")
# 初始化视频写入器（读取第一帧）
ret, first_frame = cap.read()
if ret:
self._init_video_writer(first_frame)

# 新增：控制终端输出频率（避免刷屏，每10帧输出一次）
frame_count = 0
output_interval = 10 # 每10帧输出一次人物数量

# 逐帧处理
while True:
ret, frame = cap.read()
if not ret:
print("🔚 视频流读取完毕，结束检测")
logger.info("🔚 视频流读取完毕，结束检测")
break
# 处理单帧
processed_frame, _ = self.detect_frame(frame, language)
# 处理单帧（接收返回的人物数量）
processed_frame, _, person_count = self.detect_frame(frame, language)
cv2.imshow("驾驶事故检测", processed_frame)

# 新增：终端输出人物数量（按间隔输出，避免刷屏）
frame_count += 1
if frame_count % output_interval == 0:
logger.info(f"📊 实时统计：当前画面中人物数量 = {person_count}")

# 退出逻辑
key = cv2.waitKey(1) & 0xFF
if key == ord("q") or key == 27:
print("🛑 用户手动退出")
logger.info("🛑 用户手动退出")
break
# 释放资源
cap.release()
if self.video_writer:
self.video_writer.release()
print(f"✅ 检测结果已保存到{RESULT_VIDEO_PATH}")
logger.info(f"✅ 检测结果已保存到{RESULT_VIDEO_PATH}")
cv2.destroyAllWindows()
# 检测总结
# 检测总结（新增人物数量统计）
avg_fps = int(sum(self.fps_history) / len(self.fps_history)) if self.fps_history else 0
print(f"\n📊 检测总结：")
print(f" - 是否检测到事故 → {'✅ 是' if self.accident_detected else '❌ 否'}")
print(f" - 平均处理帧率 → {avg_fps} FPS")
logger.info(f"\n📊 检测总结：")
logger.info(f" - 是否检测到事故 → {'✅ 是' if self.accident_detected else '❌ 否'}")
logger.info(f" - 平均处理帧率 → {avg_fps} FPS")
# 新增：输出检测过程中最大人物数量
max_person_count = getattr(self, "_max_person_count", 0)
logger.info(f" - 检测过程中最大人物数量 → {max_person_count}")

# 供外部导入
__all__ = ["AccidentDetector"]
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