tensorflow / tensorflow/models
How can I evaluate a pre-trained model?
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@pkulzc is already working on this.
Since Jun 17, 2020.
models:research:odapi
type:support
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Description
I have a group of images with ground truth detection boxes and I want to simply run them through a pre-trained model from the Model Zoo and get the, say, precision/recall/mAP between the ground truth boxes and predicted detections.
The solutions I've seen, in using eval.py or model_main.py all require pipeline_config files that I never configured since I'm not training the model. Is there maybe a workaround where I can specify my testing images somewhere in the pipeline_config to evaluate but not have them used in training?
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