CODEWITHSUNDEEP
tensorflowdeep-learningtensorboardobject-detection-apiloss
Ruslan
Ruslan

Reputation: 23

Plot validation loss in Tensorflow Object Detection API

I'm using Tensorflow Object Detection API for detection and localization of one class object in images. For these purposes, I use the pre-trained faster_rcnn_resnet50_coco_2018_01_28 model.

I want to detect under/overfitting after training the model. I see training loss, but after evaluating Tensorboard only shows mAP and Precision metrics and no loss.

Is this possible to plot a validation loss on Tensorboard too?

Upvotes: 2

Views: 4094

Answers (3)

waleed tawfiq al shaibani
waleed tawfiq al shaibani

Reputation: 11

Using model_main.py for training gives two curves in tensorboard. They supposed to be train and validation losses.

you can use the following command at CMD.

python object_detection/model_main.py --num_eval_steps=10 --num_train_steps=50000 --alsologtostderr --pipeline_config_path=C:/DroneMaskRCNN/DroneMaskRCNN1/mask_rcnn_inception_v2_coco.config --model_dir=C:/DroneMaskRCNN/DroneMaskRCNN1/CP

Upvotes: 1

Marjan Moodi
Marjan Moodi

Reputation: 41

To see the validation curve you should change faster_rcnn_resnet50_coco.config:

1- comment max_evals line
2- set eval_interval_secs: 60 .
3- num_examples should be equal or less than the number of "files" that you have in "val.record" . 

eval_config: { . 
  num_examples: 600 . 
  eval_interval_secs: 60 . 
  # Note: The below line limits the evaluation process to 10 evaluations.  
  # Remove the below line to evaluate indefinitely.  
  # max_evals: 10 .
}

Upvotes: 4

netanel-sam
netanel-sam

Reputation: 1912

There is validation loss. Assuming you're using the latest API, the curve under "loss" is validation loss while "loss_1/2" is the training loss.

Upvotes: 7

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