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创建网站是怎么赚钱,网站设计标题,网站模板交易,厦门做网站设计经过优化后#xff0c;稳定在60ms#xff0c;不卡顿import cv2 from ultralytics import solutions import torch # ✅ 必须在文件顶部 新增导入torch#xff01;#xff01;#xff01; import gc # ✅ 必须在文件顶部 新增导入gc#xff01;#xff01;#xff01…经过优化后稳定在60ms不卡顿import cv2 from ultralytics import solutions import torch # ✅ 必须在文件顶部 新增导入torch import gc # ✅ 必须在文件顶部 新增导入gc def open_iphone_camera_with_cv(): 主函数找到并打开iPhone摄像头 print(正在检测iPhone摄像头...\n) # for i in range(5): cap cv2.VideoCapture(0) if cap.isOpened(): print(打开默认摄像头 (索引0)) # 强制开启硬件加速解码M1 Metal cap.set(cv2.CAP_PROP_HW_ACCELERATION, cv2.VIDEO_ACCELERATION_ANY) # 开启帧缓冲区优化降低延迟 cap.set(cv2.CAP_PROP_BUFFERSIZE, 1) cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640) cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480) region_points [(20, 400), (1080, 400), (1080, 360), (20, 360)] # w, h, fps (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS)) # video_writer cv2.VideoWriter(object_counting_output.avi, cv2.VideoWriter_fourcc(*mp4v), fps, (w, h)) counter solutions.ObjectCounter( showFalse, # display the output regionregion_points, # pass region points modelyolo26x.pt, # modelyolo26n-obb.pt for object counting with OBB model. devicemps, halfFalse, conf0.3, # 置信度调高一点减少无效检测加速推理 iou0.45, # NMS IOU阈值 max_det50, # 每张图像的最大检测数量 verboseTrue, # 是否打印详细信息 # save_resultsTrue, # 是否保存结果到文件 # classes[0, 2], # count specific classes, e.g., person and car with the COCO pretrained model. trackerbotsort.yaml, # choose trackers, e.g., bytetrack.yaml ) while True: ret, frame cap.read() if ret: frame_corrected cv2.flip(frame, 1) results counter(frame_corrected) # 显存内存清理根治耗时上涨 try: torch.mps.empty_cache() except Exception: pass gc.collect() cv2.imshow(fCamera M2 Pro | 推理≈13ms 跟踪≈9ms | 按q退出, results.plot_im) if cv2.waitKey(1) 0xFF ord(q): break cv2.destroyAllWindows() cap.release() print(摄像头已关闭) else: print(无法打开摄像头请检查连接。) # 运行 if __name__ __main__: # 方法1自动检测并打开iPhone摄像头 open_iphone_camera_with_cv()