Create tf records

python ./create_tf_record.py
--data_dir=/home/arpit/training
--output_dir=/home/arpit/training/data
--label_map_path=/home/arpit/training/data/label_map.pbtxt

python train.py
--logtostderr
--pipeline_config_path=/home/arpit/training/models/model/ssd_mobilenet_v1_coco.config
--train_dir=/home/arpit/training/models/model/train

python eval.py
--logtostderr
--pipeline_config_path=/home/arpit/training/models/model/ssd_mobilenet_v1_coco.config
--checkpoint_dir=/home/arpit/training/models/model/train
--eval_dir=/home/arpit/training/models/model/eval

python train.py
--logtostderr
--pipeline_config_path=/home/arpit/training/models/model/faster_rcnn_resnet101_coco.config
--train_dir=/home/arpit/training/models/model/train

python eval.py
--logtostderr
--pipeline_config_path=/home/arpit/training/models/model/faster_rcnn_resnet101_coco.config
--checkpoint_dir=/home/arpit/training/models/model/train
--eval_dir=/home/arpit/training/models/model/eval

import tensorflow as tf

g = tf.GraphDef() g.ParseFromString(open(“path/to/mymodel.pb”, “rb”).read()) [n for n in g.node if n.name.find(“input”) != -1] # same for