구차니의 잡동사니 모음

pb 파일을 tensorboard에 끌어가면

간혹(?) graph 항목에 내용이 없는 경우가 있어서

어떻게 해야 해당 항목을 활성화 할 수 있나 검색중

[링크 : http://stackoverflow.com/questions/48391075]

writer = tf.summary.FileWriter("output", sess.graph)

[링크 : http://www.h2kinfosys.com/blog/tensorboard-how-to-use-tensorboard-for-graph-visualization/]

[링크 : http://www.tensorflow.org/tensorboard/graphs]

먼가 이상해서 하나하나 뜯어 보는중

[링크 : https://www.tensorflow.org/tutorials/load_data/tfrecord]

[링크 : https://www.kaggle.com/gauravchopracg/understanding-tfrecord-format]

학습을 하는건 돌아가는데 

탐지가 안되거나 입력 범위가 이상하거나 이런 문제가 있어서 확인하는데

tfrecord 에서는 학습에 필요한 이미지를 읽어서 넣어 두는 듯?

그 과정에서 원본이 들어가냐 bitmpa으로 들어가냐를 확인하는데

혹시나 해서 1년 이내 글로 찾아보니 업그레이드 된 generate_tfrecord.py 를 발견!

[링크 : https://github.com/EdjeElectronics/.../issues/427]

Trnasfer는 기존의 학습을 다 지우고

새로운 내용에 대한 학습을 하는 것이라면

LwF는 기존의 데이터에 추가로 학습을 하는 것.

[링크 : http://ai.stackexchange.com/questions/13644/]

transfer 는 학습된 모델에서 구조는 유지한채 학습 데이터를 날리고 

새로운 데이터로 학습하는걸 의미하는데

학습시에 양자화 범위를 지정해주는 학습도 존재하는 듯.

quant learning

def format_example(image, label):
  image = tf.cast(image, tf.float32)
  image = (image/127.5) - 1
  image = tf.image.resize(image, (IMG_SIZE, IMG_SIZE))
  return image, label

[링크 : https://www.tensorflow.org/tutorials/images/transfer_learning?hl=ko]

[링크 : https://github.com/EdjeElectronics/TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi]

기본으로 제공되는 건 없으려나?

[링크 : https://stackoverflow.com/questions/56766639/how-to-convert-ckpt-to-pb]

$ saved_model_cli convert tensorrt
usage: saved_model_cli convert [-h] --dir DIR --output_dir OUTPUT_DIR --tag_set TAG_SET {tensorrt} ...
saved_model_cli convert: error: the following arguments are required: --dir, --output_dir, --tag_set

yolo나 tensorflow 에서 학습/검증을 위한 이미지 라벨링 프로그램

pip3를 통해 설치가 가능하며 나름 깔끔한 디자인이다.

좀 아쉬운건, 수정하고 다음 이미지 누르면 저장할까요 물어보는 것도 아니고

자동 저장되는 것도 아닌 그냥 날아간다는 점 -_ㅠ

[링크 : https://github.com/tzutalin/labelImg]

[링크 : http://blog.naver.com/baek2sm/221886666289]

[링크 : https://hwauni.tistory.com/entry/API-Custom-Object-Detection-API-Tutorial-데이터-준비-Part-1]

텐서플로우 설치 문서를 다시 보는데

docker를 설치하는 과정이 있었네.. 머지?

[링크 : http://www.tensorflow.org/install/gpu?hl=ko]

[링크 : http://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf2.md#installation]

[링크 : http://blog.softwaremill.com/setting-up-tensorflow-with-gpu-acceleration-the-quick-way-add80cd5c988]

$ wget https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/python/tools/import_pb_to_tensorboard.py
$ python3 import_pb_to_tensorboard.py --model_dir ./ --log_dir ./tensorboard
$ tensorboard --logdir ./tensorboard

[링크 : https://aciddust.github.io/blog/post/Tensorflow-pb파일-TensorBoard에-올리기/]

[링크 : https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/python/tools/import_pb_to_tensorboard.py]

INFO:tensorflow:depth of additional conv before box predictor: 0
I0407 19:04:11.848860 140671031727936 convolutional_keras_box_predictor.py:153] depth of additional conv before box predictor: 0
INFO:tensorflow:depth of additional conv before box predictor: 0
I0407 19:04:11.849254 140671031727936 convolutional_keras_box_predictor.py:153] depth of additional conv before box predictor: 0
INFO:tensorflow:depth of additional conv before box predictor: 0
I0407 19:04:11.849459 140671031727936 convolutional_keras_box_predictor.py:153] depth of additional conv before box predictor: 0
INFO:tensorflow:depth of additional conv before box predictor: 0
I0407 19:04:11.849658 140671031727936 convolutional_keras_box_predictor.py:153] depth of additional conv before box predictor: 0
INFO:tensorflow:depth of additional conv before box predictor: 0
I0407 19:04:11.849853 140671031727936 convolutional_keras_box_predictor.py:153] depth of additional conv before box predictor: 0
INFO:tensorflow:depth of additional conv before box predictor: 0
I0407 19:04:11.850045 140671031727936 convolutional_keras_box_predictor.py:153] depth of additional conv before box predictor: 0

WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.meta_architectures.ssd_meta_arch.SSDMetaArch object at 0x7ff0245f8880>, because it is not built.
W0407 19:04:15.019573 140671031727936 save_impl.py:77] Skipping full serialization of Keras layer <object_detection.meta_architectures.ssd_meta_arch.SSDMetaArch object at 0x7ff0245f8880>, because it is not built.
2021-04-07 19:04:26.913764: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.

W0407 19:04:44.291487 140671031727936 save.py:236] Found untraced functions such as BoxPredictor_layer_call_and_return_conditional_losses, BoxPredictor_layer_call_fn, BoxPredictor_layer_call_fn, BoxPredictor_layer_call_and_return_conditional_losses, BoxPredictor_layer_call_and_return_conditional_losses while saving (showing 5 of 125). These functions will not be directly callable after loading.
W0407 19:04:45.480654 140671031727936 save.py:236] Found untraced functions such as BoxPredictor_layer_call_and_return_conditional_losses, BoxPredictor_layer_call_fn, BoxPredictor_layer_call_fn, BoxPredictor_layer_call_and_return_conditional_losses, BoxPredictor_layer_call_and_return_conditional_losses while saving (showing 5 of 125). These functions will not be directly callable after loading.

pb

[링크 : https://github.com/penseeartificielle/mobilenet-ssd-detection-example/.../test-video-example.py]

tflite

[링크 : https://github.com/EdjeElectronics/.../blob/master/TFLite_detection_video.py]

[링크 : https://github.com/finnickniu/tensorflow_object_detection_tflite]