LOGGER.warning(f'{prefix}WARNING ⚠️ No labels found in {path}. {HELP_URL}') x['hash'] = get_hash(self.label_files + self.im_files) x['results'] = nf, nm, ne, nc, len(self.im_files) x['msgs'] = msgs # warnings x['version'] = self.cache_version # cache version t...
train: WARNING⚠️No labels found in /content/EMSL/Train/Images.cache. Seehttps://docs.ultralytics.com/yolov5/tutorials/train_custom_data train: New cache created: /content/EMSL/Train/Images.cache Traceback (most recent call last): ...
WARNING: Dataset not found, nonexistent paths: ['/content/gdrive/MyDrive/Object/yolov7/content/gdrive/MyDrive/Object/yolov7/data/val/img'] Traceback (most recent call last): File "train.py", line 616, in train(hyp, opt, device, tb_writer) ...
PackageNotFoundError as e: if hard: raise ModuleNotFoundError(f"WARNING ⚠️ {current} package is required but not installed") from e else: return False if not required: # 如果所需版本为空 return True op = "" version = "" result = True c = parse_version(current) # 将当前版本解...
PackageNotFoundError as e: if hard: raise ModuleNotFoundError(f"WARNING ⚠️ {current} package is required but not installed") from e else: return False if not required: # 如果所需版本为空 return True op = "" version = "" result = True c = parse_version(current) # 将当前版本...
exists() for x in val): print('\nWARNING: Dataset not found, nonexistent paths: %s' % [str(x) for x in val if not x.exists()]) # 如果下载地址s和下载标记(flag)autodownload不为空, 就直接下载 if s and autodownload: # download script # 如果下载地址s是http开头就从url中下载数据集...
cls=batch["cls"].view(-1),# warning: use .view(), not .squeeze() for Classify modelsfname=self.save_dir /f"val_batch{ni}_labels.jpg", names=self.names, on_plot=self.on_plot, )# 绘制输入图像上的预测边界框并保存结果defplot_predictions(self, batch, preds, ni):"""Plots predicted...
LOGGER.warning(f"WARNING ⚠️ no labels found in {task} set, can not compute metrics without labels") # Print results per class if (verbose or (nc < 50 and not training)) and nc > 1 and len(stats): for i, c in enumerate(ap_class): LOGGER.info(pf % (names[c], seen...
warning("WARNING ⚠️ Upgrade to torch>=2.0.0 for deterministic training.") else: # 关闭确定性算法,允许非确定性行为 torch.use_deterministic_algorithms(False) torch.backends.cudnn.deterministic = False class ModelEMA: """ Updated Exponential Moving Average (EMA) from https://github.com/r...
(dataset, 'rect', False) and shuffle: LOGGER.warning("WARNING ⚠️ 'rect=True' is incompatible with DataLoader shuffle, setting shuffle=False") shuffle = False workers = 0 return build_dataloader(dataset, batch_size, workers, shuffle, rank) def preprocess_batch(self, batch): batch['img...