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TextBoxes-TensorFlow

TextBoxes re-implementation using tensorflow. Much more info can be found in Textbox and SSD This project is greatly inspired by slim project
And many functions are modified based on SSD-tensorflow project
Now the pipeline is much clear and can be resued in any tf projects.

Author: Daitao Xing : [email protected] Jin Huang : [email protected]

Progress

2017/ 03/14  

data_processing phase finished Test:

1. Download the dataset, put 1/ folder and gt.mat uner ddata/sythtext/ folder(will wirte script)   
2. python datasets/data2record.py    
3. python image_processing.py    

output: batch_size * 300 * 300 * 3 image

2017/ 03/17  

Finish the design of training(can start training)

TASET_DIR=./data/sythtext/
TRAIN_DIR=./logs/
python Textbox_train.py \
	--train_dir=${TRAIN_DIR} \
	--dataset_dir=${DATASET_DIR} \
	--save_summaries_secs=60 \
	--save_interval_secs=600 \
	--weight_decay=0.0005 \
	--optimizer=adam \
	--learning_rate=0.001 \
	--batch_size=2 \
    	--gpu_data=/cpu:0 \
	--gpu_train=/cpu:0

2017/ 03/29

Overwrite all files, so make the training pipeline much clear.

1. Write the load_batch . This can be resued in any preproceesing jobs.
2. Rewrite the traning file, so make the pipeline more clear.

Problems to be solved:

1. The loss decreases slowly after 2000 iterations, find why?		
2. Prepare the other two datasets(transform into tf.record)
3. Evaluation part scripts.

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TextBoxes re-implement using tensorflow

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  • Python 70.7%
  • Jupyter Notebook 29.3%