https://github.com/akshaypatil15/image_classification_inceptionv3

We are going to use inception v3 for mobile manufacture image based classification.
https://github.com/akshaypatil15/image_classification_inceptionv3

classification image-classification image-classification-inceptionv3 inception neural-network tensorflow

Last synced: about 2 months ago
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We are going to use inception v3 for mobile manufacture image based classification.

• Host: GitHub
• URL: https://github.com/akshaypatil15/image_classification_inceptionv3
• Owner: Akshaypatil15
• License: apache-2.0
• Created: 2019-08-03T17:52:32.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-08-03T18:28:43.000Z (over 5 years ago)
• Last Synced: 2023-12-21T09:49:41.652Z (about 1 year ago)
• Topics: classification, image-classification, image-classification-inceptionv3, inception, neural-network, tensorflow
• Language: Python
• Size: 59 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# 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