This is a tensorflow implimentation of Object Contour Detection with a Fully Convolutional Encoder-Decoder Network (https://arxiv.org/pdf/1603.04530.pdf) .
REQUIREMENTS :
pip install requirements.txt
Label Preparation :
To prepare the labels for contour detection from PASCAL Dataset , run create_lables.py and edit the file to add the path of the labels and new labels to be generated . Use this path for labels during training.
TRAINING :
python train.py \
--max_to_keep=50 \
--Epochs=100 \
--momentum=0.9 \
--learning_rate=.0000001 \
--train_crop_size=480 \
--clip_by_value=1.0 \
--train_text = ${path to text file} \
--log_dir = ${path to where logs will be saved} \
--tf_initial_checkpoint=${PATH_TO_CHECKPOINT} \
--label_dir = ${path to label directory} \
--image_dir = ${path to image directory}
EVALUATION :
python eval.py \
--checkpoint=${path to checkpoint to be evaluated} \
--save_preds=${path to folder where predictions will be saved} \
--image_dir = ${path to image directory} \
--eval_crop_size=480 \
--eval_text = ${path to eval text file}
Results :
