Comments (1)
haezu
commented on June 14, 2024
train_image_classifier.py 실행시에 옵션을 주면 된다.
python train_image_classifier.py --train_dir=/home/edu/haejoo/python/naver/sample_images/log_inception_resnet_v2_naver_6/ --dataset_dir=/home/edu/haejoo/python/naver/naver/ --dataset_name=naver --dataset_split_name=train --max_number_of_steps=1000000 --batch_size=30 --model_name=inception_resnet_v2 --checkpoint_path=/home/edu/haejoo/python/keras/keras-inception-resnet-v2/models/inception_resnet_v2_2016_08_30.ckpt --checkpoint_exclude_scopes=InceptionResnetV2/Logits,InceptionResnetV2/AuxLogits,InceptionResnetV2/Conv2d_7b_1x1,InceptionResnetV2/Block8/Conv2d_1x1 --trainable_scopes=InceptionResnetV2/Logits,InceptionResnetV2/AuxLogits,InceptionResnetV2/Conv2d_7b_1x1,InceptionResnetV2/Block8/Conv2d_1x1
trainable_scopes 를 위한 node name 은 tensorboard 를 통해 graph를 확인하면 알 수 있다.
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Related Issues (7)
- image classification -> image clustering
- 클러스터링 계층적 알고리즘에서 유사도로 DELF모듈 사용하는 문제
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- extract_features_finetune.py 에서 image 를 input tensor에 넣을 때 inception_resnet_v2.pb 의 input shape와 맞지 않는다. HOT 1
- InvalidArgumentError (see above for traceback): Nan in summary histogram for: InceptionResnetV2/AuxLogits/Conv2d_2a_5x5/BatchNorm/moving_variance_1 HOT 1
- how can i use triplet loss in data clustering?
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