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Errors_faced_in_TF_Object_detection.md

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Errors faced during the training for tensorflow object detection.

  1. ValueError: Tried to convert 't' to a tensor and failed. Error: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted [].
  • Go to models/research/object_detection/utils/learning_schedules.py lines 167-169. Change from
rate_index = tf.reduce_max(tf.where(tf.greater_equal(global_step, boundaries),range(num_boundaries),[0] * num_boundaries))

to

rate_index = tf.reduce_max(tf.where(tf.greater_equal(global_step, boundaries), list(range(num_boundaries)),[0] * num_boundaries))
  1. ModuleNotFoundError: No module named 'utils'
  • Add the models/research/slim,models/research/ and models/research/object-detection in PYTHONPATH.

  1. Check for the tfrecord_generator.py and the .csv file before running it as all the classes have to be covered.

  2. Check for the .config file if the number of classes has been set-up properly and the filepaths to the labelmap.pbtxt,'training.ckpt' and the training and testing files.

  3. CUDNN_STATUS_NOT_INITIALIZED:Go to trainer.py and go to the following line: session_config = tf.ConfigProto(allow_soft_placement=True, log_device_placement=False) replace it with: gpu_options = tf.GPUOptions(allow_growth=True) session_config = tf.ConfigProto(allow_soft_placement=True, log_device_placement=False, gpu_options=gpu_options)

Or check if the versions of CUDA and CuDNN are supported by TensorFlow.