guidesignresearch/guigan

A GAN-based GUI generation method

guigan's Issues

I encountered a problem while running the GUI_test.py, It seems that there doesn't exist an file named app_details.csv

Traceback (most recent call last):
File "/home/zhengwanjie/GAN_models/GUIGAN/code/GUIGAN_test.py", line 79, in
appsl, appsd = get_s_app(file_csv, st_dir)
File "/home/zhengwanjie/GAN_models/GUIGAN/code/./StyleEmbedding/load_data.py", line 93, in get_s_app
cv_file = csv.reader(open(file_csv,'r', encoding='UTF-8'))
FileNotFoundError: [Errno 2] No such file or directory: 'app_details.csv'

Link to Pre-trained model

Hi this repository is missing a link to the pre-trained model. Thanks

from model import siamese_net

the model is not exist in the whole project,so as siamese_net.
can you please tell me where the model and siamese_net is

There are undeclared variable in this method

Hi,

There are undeclared variables in this method. For ex:, the variable im and ui_dir is not defined in the early part of the method. Can you please let us know what this directory refers to?

GUIGAN/code/GetSubtree/save_subtree_info.py

Line 133 in 1ed4ae1

def save_subtree_img(_list,dst_dir):

How to calculate the baseline: FID and 1-NNA?

Using the pretrained model gives error

Hi, i'm trying to test with the pretrained model mentioned here #2

However running the GUIGAN_test.py gives me an error. Not sure what i'm doing wrong.

Error:

Namespace(cuda=0)
opt.cuda is not None
Namespace(cuda=0)
opt.cuda is not None

c_cats: ['Books & Reference']

loading data

Loading time for the SubTrees in training data：0.904341 s

Time for loading training embedding：0.905231 s
NEGATIVE_FILE: results/Books & Reference

subtrees_count: 2183
train_templates_count: 1167

Time for getting Repository：0.022107 s

Time for loading real world data：0.345559 s

GENERATED_NUM,real_data_id1 303

VOCAB_SIZE: 2194
real_vocab_size: 2183

Time for unifying x_info and x_emb：0.098170 s

Traceback (most recent call last):
File "GUIGAN_test.py", line 237, in
reduced_data1 = PCA(n_components=2).fit_transform(x_emb)
File "/usr/local/lib/python3.7/dist-packages/sklearn/decomposition/_pca.py", line 369, in fit_transform
U, S, V = self._fit(X)
File "/usr/local/lib/python3.7/dist-packages/sklearn/decomposition/_pca.py", line 391, in _fit
copy=self.copy)
File "/usr/local/lib/python3.7/dist-packages/sklearn/utils/validation.py", line 556, in check_array
"if it contains a single sample.".format(array))
ValueError: Expected 2D array, got 1D array instead:
array=[].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.