image_classification_inceptionV3

We are going to use inception v3 for mobile manufacture image based classification.

Generating Record files

Here we have sample record files in data directory, if you have your own data is should be splitted in train-val folder. For generating your own record files, run following command.

$ TRAIN_DIR=PATH_TO_YOUR_TRAIN_FOLDER
$ VALIDATION_DIR=PATH_TO_YOUR_VALIDATION_FOLDER
$ OUTPUT_DIRECTORY=PATH_TO_YOUR_OUTPUT_FOLDER
$ LABELS_FILE=TXT_FILE_PATH

$ python src/build_image_data.py \
	--train_directory=$TRAIN_DIR \
	--validation_directory=$VALIDATION_DIR \
	--output_directory=$OUTPUT_DIRECTORY \
	--labels_file=$LABELS_FILE

Download Pre-Trained Inception-v3 checkpoint

$ wget http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz

Train Model

$ TRAIN_DIR=PATH_TO_YOUR_DATA_FOLDER
$ CHECKPOINT_PATH=PATH_TO_PRETRAINED_INCEPTION_MODEL_FOLDER/inception_v3.ckpt
$ TRAINED_MODEL_DIR=PATH_TO_SAVE_TRAINED_MODEL_DIR

$ python src/slim/train_image_classifier.py \
	--train_dir=$TRAINED_MODEL_DIR \
	--dataset_dir=$TRAIN_DIR \
	--dataset_name=cell_phone_data \
	--dataset_split_name=train \
	--model_name=inception_v3 \
	--batch_size=32 \
	--checkpoint_path=$CHECKPOINT_PATH \
	--checkpoint_exclude_scopes=InceptionV3/Logits,InceptionV3/AuxLogits \
	--trainable_scopes=InceptionV3/Logits,InceptionV3/AuxLogits