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 :
