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 It now has been replaced by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