I am using Tensorflow's object detection framework. Training and evaluation jobs are going well, but in tensorboard I am only able to see 10 images for the evaluation job. Is there a way to increase this number to look at more images? I tried changing the config file:
eval_config: {
num_examples: 1000
max_evals: 50
}
eval_input_reader: {
tf_record_input_reader {
input_path: "xxx/eval.record"
}
label_map_path: "xxx/label_map.pbtxt"
shuffle: false
num_readers: 1
}
I thought the max_eval
parameter would change this but it doesn't.
This is the command i'm running for the evaluation job:
python ../models/research/object_detection/eval.py \
--logtostderr \
--pipeline_config_path=xxx/ssd.config \
--checkpoint_dir="xxx/train/" \
--eval_dir="xxx/eval"
Open the settings menu, and note that the default pagination limit value is 12.
--logdir is the directory you will create data to visualize. Files that TensorBoard saves data into are called event files. Type of data saved into the event files is called summary data. Optionally you can use --port=<port_you_like> to change the port TensorBoard runs on.
Probably the easiest way is to add command line argument --samples_per_plugin
Full example
tensorboard --logdir . --samples_per_plugin=images=100
https://github.com/tensorflow/tensorboard/issues/1012
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