File "/home/zhxk/.local/bin/yolo", line 8, in <module> sys.exit(entrypoint()) File "/home/zhxk/.local/lib/python3.8/site-packages/ultralytics/yolo/cfg/__init__.py", line 249, in entrypoint getattr(model, mode)(verbose=True, **overrides) File "/home/zhxk/.local/lib/python3.8/site-packages/ultralytics/yolo/engine/model.py", line 207, in train self.trainer.train() File "/home/zhxk/.local/lib/python3.8/site-packages/ultralytics/yolo/engine/trainer.py", line 183, in train self._do_train(int(os.getenv("RANK", -1)), world_size) File "/home/zhxk/.local/lib/python3.8/site-packages/ultralytics/yolo/engine/trainer.py", line 302, in _do_train self.loss, self.loss_items = self.criterion(preds, batch) File "/home/zhxk/.local/lib/python3.8/site-packages/ultralytics/yolo/v8/detect/train.py", line 76, in criterion return self.compute_loss(preds, batch) File "/home/zhxk/.local/lib/python3.8/site-packages/ultralytics/yolo/v8/detect/train.py", line 174, in __call__ _, target_bboxes, target_scores, fg_mask, _ = self.assigner( File "/home/zhxk/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl return forward_call(*input, **kwargs) File "/home/zhxk/.local/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 28, in decorate_context return func(*args, **kwargs) File "/home/zhxk/.local/lib/python3.8/site-packages/ultralytics/yolo/utils/tal.py", line 97, in forward target_gt_idx, fg_mask, mask_pos = select_highest_overlaps(mask_pos, overlaps, self.n_max_boxes) File "/home/zhxk/.local/lib/python3.8/site-packages/ultralytics/yolo/utils/tal.py", line 44, in select_highest_overlaps if fg_mask.max() > 1: # one anchor is assigned to multiple gt_bboxes RuntimeError: CUDA error: device-side assert triggered CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1. Sentry is attempting to send 2 pending error messages Waiting up to 2 seconds Press Ctrl-C to quit THCudaCheck FAIL file=/pytorch/aten/src/THC/THCCachingHostAllocator.cpp line=278 error=710 : device-side assert triggered
时间: 2023-08-21 19:02:02 浏览: 75
根据您提供的错误信息,这是一个与CUDA相关的错误。出现此错误通常是由于CUDA内核遇到了问题,触发了设备端断言。这可能是由于使用了不正确的参数或数据类型,或者是由于内存不足等问题引起的。
为了调试此问题,您可以尝试以下几个步骤:
1. 确保您的CUDA版本与使用的深度学习框架兼容,并且已正确安装CUDA驱动程序和依赖项。
2. 检查您的代码和模型配置是否正确,特别是与CUDA相关的部分。确保正确设置了设备(device)和数据类型(dtype)。
3. 如果您的显卡内存不足,可以尝试减小批量大小(batch size)或模型大小,或者考虑使用更高性能的显卡。
4. 尝试将环境变量`CUDA_LAUNCH_BLOCKING`设置为1,以便在CUDA错误发生时阻塞程序并打印更详细的错误信息。
如果以上步骤都没有解决问题,您可以尝试在相关社区或论坛上提供更详细的错误信息以寻求帮助。
相关问题
File "Car_recognition.py", line 280, in <module> ori_img = draw_result(img, dict_list) File "Car_recognition.py", line 223, in draw_result orgimg = cv2ImgAddText(orgimg, car_color_str, rect_area[0], rect_area[1], (0, 255, 0), height_area) File "/home/zhxk/sufan/license_recognition_server/license_recognition_server/utils/cv_puttext.py", line 9, in cv2ImgAddText fontText = ImageFont.truetype( File "/home/zhxk/.local/lib/python3.8/site-packages/PIL/ImageFont.py", line 996, in truetype return freetype(font) File "/home/zhxk/.local/lib/python3.8/site-packages/PIL/ImageFont.py", line 993, in freetype return FreeTypeFont(font, size, index, encoding, layout_engine) File "/home/zhxk/.local/lib/python3.8/site-packages/PIL/ImageFont.py", line 248, in __init__ self.font = core.getfont( OSError: cannot open resource
这个错误似乎是Pillow库在加载字体文件时出现问题。您可以尝试以下解决方法:
1. 检查字体路径是否正确:您需要在cv_puttext.py文件中检查字体路径是否正确。确保字体文件存在并且路径正确。
2. 安装所需的字体:如果字体文件确实存在但仍出现错误,请尝试在系统中安装所需的字体。命令如下:
```
sudo apt-get install ttf-mscorefonts-installer
```
3. 更新Pillow库:如果上述解决方法都无法解决问题,请尝试更新Pillow库。命令如下:
```
pip install -U Pillow
```
希望这些解决方法能够帮助您解决问题。
Traceback (most recent call last): File "/usr/lib/python3.8/threading.py", line 932, in _bootstrap_inner self.run() File "/usr/lib/python3.8/threading.py", line 870, in run self._target(*self._args, **self._kwargs) File "/home/zhxk/sufan/PLATE/1.30/1.30/weigh11_23/localcheck_checking.py", line 138, in load_check myJudge.update(moment, detects, frame,camera) # 按照跟踪结果,作出判断 #frame File "/home/zhxk/sufan/PLATE/1.30/1.30/weigh11_23/load_judge.py", line 145, in update one.plate_num(cropped) File "/home/zhxk/sufan/PLATE/Car_recognition-master/one.py", line 259, in plate_num detect_model = load_model(detect_model, device) # 初始化检测模型 File "/home/zhxk/sufan/PLATE/Car_recognition-master/one.py", line 63, in load_model model = attempt_load(weights, map_location=device) # load FP32 model File "/home/zhxk/sufan/PLATE/Car_recognition-master/models1/experimental.py", line 121, in attempt_load model.append(torch.load(w, map_location=map_location)['model'].float().fuse().eval()) # load FP32 model File "/home/zhxk/.local/lib/python3.8/site-packages/torch/serialization.py", line 607, in load return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args) File "/home/zhxk/.local/lib/python3.8/site-packages/torch/serialization.py", line 882, in _load result = unpickler.load() File "/home/zhxk/.local/lib/python3.8/site-packages/torch/serialization.py", line 875, in find_class return super().find_class(mod_name, name)
这个错误是由于在加载模型时出现的。根据错误信息,似乎是在加载模型的过程中无法找到所需的类或属性。
可能的原因是在加载模型时,使用了一个不存在的类或属性。请检查加载模型的代码,确保它所依赖的类或属性是正确的,并且已经导入到了代码中。
另外,还要确保模型文件存在并且路径正确。如果模型文件不存在或路径不正确,也会导致加载模型失败。
如果以上检查都没有问题,那么可能是模型文件本身出现了问题。你可以尝试重新下载或获取正确的模型文件,并将其替换原有的模型文件。
如果问题仍然存在,请提供更多的代码和错误信息,以便我能够更好地帮助你解决问题。