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Tensorboard logger for DeepDetect server JSON output
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Version 0.4

Works with: Python 2.7

Converts logs to "TensorBoard compatible" data.

Parameters (except for del_dir, they must be written between quotes, even if left empty):

  • log_src = string, log source to analyze (flow, log file or any Python dict / JSON object).
  • base_dir = string, general cache directory used by tensorboard. If not existing, will be created.
  • sub_dir = string, subdirectory of the current run used by tensorboard. If not existing, will be created.
  • del_dir = bolean, False if ommited. If set to False, the new graph is displayed after the preceding one, if any. If set to True, the tensorboard cache directory (base_dir/sub_dir) will be deleted and the new graph will be the only one to appear.



from dd_board_logger import DDBoard


read_dd = DDBoard(base_dir, sub_dir, del_dir)

Then, with a log flow:


Or, with a log file:


Or with external data (need "import json, time", for this example):

log_src = open(json_src, 'r')
for line in log_src:

json_src = open(log_src, 'r')
for line in json_src:
	json_obj = json.loads(line)

You can then start TensorBoard in console:

$tensorboard --logdir base_dir

(base_dir without quotes, here. Ex: tensorboard --logdir runs)

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