cd src
python convert_single_image.py --png_path ../examples/drawn_example1.png \
--output_folder ./generated_html \
--model_json_file ../bin/model_json.json \
--model_weights_file ../bin/weights.h5
一般用法
使用权重将单个图像转换为HTML代码:
cd src
python convert_single_image.py --png_path {path/to/img.png} \
--output_folder {folder/to/output/html} \
--model_json_file {path/to/model/json_file.json} \
--model_weights_file {path/to/model/weights.h5}
将文件夹中的一批图像转换为HTML:
cd src
python convert_batch_of_images.py --pngs_path {path / to / folder / with / pngs} \
--output_folder {folder / to / output / html} \
--model_json_file {path / to / model / json_file.json} \
- -model_weights_file {path / to / model / weights.h5}
训练模型:
cd src
# training from scratch
# adds Keras ImageDataGenerator augmentation for training images
python train.py --data_input_path {path/to/folder/with/pngs/guis} \
--validation_split 0.2 \
--epochs 10 \
--model_output_path {path/to/output/model}
--augment_training_data 1
# training starting with pretrained model
python train.py --data_input_path {path/to/folder/with/pngs/guis} \
--validation_split 0.2 \
--epochs 10 \
--model_output_path {path/to/output/model} \
--model_json_file ../bin/model_json.json \
--model_weights_file ../bin/pretrained_weights.h5 \
--augment_training_data 1
使用BLEU分数评估生成的预测
cd src
# evaluate single GUI prediction
python evaluate_single_gui.py --original_gui_filepath {path/to/original/gui/file} \
--predicted_gui_filepath {path/to/predicted/gui/file}
# training starting with pretrained model
python evaluate_batch_guis.py --original_guis_filepath {path/to/folder/with/original/guis} \
--predicted_guis_filepath {path/to/folder/with/predicted/guis}