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# Frequently Asked Questions |
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## Q: How can I ensure that all the groundtruth boxes are used during train and eval? |
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A: For the object detecion framework to be TPU-complient, we must pad our input |
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tensors to static shapes. This means that we must pad to a fixed number of |
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bounding boxes, configured by `InputReader.max_number_of_boxes`. It is |
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important to set this value to a number larger than the maximum number of |
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groundtruth boxes in the dataset. If an image is encountered with more |
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bounding boxes, the excess boxes will be clipped. |
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## Q: AttributeError: 'module' object has no attribute 'BackupHandler' |
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A: This BackupHandler (tf_slim.tfexample_decoder.BackupHandler) was |
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introduced in tensorflow 1.5.0 so runing with earlier versions may cause this |
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issue. It now has been replaced by |
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object_detection.data_decoders.tf_example_decoder.BackupHandler. Whoever sees |
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this issue should be able to resolve it by syncing your fork to HEAD. |
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Same for LookupTensor. |
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## Q: AttributeError: 'module' object has no attribute 'LookupTensor' |
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A: Similar to BackupHandler, syncing your fork to HEAD should make it work. |
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## Q: Why can't I get the inference time as reported in model zoo? |
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A: The inference time reported in model zoo is mean time of testing hundreds of |
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images with an internal machine. As mentioned in |
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[Tensorflow detection model zoo](detection_model_zoo.md), this speed depends |
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highly on one's specific hardware configuration and should be treated more as |
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relative timing. |
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