# 标签文件 需要自己新建文件 class_id_map_file: dataset/foods/label_list.txt 按照对应的进行编写: 如食品分类(要对照之前的txt的类别确认无误) 0 beef_carpaccio 1 baby_back_ribs 2 baklava 3 apple_pie 4 beef_tartare 现在的PaddleClas/dataset/foods/下是这样的: 5.2 开始训练 In [19] # 提示...
修改class_id_map_file: ../species.txt 修改标签映射文件 In [ ] # 切换目录到PaddleClas下 %cd /home/aistudio/PaddleClas # 开始训练 !python tools/train.py -c ./ppcls/configs/quick_start/ResNet50_vd.yaml -o Arch.pretrained=True 4.4意外中断,重新训练 添加-o Global.checkpoints参数,后面跟上...
有些特定字符转义之后出现问题 #划分数据集importcodecsimportosimportrandomimportshutilfromPILimportImagetrain_ratio=4.0/5all_file_dir='PaddleClas/dataset/fer62013'class_list=[cforcinos.listdir(all_file_dir)ifos.path.isdir(os.path.join(all_file_dir,c))andnotc.endswith('Set')andnotc.startswith(...
mkdir ppcls/configs/peach # 复制一份配置文件并根据数据集对应修改 cp ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml ppcls/configs/peach/ # 需要修改的地方如下 pretrained_model: ./output/PPLCNetV2_base_ssld_pretrained class_num: 4 Train: dataset: name: MultiScaleDataset image_root: ...
花卉class_num:102 train/val:5789/23960.77790.9892 手绘简笔画class_num:18 train/val:1007/4320.87850.9107 植物叶子class_num:6 train/val:5256/22780.82120.8385 集装箱车辆class_num:115 train/val:4879/20940.6230.9524 椅子class_num:5 train/val:169/780.85570.9077 ...
花卉class_num:102 train/val:5789/23960.77790.9892 手绘简笔画class_num:18 train/val:1007/4320.87850.9107 植物叶子class_num:6 train/val:5256/22780.82120.8385 集装箱车辆class_num:115 train/val:4879/20940.6230.9524 椅子class_num:5 train/val:169/780.85570.9077 ...
本次分享将带领大家从0到1完成一个图像分类任务的模型训练评估和推理部署全流程,项目将采用以PaddleClas为核心的飞浆深度学习套装进行开发,并总结开发过程...
可以通过参数class_id_map_file指定class id与lable的对应关系。PaddleClas默认使用ImageNet1K的label_name(ppcls/utils/imagenet1k_label_list.txt)。 class_id_map_file文件内容格式应为: class_id<space>class_name<\n> 例如: 0 tench, Tinca tinca 1 goldfish, Carassius auratus 2 great white shark, ...
class MNIST(fluid.dygraph.Layer): def __init__(self): super(MNIST, self).__init__() # self.linear1 = Linear(input_dim=28*28,output_dim=10,act=None) # self.linear2 = Linear(input_dim=10,output_dim=10,act='sigmoid') # self.linear3 = Linear(input_dim=10,output_dim=1,act='...
class Settings(object):def __init__(self,dataset=None,data_dir=None,label_file=None,resize_h=300,resize_w=300,mean_value=[127.5, 127.5, 127.5],apply_distort=True,apply_expand=True,ap_version='11point'):self._dataset = datasetself._ap_version = ap_version# 把data_dir替换为数据所在路径...