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ubuntu 20.04 paddle 2.4.2 nvidia 单卡 v100 32G
执行命令:
python tools/train.py -c configs/yolov5u/yolov5up6_s_300e_coco.yml --eval --amp
调整了数据集的样本数量,使用roadsign_voc,样本数量少于32的时候会报错。所以自己选取原样本中35个样本去测试,我的标签数量是250个,抽取的样本尺寸是2048*2048。yolov5up6_s_300e_coco.yml 相关的配置,除了数据集路径外,其他没做改动。抽取的样本如链接: https://pan.baidu.com/s/1TvUUjSGGShppZAnewPURPA?pwd=cnen 提取码: cnen
报错如下:
The text was updated successfully, but these errors were encountered:
请先尝试yolov5s或别的模型,如果也报同样的错,则可认为是数据集制作的问题。
Sorry, something went wrong.
@nemonameless 出现同样的问题,也已在其他模型训练过
你好,如还需要帮看下问题的话还请提供下您的数据集。库里的模型是在coco voc上验证过的,应该是大部分数据集边界情况都覆盖了。
nemonameless
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ubuntu 20.04
paddle 2.4.2
nvidia 单卡 v100 32G
执行命令:
调整了数据集的样本数量,使用roadsign_voc,样本数量少于32的时候会报错。所以自己选取原样本中35个样本去测试,我的标签数量是250个,抽取的样本尺寸是2048*2048。yolov5up6_s_300e_coco.yml 相关的配置,除了数据集路径外,其他没做改动。抽取的样本如链接: https://pan.baidu.com/s/1TvUUjSGGShppZAnewPURPA?pwd=cnen 提取码: cnen
报错如下:
The text was updated successfully, but these errors were encountered: