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自定义数据集上的tensorflow对象检测API评估

[英]tensorflow object-detection api eval on custom dataset

I have a custom dataset that I trained using tensorflow object-detection api [Faster RCNN]. 我有一个使用Tensorflow对象检测API [Faster RCNN]训练的自定义数据集。

I saved the model checkpoints. 我保存了模型检查点。 Now, I want to run this model on my eval set. 现在,我想在我的评估集上运行该模型。 But, I cannot find the script that I use to run on eval set. 但是,我找不到用于在评估集上运行的脚本。 I have tfrecord files for eval set. 我有efset的tfrecord文件。

How do I run the eval script from the object-detection api for my own saved model checkpoint? 如何为自己保存的模型检查点从对象检测api运行评估脚本? I couldn't find the script. 我找不到脚本。

You are looking fot the eval.py . 您正在寻找eval.py。

Run this script with the command: 使用以下命令运行此脚本:

python eval.py \
--logtostderr \
--pipeline_config_path=PATH_TO_YOUR_CONFIG_FILE \
--checkpoint_dir=PATH_TO_CHECKPOINT \
--eval_dir=OUTPUT_PATH

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