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if file == file_name: output_subdirectory = os.path.join(output_directory, subdirectory) os.makedirs(output_subdirectory, exist_ok=True) # 创建输出子文件夹 source_file = os.path.join(subdirectory_path, file) destination_file = os.path.join(output_subdirectory, file) shutil.copy(source_file, destination_file) print(f"已复制文件: {file} 到目录: {output_subdirectory}")

时间: 2024-04-13 07:28:52 浏览: 207
很抱歉,我之前的回答有误。在你的代码中,`file == file_name`这个条件是错误的,因为`file`是文件名,而`file_name`是不包括扩展名的文件名。你可以使用`os.path.splitext()`函数来获取文件名和扩展名,然后比较文件名是否相同。 以下是修正后的代码示例: ```python import os import shutil def get_files_with_same_name(directory, output_directory): # 获取目录下的所有文件夹 subdirectories = [name for name in os.listdir(directory) if os.path.isdir(os.path.join(directory, name))] for subdirectory in subdirectories: # 构建当前子文件夹的完整路径 subdirectory_path = os.path.join(directory, subdirectory) # 获取当前子文件夹下的所有文件 files = [name for name in os.listdir(subdirectory_path) if os.path.isfile(os.path.join(subdirectory_path, name))] # 使用字典来存储相同文件名的文件列表 files_dict = {} for file in files: file_name = os.path.splitext(file)[0] # 只获取文件名,不包括扩展名 if file_name not in files_dict: files_dict[file_name] = [] files_dict[file_name].append(file) # 将相同文件名的文件复制到输出目录中 for file_list in files_dict.values(): if len(file_list) > 1: output_subdirectory = os.path.join(output_directory, subdirectory) os.makedirs(output_subdirectory, exist_ok=True) # 创建输出子文件夹 for file in file_list: source_file = os.path.join(subdirectory_path, file) destination_file = os.path.join(output_subdirectory, file) shutil.copy(source_file, destination_file) print(f"已复制文件: {file} 到目录: {output_subdirectory}") # 指定目录和输出目录 directory = 'path/to/directory' output_directory = 'path/to/output_directory' # 调用函数获取相同文件名的文件并保存到指定文件夹 get_files_with_same_name(directory, output_directory) ``` 在修正后的代码中,我们将`file`的比较改为比较文件名(不包括扩展名),并遍历字典的值来获取相同文件名的文件列表。然后,将这些文件复制到指定的输出目录中的子文件夹中。 请确保在运行代码之前已经安装了必要的模块(os、shutil),并将目录路径替换为你自己的实际路径。
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# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license """ Run YOLOv5 detection inference on images, videos, directories, globs, YouTube, webcam, streams, etc. Usage - sources: $ python detect.py --weights yolov5s.pt --source 0 # webcam img.jpg # image vid.mp4 # video screen # screenshot path/ # directory list.txt # list of images list.streams # list of streams 'path/*.jpg' # glob 'https://youtu.be/LNwODJXcvt4' # YouTube 'rtsp://example.com/media.mp4' # RTSP, RTMP, HTTP stream Usage - formats: $ python detect.py --weights yolov5s.pt # PyTorch yolov5s.torchscript # TorchScript yolov5s.onnx # ONNX Runtime or OpenCV DNN with --dnn yolov5s_openvino_model # OpenVINO yolov5s.engine # TensorRT yolov5s.mlpackage # CoreML (macOS-only) yolov5s_saved_model # TensorFlow SavedModel yolov5s.pb # TensorFlow GraphDef yolov5s.tflite # TensorFlow Lite yolov5s_edgetpu.tflite # TensorFlow Edge TPU yolov5s_paddle_model # PaddlePaddle """ import argparse import csv import os import platform import sys from pathlib import Path import torch FILE = Path(__file__).resolve() ROOT = FILE.parents[0] # YOLOv5 root directory if str(ROOT) not in sys.path: sys.path.append(str(ROOT)) # add ROOT to PATH ROOT = Path(os.path.relpath(ROOT, Path.cwd())) # relative from ultralytics.utils.plotting import Annotator, colors, save_one_box from models.common import DetectMultiBackend from utils.dataloaders import IMG_FORMATS, VID_FORMATS, LoadImages, LoadScreenshots, LoadStreams from utils.general import ( LOGGER, Profile, check_file, check_img_size, check_imshow, check_requirements, colorstr, cv2, increment_path, non_max_suppression, print_args, scale_boxes, strip_optimizer, xyxy2xywh, ) from utils.torch_utils import select_device, smart_inference_mode # 新增:计算IOU函数 def calculate_iou(box1, box2): """计算两个边界框的IOU""" x1, y1, x2, y2 = box1 x1g, y1g, x2g, y2g = box2 # 计算交集区域 xA = max(x1, x1g) yA = max(y1, y1g) xB = min(x2, x2g) yB = min(y2, y2g) # 计算交集面积 inter_area = max(0, xB - xA + 1) * max(0, yB - yA + 1) # 计算并集面积 box1_area = (x2 - x1 + 1) * (y2 - y1 + 1) box2_area = (x2g - x1g + 1) * (y2g - y1g + 1) union_area = float(box1_area + box2_area - inter_area) # 计算IOU iou = inter_area / union_area return iou # 新增:计算准确率函数 def calculate_accuracy(gt_labels, pred_detections, iou_threshold=0.5): """计算目标检测的准确率""" correct_predictions = 0 total_gt_objects = 0 total_pred_objects = 0 for img_name in gt_labels: if img_name not in pred_detections: continue gt_boxes = gt_labels[img_name] pred_boxes = pred_detections[img_name] total_gt_objects += len(gt_boxes) total_pred_objects += len(pred_boxes) # 标记已匹配的真实标签 gt_matched = [False] * len(gt_boxes) for pred_box in pred_boxes: pred_class, pred_bbox, pred_conf = pred_box best_iou = 0 best_gt_idx = -1 # 寻找最佳匹配的真实标签 for i, gt_box in enumerate(gt_boxes): gt_class, gt_bbox = gt_box if gt_matched[i]: continue iou = calculate_iou(pred_bbox, gt_bbox) if iou > best_iou and pred_class == gt_class: best_iou = iou best_gt_idx = i # 如果IOU超过阈值且类别正确,则计为正确预测 if best_gt_idx != -1 and best_iou >= iou_threshold: correct_predictions += 1 gt_matched[best_gt_idx] = True # 避免除零错误 if total_gt_objects == 0: return 0.0 # 计算准确率 return correct_predictions / total_gt_objects @smart_inference_mode() def run( weights=ROOT / "yolov5s.pt", # model path or triton URL source=ROOT / "data/images", # file/dir/URL/glob/screen/0(webcam) data=ROOT / "data/coco128.yaml", # dataset.yaml path imgsz=(640, 640), # inference size (height, width) conf_thres=0.25, # confidence threshold iou_thres=0.45, # NMS IOU threshold max_det=1000, # maximum detections per image device="", # cuda device, i.e. 0 or 0,1,2,3 or cpu view_img=False, # show results save_txt=False, # save results to *.txt save_format=0, # save boxes coordinates in YOLO format or Pascal-VOC format (0 for YOLO and 1 for Pascal-VOC) save_csv=False, # save results in CSV format save_conf=False, # save confidences in --save-txt labels save_crop=False, # save cropped prediction boxes nosave=False, # do not save images/videos classes=None, # filter by class: --class 0, or --class 0 2 3 agnostic_nms=False, # class-agnostic NMS augment=False, # augmented inference visualize=False, # visualize features update=False, # update all models project=ROOT / "runs/detect", # save results to project/name name="exp", # save results to project/name exist_ok=False, # existing project/name ok, do not increment line_thickness=3, # bounding box thickness (pixels) hide_labels=False, # hide labels hide_conf=False, # hide confidences half=False, # use FP16 half-precision inference dnn=False, # use OpenCV DNN for ONNX inference vid_stride=1, # video frame-rate stride gt_dir="", # 新增:真实标签目录 eval_interval=10, # 新增:评估间隔帧数 ): """ Runs YOLOv5 detection inference on various sources like images, videos, directories, streams, etc. Args: weights (str | Path): Path to the model weights file or a Triton URL. Default is 'yolov5s.pt'. source (str | Path): Input source, which can be a file, directory, URL, glob pattern, screen capture, or webcam index. Default is 'data/images'. data (str | Path): Path to the dataset YAML file. Default is 'data/coco128.yaml'. imgsz (tuple[int, int]): Inference image size as a tuple (height, width). Default is (640, 640). conf_thres (float): Confidence threshold for detections. Default is 0.25. iou_thres (float): Intersection Over Union (IOU) threshold for non-max suppression. Default is 0.45. max_det (int): Maximum number of detections per image. Default is 1000. device (str): CUDA device identifier (e.g., '0' or '0,1,2,3') or 'cpu'. Default is an empty string, which uses the best available device. view_img (bool): If True, display inference results using OpenCV. Default is False. save_txt (bool): If True, save results in a text file. Default is False. save_format (int): Whether to save boxes coordinates in YOLO format or Pascal-VOC format. Default is 0. save_csv (bool): If True, save results in a CSV file. Default is False. save_conf (bool): If True, include confidence scores in the saved results. Default is False. save_crop (bool): If True, save cropped prediction boxes. Default is False. nosave (bool): If True, do not save inference images or videos. Default is False. classes (list[int]): List of classes to filter detections by. Default is None. agnostic_nms (bool): If True, perform class-agnostic non-max suppression. Default is False. augment (bool): If True, use augmented inference. Default is False. visualize (bool): If True, visualize feature maps. Default is False. update (bool): If True, update all models' weights. Default is False. project (str | Path): Directory to save results. Default is 'runs/detect'. name (str): Name of the current experiment; used to create a subdirectory within 'project'. Default is 'exp'. exist_ok (bool): If True, existing directories with the same name are reused instead of being incremented. Default is False. line_thickness (int): Thickness of bounding box lines in pixels. Default is 3. hide_labels (bool): If True, do not display labels on bounding boxes. Default is False. hide_conf (bool): If True, do not display confidence scores on bounding boxes. Default is False. half (bool): If True, use FP16 half-precision inference. Default is False. dnn (bool): If True, use OpenCV DNN backend for ONNX inference. Default is False. vid_stride (int): Stride for processing video frames, to skip frames between processing. Default is 1. gt_dir (str): 新增:真实标签目录路径 eval_interval (int): 新增:每隔多少帧计算一次准确率 Returns: None """ source = str(source) save_img = not nosave and not source.endswith(".txt") # save inference images is_file = Path(source).suffix[1:] in (IMG_FORMATS + VID_FORMATS) is_url = source.lower().startswith(("rtsp://", "rtmp://", "https://", "https://")) webcam = source.isnumeric() or source.endswith(".streams") or (is_url and not is_file) screenshot = source.lower().startswith("screen") if is_url and is_file: source = check_file(source) # download # Directories save_dir = increment_path(Path(project) / name, exist_ok=exist_ok) # increment run (save_dir / "labels" if save_txt else save_dir).mkdir(parents=True, exist_ok=True) # make dir # Load model device = select_device(device) model = DetectMultiBackend(weights, device=device, dnn=dnn, data=data, fp16=half) stride, names, pt = model.stride, model.names, model.pt imgsz = check_img_size(imgsz, s=stride) # check image size # Dataloader bs = 1 # batch_size if webcam: view_img = check_imshow(warn=True) dataset = LoadStreams(source, img_size=imgsz, stride=stride, auto=pt, vid_stride=vid_stride) bs = len(dataset) elif screenshot: dataset = LoadScreenshots(source, img_size=imgsz, stride=stride, auto=pt) else: dataset = LoadImages(source, img_size=imgsz, stride=stride, auto=pt, vid_stride=vid_stride) vid_path, vid_writer = [None] * bs, [None] * bs # 新增:加载真实标签数据 gt_labels = {} if gt_dir: gt_dir = Path(gt_dir) for txt_file in gt_dir.glob("*.txt"): img_name = txt_file.stem gt_labels[img_name] = [] with open(txt_file, "r") as f: for line in f: parts = line.strip().split() if len(parts) >= 5: cls = int(parts[0]) # 将YOLO格式转换为xyxy格式 x, y, w, h = map(float, parts[1:5]) # 假设真实标签对应的图像尺寸与输入图像一致 x1 = (x - w/2) * imgsz[1] y1 = (y - h/2) * imgsz[0] x2 = (x + w/2) * imgsz[1] y2 = (y + h/2) * imgsz[0] gt_labels[img_name].append((cls, (x1, y1, x2, y2))) # 新增:收集预测结果 pred_detections = {} frame_count = 0 accuracy = 0.0 # 初始化准确率 # Run inference model.warmup(imgsz=(1 if pt or model.triton else bs, 3, *imgsz)) # warmup seen, windows, dt = 0, [], (Profile(device=device), Profile(device=device), Profile(device=device)) for path, im, im0s, vid_cap, s in dataset: with dt[0]: im = torch.from_numpy(im).to(model.device) im = im.half() if model.fp16 else im.float() # uint8 to fp16/32 im /= 255 # 0 - 255 to 0.0 - 1.0 if len(im.shape) == 3: im = im[None] # expand for batch dim if model.xml and im.shape[0] > 1: ims = torch.chunk(im, im.shape[0], 0) # Inference with dt[1]: visualize = increment_path(save_dir / Path(path).stem, mkdir=True) if visualize else False if model.xml and im.shape[0] > 1: pred = None for image in ims: if pred is None: pred = model(image, augment=augment, visualize=visualize).unsqueeze(0) else: pred = torch.cat((pred, model(image, augment=augment, visualize=visualize).unsqueeze(0)), dim=0) pred = [pred, None] else: pred = model(im, augment=augment, visualize=visualize) # NMS with dt[2]: pred = non_max_suppression(pred, conf_thres, iou_thres, classes, agnostic_nms, max_det=max_det) # Second-stage classifier (optional) # pred = utils.general.apply_classifier(pred, classifier_model, im, im0s) # Define the path for the CSV file csv_path = save_dir / "predictions.csv" # Create or append to the CSV file def write_to_csv(image_name, prediction, confidence): """Writes prediction data for an image to a CSV file, appending if the file exists.""" data = {"Image Name": image_name, "Prediction": prediction, "Confidence": confidence} file_exists = os.path.isfile(csv_path) with open(csv_path, mode="a", newline="") as f: writer = csv.DictWriter(f, fieldnames=data.keys()) if not file_exists: writer.writeheader() writer.writerow(data) # Process predictions for i, det in enumerate(pred): # per image seen += 1 if webcam: # batch_size >= 1 p, im0, frame = path[i], im0s[i].copy(), dataset.count s += f"{i}: " else: p, im0, frame = path, im0s.copy(), getattr(dataset, "frame", 0) p = Path(p) # to Path save_path = str(save_dir / p.name) # im.jpg txt_path = str(save_dir / "labels" / p.stem) + ("" if dataset.mode == "image" else f"_{frame}") # im.txt s += "{:g}x{:g} ".format(*im.shape[2:]) # print string gn = torch.tensor(im0.shape)[[1, 0, 1, 0]] # normalization gain whwh imc = im0.copy() if save_crop else im0 # for save_crop annotator = Annotator(im0, line_width=line_thickness, example=str(names)) if len(det): # Rescale boxes from img_size to im0 size det[:, :4] = scale_boxes(im.shape[2:], det[:, :4], im0.shape).round() # Print results for c in det[:, 5].unique(): n = (det[:, 5] == c).sum() # detections per class s += f"{n} {names[int(c)]}{'s' * (n > 1)}, " # add to string # Write results for *xyxy, conf, cls in reversed(det): c = int(cls) # integer class label = names[c] if hide_conf else f"{names[c]}" confidence = float(conf) confidence_str = f"{confidence:.2f}" if save_csv: write_to_csv(p.name, label, confidence_str) if save_txt: # Write to file if save_format == 0: coords = ( (xyxy2xywh(torch.tensor(xyxy).view(1, 4)) / gn).view(-1).tolist() ) # normalized xywh else: coords = (torch.tensor(xyxy).view(1, 4) / gn).view(-1).tolist() # xyxy line = (cls, *coords, conf) if save_conf else (cls, *coords) # label format with open(f"{txt_path}.txt", "a") as f: f.write(("%g " * len(line)).rstrip() % line + "\n") if save_img or save_crop or view_img: # Add bbox to image c = int(cls) # integer class label = None if hide_labels else (names[c] if hide_conf else f"{names[c]} {conf:.2f}") annotator.box_label(xyxy, label, color=colors(c, True)) if save_crop: save_one_box(xyxy, imc, file=save_dir / "crops" / names[c] / f"{p.stem}.jpg", BGR=True) # 新增:收集预测结果 img_name = p.stem pred_detections[img_name] = [] if len(det): for *xyxy, conf, cls in det: c = int(cls) x1, y1, x2, y2 = map(int, xyxy) pred_detections[img_name].append((c, (x1, y1, x2, y2), float(conf))) # 新增:定期计算准确率并显示 frame_count += 1 if gt_dir and frame_count % eval_interval == 0: accuracy = calculate_accuracy(gt_labels, pred_detections) if save_img or view_img: accuracy_text = f"Accuracy: {accuracy:.2f}" annotator.text((10, 30), accuracy_text, txt_color=(255, 255, 255)) im0 = annotator.result() # Stream results im0 = annotator.result() if view_img: if platform.system() == "Linux" and p not in windows: windows.append(p) cv2.namedWindow(str(p), cv2.WINDOW_NORMAL | cv2.WINDOW_KEEPRATIO) # allow window resize (Linux) cv2.resizeWindow(str(p), im0.shape[1], im0.shape[0]) cv2.imshow(str(p), im0) cv2.waitKey(1) # 1 millisecond # Save results (image with detections) if save_img: if dataset.mode == "image": cv2.imwrite(save_path, im0) else: # 'video' or 'stream' if vid_path[i] != save_path: # new video vid_path[i] = save_path if isinstance(vid_writer[i], cv2.VideoWriter): vid_writer[i].release() # release previous video writer if vid_cap: # video fps = vid_cap.get(cv2.CAP_PROP_FPS) w = int(vid_cap.get(cv2.CAP_PROP_FRAME_WIDTH)) h = int(vid_cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) else: # stream fps, w, h = 30, im0.shape[1], im0.shape[0] save_path = str(Path(save_path).with_suffix(".mp4")) # force *.mp4 suffix on results videos vid_writer[i] = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h)) vid_writer[i].write(im0) # Print time (inference-only) LOGGER.info(f"{s}{'' if len(det) else '(no detections), '}{dt[1].dt * 1e3:.1f}ms") # 新增:在终端输出最终准确率 if gt_dir: accuracy = calculate_accuracy(gt_labels, pred_detections) LOGGER.info(f"Overall Accuracy: {accuracy:.4f}") # Print results t = tuple(x.t / seen * 1e3 for x in dt) # speeds per image LOGGER.info(f"Speed: %.1fms pre-process, %.1fms inference, %.1fms NMS per image at shape {(1, 3, *imgsz)}" % t) if save_txt or save_img: s = f"\n{len(list(save_dir.glob('labels/*.txt')))} labels saved to {save_dir / 'labels'}" if save_txt else "" LOGGER.info(f"Results saved to {colorstr('bold', save_dir)}{s}") if update: strip_optimizer(weights[0]) # update model (to fix SourceChangeWarning) def parse_opt(): """ Parse command-line arguments for YOLOv5 detection, allowing custom inference options and model configurations. Args: --weights (str | list[str], optional): Model path or triton URL. Defaults to ROOT / 'yolov5s.pt'. --source (str, optional): File/dir/URL/glob/screen/0(webcam). Defaults to ROOT / 'data/images'. --data (str, optional): Dataset YAML path. Provides dataset configuration information. --imgsz (list[int], optional): Inference size (height, width). Defaults to [640]. --conf-thres (float, optional): Confidence threshold. Defaults to 0.25. --iou-thres (float, optional): NMS IoU threshold. Defaults to 0.45. --max-det (int, optional): Maximum number of detections per image. Defaults to 1000. --device (str, optional): CUDA device, i.e. 0 or 0,1,2,3 or cpu. Defaults to "". --view-img (bool, optional): Flag to display results. Default is False. --save-txt (bool, optional): Flag to save results to *.txt files. Default is False. --save-format (int, optional): Whether to save boxes coordinates in YOLO format or Pascal-VOC format. Default is 0. --save-csv (bool, optional): Flag to save results in CSV format. Default is False. --save-conf (bool, optional): Flag to save confidences in labels saved via --save-txt. Default is False. --save-crop (bool, optional): Flag to save cropped prediction boxes. Default is False. --nosave (bool, optional): Flag to prevent saving images/videos. Default is False. --classes (list[int], optional): List of classes to filter results by. Default is None. --agnostic-nms (bool, optional): Flag for class-agnostic NMS. Default is False. --augment (bool, optional): Flag for augmented inference. Default is False. --visualize (bool, optional): Flag for visualizing features. Default is False. --update (bool, optional): Flag to update all models in the model directory. Default is False. --project (str, optional): Directory to save results. Default is ROOT / 'runs/detect'. --name (str, optional): Sub-directory name for saving results within --project. Default is 'exp'. --exist-ok (bool, optional): Flag to allow overwriting if the project/name already exists. Default is False. --line-thickness (int, optional): Thickness (in pixels) of bounding boxes. Default is 3. --hide-labels (bool, optional): Flag to hide labels in the output. Default is False. --hide-conf (bool, optional): Flag to hide confidences in the output. Default is False. --half (bool, optional): Flag to use FP16 half-precision inference. Default is False. --dnn (bool, optional): Flag to use OpenCV DNN for ONNX inference. Default is False. --vid-stride (int, optional): Video frame-rate stride. Default is 1. --gt-dir (str, optional): 新增:真实标签目录路径 --eval-interval (int, optional): 新增:每隔多少帧计算一次准确率 Returns: argparse.Namespace: Parsed command-line arguments as an argparse.Namespace object. """ parser = argparse.ArgumentParser() parser.add_argument("--weights", nargs="+", type=str, default=ROOT / "yolov5s.pt", help="model path or triton URL") parser.add_argument("--source", type=str, default=ROOT / "data/images", help="file/dir/URL/glob/screen/0(webcam)") parser.add_argument("--data", type=str, default=ROOT / "data/coco128.yaml", help="(optional) dataset.yaml path") parser.add_argument("--imgsz", "--img", "--img-size", nargs="+", type=int, default=[640], help="inference size h,w") parser.add_argument("--conf-thres", type=float, default=0.25, help="confidence threshold") parser.add_argument("--iou-thres", type=float, default=0.45, help="NMS IoU threshold") parser.add_argument("--max-det", type=int, default=1000, help="maximum detections per image") parser.add_argument("--device", default="", help="cuda device, i.e. 0 or 0,1,2,3 or cpu") parser.add_argument("--view-img", action="store_true", help="show results") parser.add_argument("--save-txt", action="store_true", help="save results to *.txt") parser.add_argument( "--save-format", type=int, default=0, help="whether to save boxes coordinates in YOLO format or Pascal-VOC format when save-txt is True, 0 for YOLO and 1 for Pascal-VOC", ) parser.add_argument("--save-csv", action="store_true", help="save results in CSV format") parser.add_argument("--save-conf", action="store_true", help="save confidences in --save-txt labels") parser.add_argument("--save-crop", action="store_true", help="save cropped prediction boxes") parser.add_argument("--nosave", action="store_true", help="do not save images/videos") parser.add_argument("--classes", nargs="+", type=int, help="filter by class: --classes 0, or --classes 0 2 3") parser.add_argument("--agnostic-nms", action="store_true", help="class-agnostic NMS") parser.add_argument("--augment", action="store_true", help="augmented inference") parser.add_argument("--visualize", action="store_true", help="visualize features") parser.add_argument("--update", action="store_true", help="update all models") parser.add_argument("--project", default=ROOT / "runs/detect", help="save results to project/name") parser.add_argument("--name", default="exp", help="save results to project/name") parser.add_argument("--exist-ok", action="store_true", help="existing project/name ok, do not increment") parser.add_argument("--line-thickness", default=3, type=int, help="bounding box thickness (pixels)") parser.add_argument("--hide-labels", default=False, action="store_true", help="hide labels") parser.add_argument("--hide-conf", default=False, action="store_true", help="hide confidences") parser.add_argument("--half", action="store_true", help="use FP16 half-precision inference") parser.add_argument("--dnn", action="store_true", help="use OpenCV DNN for ONNX inference") parser.add_argument("--vid-stride", type=int, default=1, help="video frame-rate stride") # 新增参数 parser.add_argument("--gt-dir", type=str, default="", help="ground truth labels directory") parser.add_argument("--eval-interval", type=int, default=10, help="evaluate accuracy every N frames") opt = parser.parse_args() opt.imgsz *= 2 if len(opt.imgsz) == 1 else 1 # expand print_args(vars(opt)) return opt def main(opt): """ Executes YOLOv5 model inference based on provided command-line arguments, validating dependencies before running. Args: opt (argparse.Namespace): Command-line arguments for YOLOv5 detection. Returns: None """ check_requirements(ROOT / "requirements.txt", exclude=("tensorboard", "thop")) run(**vars(opt)) if __name__ == "__main__": opt = parse_opt() main(opt)代码如上。yolov5在detect.py得到有类别和置信度标注的视频和图片,请问我如何操作,才能在有类别和置信度标注的视频和图片的基础上,在视频或图片中显示识别准确率Accuracy。请给出修改后的完整代码(尽量少修改,不要改变代码的其他地方),要求直接在vscode点击运行即可生成显示识别准确率Accuracy的视频或图片

[main] 正在配置项目: shilei [proc] 执行命令: /usr/bin/cmake -DCMAKE_BUILD_TYPE:STRING=Debug -Dcmake.cmakePath:STRING=/usr/bin/cmake -DCMAKE_EXPORT_COMPILE_COMMANDS:BOOL=TRUE -DCMAKE_C_COMPILER:FILEPATH=/usr/bin/gcc -DCMAKE_CXX_COMPILER:FILEPATH=/usr/bin/g++ --no-warn-unused-cli -S/home/yun/shilei/chatproject -B/home/yun/shilei/build -G "Unix Makefiles" [cmake] Not searching for unused variables given on the command line. [cmake] -- The C compiler identification is GNU 13.2.0 [cmake] -- The CXX compiler identification is GNU 13.2.0 [cmake] -- Detecting C compiler ABI info [cmake] -- Detecting C compiler ABI info - done [cmake] -- Check for working C compiler: /usr/bin/gcc - skipped [cmake] -- Detecting C compile features [cmake] -- Detecting C compile features - done [cmake] -- Detecting CXX compiler ABI info [cmake] -- Detecting CXX compiler ABI info - done [cmake] -- Check for working CXX compiler: /usr/bin/g++ - skipped [cmake] -- Detecting CXX compile features [cmake] -- Detecting CXX compile features - done [cmake] CMake Error at CMakeLists.txt:18 (add_subdirectory): [cmake] The source directory [cmake] [cmake] /home/yun/shilei/chatproject/src [cmake] [cmake] does not contain a CMakeLists.txt file. [cmake] [cmake] [cmake] -- Configuring incomplete, errors occurred! [cmake] See also "/home/yun/shilei/build/CMakeFiles/CMakeOutput.log". [proc] 命令“/usr/bin/cmake -DCMAKE_BUILD_TYPE:STRING=Debug -Dcmake.cmakePath:STRING=/usr/bin/cmake -DCMAKE_EXPORT_COMPILE_COMMANDS:BOOL=TRUE -DCMAKE_C_COMPILER:FILEPATH=/usr/bin/gcc -DCMAKE_CXX_COMPILER:FILEPATH=/usr/bin/g++ --no-warn-unused-cli -S/home/yun/shilei/chatproject -B/home/yun/shilei/build -G "Unix Makefiles"”已退出,代码为 1 [ctest] 在测试资源管理器中找不到文件夹: /home/yun/shilei/chatproject

abot@abot:~/robot_ws$ cd ~/robot_ws && catkin_make -DCATKIN_WHITELIST_PACKAGES="robot_slam" Base path: /home/abot/robot_ws Source space: /home/abot/robot_ws/src Build space: /home/abot/robot_ws/build Devel space: /home/abot/robot_ws/devel Install space: /home/abot/robot_ws/install #### #### Running command: "make cmake_check_build_system" in "/home/abot/robot_ws/build" #### -- Using CATKIN_DEVEL_PREFIX: /home/abot/robot_ws/devel -- Using CMAKE_PREFIX_PATH: /opt/ros/noetic -- This workspace overlays: /opt/ros/noetic -- Found PythonInterp: /usr/bin/python3 (found suitable version "3.8.10", minimum required is "3") -- Using PYTHON_EXECUTABLE: /usr/bin/python3 -- Using Debian Python package layout -- Using empy: /usr/lib/python3/dist-packages/em.py -- Using CATKIN_ENABLE_TESTING: ON -- Call enable_testing() -- Using CATKIN_TEST_RESULTS_DIR: /home/abot/robot_ws/build/test_results -- Forcing gtest/gmock from source, though one was otherwise available. -- Found gtest sources under '/usr/src/googletest': gtests will be built -- Found gmock sources under '/usr/src/googletest': gmock will be built -- Found PythonInterp: /usr/bin/python3 (found version "3.8.10") -- Using Python nosetests: /usr/bin/nosetests3 -- catkin 0.8.10 -- BUILD_SHARED_LIBS is on -- BUILD_SHARED_LIBS is on -- Using CATKIN_WHITELIST_PACKAGES: robot_slam -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -- ~~ traversing 1 packages in topological order: -- ~~ - robot_slam -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -- +++ processing catkin package: 'robot_slam' -- ==> add_subdirectory(robot_slam) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy CMake Error at robot_slam/CMakeLists.txt:212 (add_subdirectory): add_subdirectory given source "openslam" which is not an existing directory. CMake Error at robot_slam/CMakeLists.txt:213 (add_subdirectory): add_subdirectory given source "gmapping" which is not an existing directory. CMake Error at robot_slam/CMakeLis

Make Deprecation Warning at CMakeLists.txt:1 (cmake_minimum_required): Compatibility with CMake < 2.8.12 will be removed from a future version of CMake. Update the VERSION argument <min> value or use a ...<max> suffix to tell CMake that the project does not need compatibility with older versions. -- The C compiler identification is GNU 7.5.0 -- The CXX compiler identification is GNU 7.5.0 -- Detecting C compiler ABI info -- Detecting C compiler ABI info - done -- Check for working C compiler: /usr/bin/cc - skipped -- Detecting C compile features -- Detecting C compile features - done -- Detecting CXX compiler ABI info -- Detecting CXX compiler ABI info - done -- Check for working CXX compiler: /usr/bin/c++ - skipped -- Detecting CXX compile features -- Detecting CXX compile features - done Build type: Release -- Performing Test COMPILER_SUPPORTS_CXX11 -- Performing Test COMPILER_SUPPORTS_CXX11 - Success -- Performing Test COMPILER_SUPPORTS_CXX0X -- Performing Test COMPILER_SUPPORTS_CXX0X - Success -- Using flag -std=c++11. -- Found OpenCV: /usr/local (found suitable version "4.2.0", minimum required is "4.2") OPENCV VERSION: 4.2.0 CMake Warning at CMakeLists.txt:43 (find_package): By not providing "Findrealsense2.cmake" in CMAKE_MODULE_PATH this project has asked CMake to find a package configuration file provided by "realsense2", but CMake did not find one. Could not find a package configuration file provided by "realsense2" with any of the following names: realsense2Config.cmake realsense2-config.cmake Add the installation prefix of "realsense2" to CMAKE_PREFIX_PATH or set "realsense2_DIR" to a directory containing one of the above files. If "realsense2" provides a separate development package or SDK, be sure it has been installed. CMake Error at CMakeLists.txt:116 (add_subdirectory): add_subdirectory given source "Thirdparty/g2o" which is not an existing directory. -- Configuring incomplete, errors occurred! See also "/home/robot/XTDrone/sensing/slam/vslam/ORB_SLAM3/build/CMakeFiles/CMakeOutput.log". make: *** 没有指明目标并且找不到 makefile。 停止。 ./build.sh: 第 9 行: cd: ../../g2o: 没有那个文件或目录 Configuring and building Thirdparty/g2o ... CMake Deprecation Warning at CMakeLists.txt:1 (cmake_minimum_required): Compatibility with CMake < 2.8.12 will be removed from a future version of CMake. Update the VERSION argument <min> value or use a ...<max> suffix to tell CMake that the project does not need compatibility with older versions. Build type: Release -- Using flag -std=c++11. OPENCV VERSION: 4.2.0 CMake Warning at CMakeLists.txt:43 (find_package): By not providing "Findrealsense2.cmake" in CMAKE_MODULE_PATH this project has asked CMake to find a package configuration file provided by "realsense2", but CMake did not find one. Could not find a package configuration file provided by "realsense2" with any of the following names: realsense2Config.cmake realsense2-config.cmake Add the installation prefix of "realsense2" to CMAKE_PREFIX_PATH or set "realsense2_DIR" to a directory containing one of the above files. If "realsense2" provides a separate development package or SDK, be sure it has been installed. CMake Error at CMakeLists.txt:116 (add_subdirectory): add_subdirectory given source "Thirdparty/g2o" which is not an existing directory. -- Configuring incomplete, errors occurred! See also "/home/robot/XTDrone/sensing/slam/vslam/ORB_SLAM3/build/CMakeFiles/CMakeOutput.log". make: *** 没有指明目标并且找不到 makefile。 停止。 ./build.sh: 第 18 行: cd: ../../Sophus: 没有那个文件或目录 Configuring and building Thirdparty/Sophus ... CMake Error: The source directory "/home/robot/XTDrone/sensing/slam/vslam/ORB_SLAM3/build/build" does not appear to contain CMakeLists.txt. Specify --help for usage, or press the help button on the CMake GUI. make: *** 没有指明目标并且找不到 makefile。 停止。 Uncompress vocabulary ... Configuring and building ORB_SLAM3 ... mkdir: 无法创建目录"build": 文件已存在 CMake Deprecation Warning at CMakeLists.txt:1 (cmake_minimum_required): Compatibility with CMake < 2.8.12 will be removed from a future version of CMake. Update the VERSION argument <min> value or use a ...<max> suffix to tell CMake that the project does not need compatibility with older versions. Build type: Release -- Using flag -std=c++11. OPENCV VERSION: 4.2.0 CMake Warning at CMakeLists.txt:43 (find_package): By not providing "Findrealsense2.cmake" in CMAKE_MODULE_PATH this project has asked CMake to find a package configuration file provided by "realsense2", but CMake did not find one. Could not find a package configuration file provided by "realsense2" with any of the following names: realsense2Config.cmake realsense2-config.cmake Add the installation prefix of "realsense2" to CMAKE_PREFIX_PATH or set "realsense2_DIR" to a directory containing one of the above files. If "realsense2" provides a separate development package or SDK, be sure it has been installed. CMake Error at CMakeLists.txt:116 (add_subdirectory): add_subdirectory given source "Thirdparty/g2o" which is not an existing directory. -- Configuring incomplete, errors occurred! See also "/home/robot/XTDrone/sensing/slam/vslam/ORB_SLAM3/build/CMakeFiles/CMakeOutput.log". make: *** 没有指明目标并且找不到 makefile。 停止。

EPRobot@EPRobot:~/robot_ws$ cd ~/robot_ws # 在每次打开新终端时运行 EPRobot@EPRobot:~/robot_ws$ catkin_make Base path: /home/EPRobot/robot_ws Source space: /home/EPRobot/robot_ws/src Build space: /home/EPRobot/robot_ws/build Devel space: /home/EPRobot/robot_ws/devel Install space: /home/EPRobot/robot_ws/install #### #### Running command: "make cmake_check_build_system" in "/home/EPRobot/robot_ws/build" #### -- Using CATKIN_DEVEL_PREFIX: /home/EPRobot/robot_ws/devel -- Using CMAKE_PREFIX_PATH: /home/EPRobot/robot_ws/devel;/opt/ros/melodic -- This workspace overlays: /home/EPRobot/robot_ws/devel;/opt/ros/melodic -- Found PythonInterp: /usr/bin/python2 (found suitable version "2.7.17", minimum required is "2") -- Using PYTHON_EXECUTABLE: /usr/bin/python2 -- Using Debian Python package layout -- Using empy: /usr/bin/empy -- Using CATKIN_ENABLE_TESTING: ON -- Call enable_testing() -- Using CATKIN_TEST_RESULTS_DIR: /home/EPRobot/robot_ws/build/test_results -- Found gtest sources under '/usr/src/googletest': gtests will be built -- Found gmock sources under '/usr/src/googletest': gmock will be built -- Found PythonInterp: /usr/bin/python2 (found version "2.7.17") -- Using Python nosetests: /usr/bin/nosetests-2.7 -- catkin 0.7.29 -- BUILD_SHARED_LIBS is on -- BUILD_SHARED_LIBS is on -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -- ~~ traversing 62 packages in topological order: -- ~~ - astra_launch -- ~~ - base_control -- ~~ - hibot_follower -- ~~ - lslidar (metapackage) -- ~~ - navigation (metapackage) -- ~~ - robot_navigation -- ~~ - robot_upstart -- ~~ - simple_navigation_goals -- ~~ - lslidar_msgs -- ~~ - rospy_message_converter -- ~~ - eprobot_auto_home -- ~~ - eprobot_start -- ~~ - ls01d -- ~~ - map_server -- ~~ - hls_lfcd_lds_driver -- ~~ - iiiroboticslidar2 -- ~~ - astra_camera -- ~~ - rplidar_ros -- ~~ - eprobot_joy -- ~~ - lslidar_driver -- ~~ - robot_pose_ekf -- ~~ - sc_mini -- ~~ - amcl -- ~~ - fake_localization -- ~~ - laser_filters -- ~~ - robot_localization -- ~~ - track_detection -- ~~ - voxel_grid -- ~~ - costmap_2d -- ~~ - nav_core -- ~~ - base_local_planner -- ~~ - carrot_planner -- ~~ - clear_costmap_recovery -- ~~ - dwa_local_planner -- ~~ - move_slow_and_clear -- ~~ - navfn -- ~~ - global_planner -- ~~ - rotate_recovery -- ~~ - move_base -- ~~ - teb_local_planner -- ~~ - eprobot_description -- ~~ - xf_mic_asr_offline -- ~~ - ydlidar -- ~~ - yocs_ar_pair_approach -- ~~ - yocs_cmd_vel_mux -- ~~ - yocs_controllers -- ~~ - yocs_keyop -- ~~ - yocs_localization_manager -- ~~ - yocs_math_toolkit -- ~~ - yocs_ar_marker_tracking -- ~~ - yocs_diff_drive_pose_controller -- ~~ - yocs_ar_pair_tracking -- ~~ - yocs_joyop -- ~~ - yocs_navi_toolkit -- ~~ - yocs_navigator -- ~~ - yocs_rapps -- ~~ - yocs_safety_controller -- ~~ - yocs_velocity_smoother -- ~~ - yocs_virtual_sensor -- ~~ - yocs_waypoint_provider -- ~~ - yocs_waypoints_navi -- ~~ - yujin_ocs (metapackage) -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -- +++ processing catkin package: 'astra_launch' -- ==> add_subdirectory(ros_astra_launch) -- +++ processing catkin package: 'base_control' -- ==> add_subdirectory(base_control) -- +++ processing catkin package: 'hibot_follower' -- ==> add_subdirectory(hibot_follower) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy CMake Warning at /opt/ros/melodic/share/catkin/cmake/catkin_package.cmake:166 (message): catkin_package() DEPENDS on 'system_lib' but neither 'system_lib_INCLUDE_DIRS' nor 'system_lib_LIBRARIES' is defined. Call Stack (most recent call first): /opt/ros/melodic/share/catkin/cmake/catkin_package.cmake:102 (_catkin_package) hibot_follower/CMakeLists.txt:24 (catkin_package) -- +++ processing catkin metapackage: 'lslidar' -- ==> add_subdirectory(lslidar) -- +++ processing catkin metapackage: 'navigation' -- ==> add_subdirectory(navigation-melodic/navigation) -- +++ processing catkin package: 'robot_navigation' -- ==> add_subdirectory(robot_navigation) -- +++ processing catkin package: 'robot_upstart' -- ==> add_subdirectory(robot_upstart) -- +++ processing catkin package: 'simple_navigation_goals' -- ==> add_subdirectory(simple_navigation_goals) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- +++ processing catkin package: 'lslidar_msgs' -- ==> add_subdirectory(lslidar_msgs) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- lslidar_msgs: 5 messages, 0 services -- +++ processing catkin package: 'rospy_message_converter' -- ==> add_subdirectory(rospy_message_converter) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- rospy_message_converter: 4 messages, 1 services -- +++ processing catkin package: 'eprobot_auto_home' -- ==> add_subdirectory(eprobot_auto_home) -- +++ processing catkin package: 'eprobot_start' -- ==> add_subdirectory(eprobot_start) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy CMake Warning at /opt/ros/melodic/share/catkin/cmake/catkin_package.cmake:166 (message): catkin_package() DEPENDS on 'system_lib' but neither 'system_lib_INCLUDE_DIRS' nor 'system_lib_LIBRARIES' is defined. Call Stack (most recent call first): /opt/ros/melodic/share/catkin/cmake/catkin_package.cmake:102 (_catkin_package) eprobot_start/CMakeLists.txt:24 (catkin_package) -- +++ processing catkin package: 'ls01d' -- ==> add_subdirectory(lidar/ls01d) -- +++ processing catkin package: 'map_server' -- ==> add_subdirectory(navigation-melodic/map_server) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- Boost version: 1.65.1 -- Found the following Boost libraries: -- filesystem -- system -- +++ processing catkin package: 'hls_lfcd_lds_driver' -- ==> add_subdirectory(lidar/hls_lfcd_lds_driver) -- Boost version: 1.65.1 -- +++ processing catkin package: 'iiiroboticslidar2' -- ==> add_subdirectory(lidar/iiiroboticslidar2_ros) -- +++ processing catkin package: 'astra_camera' -- ==> add_subdirectory(ros_astra_camera) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- Boost version: 1.65.1 -- Found the following Boost libraries: -- system -- thread -- chrono -- date_time -- atomic -- ORRBEC Machine : aarch64 -- ORRBEC Machine Bits : 64 -- ORRBEC : arm64 -- libuvc 0.0.6 -- astra_camera: 0 messages, 19 services -- +++ processing catkin package: 'rplidar_ros' -- ==> add_subdirectory(lidar/rplidar_ros) -- +++ processing catkin package: 'eprobot_joy' -- ==> add_subdirectory(eprobot_joy) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy CMake Warning at /opt/ros/melodic/share/catkin/cmake/catkin_package.cmake:166 (message): catkin_package() DEPENDS on 'system_lib' but neither 'system_lib_INCLUDE_DIRS' nor 'system_lib_LIBRARIES' is defined. Call Stack (most recent call first): /opt/ros/melodic/share/catkin/cmake/catkin_package.cmake:102 (_catkin_package) eprobot_joy/CMakeLists.txt:39 (catkin_package) -- +++ processing catkin package: 'lslidar_driver' -- ==> add_subdirectory(lslidar_driver) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- Boost version: 1.65.1 CMake Warning at /opt/ros/melodic/share/catkin/cmake/catkin_package.cmake:166 (message): catkin_package() DEPENDS on 'boost' but neither 'boost_INCLUDE_DIRS' nor 'boost_LIBRARIES' is defined. Call Stack (most recent call first): /opt/ros/melodic/share/catkin/cmake/catkin_package.cmake:102 (_catkin_package) lslidar_driver/CMakeLists.txt:22 (catkin_package) -- +++ processing catkin package: 'robot_pose_ekf' -- ==> add_subdirectory(robot_pose_ekf) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- Boost version: 1.65.1 -- Found the following Boost libraries: -- thread -- chrono -- system -- date_time -- atomic -- robot_pose_ekf: 0 messages, 1 services -- +++ processing catkin package: 'sc_mini' -- ==> add_subdirectory(lidar/sc_mini) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- Boost version: 1.65.1 -- +++ processing catkin package: 'amcl' -- ==> add_subdirectory(navigation-melodic/amcl) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- Boost version: 1.65.1 -- +++ processing catkin package: 'fake_localization' -- ==> add_subdirectory(navigation-melodic/fake_localization) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- Boost version: 1.65.1 -- +++ processing catkin package: 'laser_filters' -- ==> add_subdirectory(laser_filters) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- Boost version: 1.65.1 -- Found the following Boost libraries: -- system -- +++ processing catkin package: 'robot_localization' -- ==> add_subdirectory(robot_localization) robot_localization: You did not request a specific build type: selecting 'RelWithDebInfo'. -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- robot_localization: 0 messages, 7 services -- +++ processing catkin package: 'track_detection' -- ==> add_subdirectory(track_detection) -- +++ processing catkin package: 'voxel_grid' -- ==> add_subdirectory(navigation-melodic/voxel_grid) -- +++ processing catkin package: 'costmap_2d' -- ==> add_subdirectory(navigation-melodic/costmap_2d) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- Boost version: 1.65.1 -- Found the following Boost libraries: -- system -- thread -- chrono -- date_time -- atomic -- costmap_2d: 1 messages, 0 services -- +++ processing catkin package: 'nav_core' -- ==> add_subdirectory(navigation-melodic/nav_core) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- +++ processing catkin package: 'base_local_planner' -- ==> add_subdirectory(navigation-melodic/base_local_planner) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- Boost version: 1.65.1 -- Found the following Boost libraries: -- thread -- chrono -- system -- date_time -- atomic -- base_local_planner: 1 messages, 0 services -- +++ processing catkin package: 'carrot_planner' -- ==> add_subdirectory(navigation-melodic/carrot_planner) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- +++ processing catkin package: 'clear_costmap_recovery' -- ==> add_subdirectory(navigation-melodic/clear_costmap_recovery) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- +++ processing catkin package: 'dwa_local_planner' -- ==> add_subdirectory(navigation-melodic/dwa_local_planner) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- +++ processing catkin package: 'move_slow_and_clear' -- ==> add_subdirectory(navigation-melodic/move_slow_and_clear) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- Boost version: 1.65.1 -- Found the following Boost libraries: -- thread -- chrono -- system -- date_time -- atomic -- +++ processing catkin package: 'navfn' -- ==> add_subdirectory(navigation-melodic/navfn) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- navfn: 0 messages, 2 services -- NAVFN_HAVE_FLTK: , NETPBM: 1 -- FLTK orf NETPBM not found: cannot build navtest -- +++ processing catkin package: 'global_planner' -- ==> add_subdirectory(navigation-melodic/global_planner) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- +++ processing catkin package: 'rotate_recovery' -- ==> add_subdirectory(navigation-melodic/rotate_recovery) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- +++ processing catkin package: 'move_base' -- ==> add_subdirectory(navigation-melodic/move_base) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- +++ processing catkin package: 'teb_local_planner' -- ==> add_subdirectory(teb_local_planner-melodic) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- System: Linux-5.3.0-1030-raspi2 -- /opt/ros/melodic/share/cmake_modules/cmake/../../../share/cmake_modules/cmake/Modules;/home/EPRobot/robot_ws/src/teb_local_planner-melodic/cmake_modules -- Boost version: 1.65.1 -- Found the following Boost libraries: -- system -- thread -- graph -- chrono -- date_time -- atomic -- Found SuiteSparse -- Searching for g2o ... -- Found g2o headers in: /opt/ros/melodic/include/g2o -- Found libg2o: /opt/ros/melodic/lib/libg2o_csparse_extension.so;/opt/ros/melodic/lib/libg2o_core.so;/opt/ros/melodic/lib/libg2o_stuff.so;/opt/ros/melodic/lib/libg2o_types_slam2d.so;/opt/ros/melodic/lib/libg2o_types_slam3d.so;/opt/ros/melodic/lib/libg2o_solver_cholmod.so;/opt/ros/melodic/lib/libg2o_solver_pcg.so;/opt/ros/melodic/lib/libg2o_solver_csparse.so;/opt/ros/melodic/lib/libg2o_incremental.so -- teb_local_planner: 3 messages, 0 services -- +++ processing catkin package: 'eprobot_description' -- ==> add_subdirectory(eprobot_description) -- +++ processing catkin package: 'xf_mic_asr_offline' -- ==> add_subdirectory(xf_mic_asr_offline) -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- xf_mic_asr_offline: 2 messages, 7 services -- +++ processing catkin package: 'ydlidar' -- ==> add_subdirectory(ydlidar) -- +++ processing catkin package: 'yocs_ar_pair_approach' -- ==> add_subdirectory(yujin_ocs/yocs_ar_pair_approach) -- +++ processing catkin package: 'yocs_cmd_vel_mux' -- ==> add_subdirectory(yujin_ocs/yocs_cmd_vel_mux) -- +++ processing catkin package: 'yocs_controllers' -- ==> add_subdirectory(yujin_ocs/yocs_controllers) -- +++ processing catkin package: 'yocs_keyop' -- ==> add_subdirectory(yujin_ocs/yocs_keyop) -- Could NOT find ecl_threads (missing: ecl_threads_DIR) -- Could not find the required component 'ecl_threads'. The following CMake error indicates that you either need to install the package with the same name or change your environment so that it can be found. CMake Error at /opt/ros/melodic/share/catkin/cmake/catkinConfig.cmake:83 (find_package): Could not find a package configuration file provided by "ecl_threads" with any of the following names: ecl_threadsConfig.cmake ecl_threads-config.cmake Add the installation prefix of "ecl_threads" to CMAKE_PREFIX_PATH or set "ecl_threads_DIR" to a directory containing one of the above files. If "ecl_threads" provides a separate development package or SDK, be sure it has been installed. Call Stack (most recent call first): yujin_ocs/yocs_keyop/CMakeLists.txt:3 (find_package) -- Configuring incomplete, errors occurred! See also "/home/EPRobot/robot_ws/build/CMakeFiles/CMakeOutput.log". See also "/home/EPRobot/robot_ws/build/CMakeFiles/CMakeError.log". Makefile:9560: recipe for target 'cmake_check_build_system' failed make: *** [cmake_check_build_system] Error 1 Invoking "make cmake_check_build_system" failed EPRobot@EPRobot:~/robot_ws$ source devel/setup.bash # 在每次打开新终端时运行

PS D:\code\pythonProject1> pytest scripts/test_import.py ============================================================== test session starts =============================================================== platform win32 -- Python 3.11.9, pytest-8.1.1, pluggy-1.4.0 -- C:\Users\1\AppData\Local\Programs\Python\Python311\python.exe cachedir: .pytest_cache metadata: {'Python': '3.11.9', 'Platform': 'Windows-10-10.0.19045-SP0', 'Packages': {'pytest': '8.1.1', 'pluggy': '1.4.0'}, 'Plugins': {'allure-pytest': '2.13.5', 'html': '4.1.1', 'metadata': '3.1.1'}, 'JAVA_HOME': 'C:\\Program Files\\Java\\jdk-21'} rootdir: D:\code\pythonProject1 configfile: pytest.ini plugins: allure-pytest-2.13.5, html-4.1.1, metadata-3.1.1 collected 0 items / 1 error ===================================================================== ERRORS ===================================================================== ____________________________________________________ ERROR collecting scripts/test_import.py _____________________________________________________ ImportError while importing test module 'D:\code\pythonProject1\scripts\test_import.py'. Hint: make sure your test modules/packages have valid Python names. Traceback: C:\Users\1\AppData\Local\Programs\Python\Python311\Lib\importlib\__init__.py:126: in import_module return _bootstrap._gcd_import(name[level:], package, level) scripts\test_import.py:5: in <module> from page.element import ActionElement E ModuleNotFoundError: No module named 'page' ============================================================ short test summary info ============================================================= ERROR scripts/test_import.py !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! =======================================================

-- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- mav_state_machine_msgs: 1 messages, 1 services -- +++ processing catkin package: 'mav_system_msgs' -- ==> add_subdirectory(mav_comm/mav_system_msgs) CMake Deprecation Warning at mav_comm/mav_system_msgs/CMakeLists.txt:1 (cmake_minimum_required): Compatibility with CMake < 2.8.12 will be removed from a future version of CMake. Update the VERSION argument <min> value or use a ...<max> suffix to tell CMake that the project does not need compatibility with older versions. -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- mav_system_msgs: 2 messages, 0 services -- +++ processing catkin package: 'rotors_comm' -- ==> add_subdirectory(rotors_simulator/rotors_comm) CMake Deprecation Warning at rotors_simulator/rotors_comm/CMakeLists.txt:1 (cmake_minimum_required): Compatibility with CMake < 2.8.12 will be removed from a future version of CMake. Update the VERSION argument <min> value or use a ...<max> suffix to tell CMake that the project does not need compatibility with older versions. -- Using these message generators: gencpp;geneus;genlisp;gennodejs;genpy -- Could NOT find octomap_msgs (missing: octomap_msgs_DIR) -- Could not find the required component 'octomap_msgs'. The following CMake error indicates that you either need to install the package with the same name or change your environment so that it can be found. CMake Error at /home/zk/ros_catkin_ws/install_isolated/share/catkin/cmake/catkinConfig.cmake:83 (find_package): Could not find a package configuration file provided by "octomap_msgs" with any of the following names: octomap_msgsConfig.cmake octomap_msgs-config.cmake Add the installation prefix of "octomap_msgs" to CMAKE_PREFIX_PATH or set "octomap_msgs_DIR" to a directory containing one of the above files. If "octomap_msgs" provides a separate development package or SDK, be sure it has been installed. Call Stack (most recent call first): rotors_simulator/rotors_comm/CMakeLists.txt:3 (find_package) -- Configuring incomplete, errors occurred! See also "/home/zk/catkin_ws/build/CMakeFiles/CMakeOutput.log". make: *** [Makefile:282:cmake_check_build_system] 错误 1 Invoking "make cmake_check_build_system" failed

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