我使用main对a对象检测模型进行了11个类(0=base+10个实际类)的训练_模型.py. 然后我想导出推理图使用导出推理推理_图形.py. 我使用与训练完全相同的pipeline_config_路径,并且trained_checkpoint_prefix参数引用型号.ckpt我受过训练。我收到以下错误:
InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape= [44] rhs shape= [360]
[[Node: save/Assign_526 = Assign[T=DT_FLOAT, _class=["loc:@SecondStageBoxPredictor/BoxEncodingPredictor/biases"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](SecondStageBoxPredictor/BoxEncodingPredictor/biases, save/RestoreV2:526)]]
标签地图:https://drive.google.com/file/d/1isVO81rbYRGNrSboUd_DQh03DOxWV5is/view?usp=sharing
配置文件:https://drive.google.com/file/d/1vFkKbU5cytWMJwyt7tztLPxAnQ_bVnNo/view?usp=sharing
Python:3.6.2 Tensorflow:1.3.0
你的labelmap和configs都不见了。请确保你的num_classes=11而不是90。在
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