Closed diligentpeng closed 4 years ago
请问下使用的是什么模型呢,另外训练使用的num_classes也是29吗
模型是:faster_rcnn_r50_fpn_1x 训练使用的num_classes是29
rchitecture: FasterRCNN max_iters: 30000 use_gpu: true snapshot_iter: 6000 log_smooth_window: 100 log_iter: 100 save_dir: output pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar metric: VOC map_type: 11point weights: output/faster_rcnn_r50_fpn_1x_2/model_final num_classes: 29
rcnn系列模型会输出背景类,因此num_classes增加背景类,同时with_ground也设置为True,后续我们提供下rcnn在voc数据集上的配置文件以便参考
好的,谢谢
打印信息: The 'num_classes'(number of classes) you set is 29, and 'with_background' in 'dataset' sets False. So please note the actual number of categories is 29.
config文件中设置: metric: VOC num_classes: 29 以及 use_default_label: true with_background: false
PaddleDetection/ppdet/data/source/voc.py文件中的类别也改为了对应的29类