I've correctly installed Tensorflow Object Detection API according to the provided documentation. However, when I need to train my network there is no train.py file in the research/object_detection directory. Is there anything I can do to fix this?
Link: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/installation.md
You should refer to Running locally section on the tutorial page.
Here is the sample configuration:
#From the tensorflow/models/research/ directory
PIPELINE_CONFIG_PATH={path to pipeline config file}
MODEL_DIR={path to model directory}
NUM_TRAIN_STEPS=50000
NUM_EVAL_STEPS=2000
python object_detection/model_main.py \
--pipeline_config_path=${PIPELINE_CONFIG_PATH} \
--model_dir=${MODEL_DIR} \
--num_train_steps=${NUM_TRAIN_STEPS} \
--num_eval_steps=${NUM_EVAL_STEPS} \
--alsologtostderr
and to run tensorboard:
tensorboard --logdir=${MODEL_DIR}
in the newest merge the train and eval moved to legacy dir. You can go to a previous version if you work with a tutorial.
For some clarification, as aforementioned by Derek Chow, it seems the train and evaluation python scripts were recently (~6 days ago) moved into the 'legacy' directory. Assuming you wanted to continue using the old way..
If one was beginning training by calling:
python train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/ssd_mobilenet_v1_pets.config
One would know begin training by calling:
python legacy/train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/ssd_mobilenet_v1_pets.config
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