feat: add generation statistics calc script
Browse files- font_ds_stat.py +62 -0
font_ds_stat.py
ADDED
|
@@ -0,0 +1,62 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import sys
|
| 2 |
+
import traceback
|
| 3 |
+
import pickle
|
| 4 |
+
import os
|
| 5 |
+
import concurrent.futures
|
| 6 |
+
from tqdm import tqdm
|
| 7 |
+
from font_dataset.font import load_fonts
|
| 8 |
+
from font_dataset.layout import generate_font_image
|
| 9 |
+
from font_dataset.text import CorpusGeneratorManager
|
| 10 |
+
from font_dataset.background import background_image_generator
|
| 11 |
+
|
| 12 |
+
|
| 13 |
+
cjk_ratio = 3
|
| 14 |
+
|
| 15 |
+
train_cnt = 100
|
| 16 |
+
val_cnt = 10
|
| 17 |
+
test_cnt = 30
|
| 18 |
+
|
| 19 |
+
train_cnt_cjk = int(train_cnt * cjk_ratio)
|
| 20 |
+
val_cnt_cjk = int(val_cnt * cjk_ratio)
|
| 21 |
+
test_cnt_cjk = int(test_cnt * cjk_ratio)
|
| 22 |
+
|
| 23 |
+
dataset_path = "./dataset/font_img"
|
| 24 |
+
os.makedirs(dataset_path, exist_ok=True)
|
| 25 |
+
|
| 26 |
+
fonts = load_fonts()
|
| 27 |
+
|
| 28 |
+
|
| 29 |
+
cnt = 0
|
| 30 |
+
|
| 31 |
+
for font in fonts:
|
| 32 |
+
if font.language == "CJK":
|
| 33 |
+
cnt += cjk_ratio
|
| 34 |
+
else:
|
| 35 |
+
cnt += 1
|
| 36 |
+
|
| 37 |
+
|
| 38 |
+
print("Total training images:", train_cnt * cnt)
|
| 39 |
+
print("Total validation images:", val_cnt * cnt)
|
| 40 |
+
print("Total testing images:", test_cnt * cnt)
|
| 41 |
+
|
| 42 |
+
if os.path.exists(os.path.join(dataset_path, "train")):
|
| 43 |
+
num_file_train = len(os.listdir(os.path.join(dataset_path, "train")))
|
| 44 |
+
else:
|
| 45 |
+
num_file_train = 0
|
| 46 |
+
|
| 47 |
+
if os.path.exists(os.path.join(dataset_path, "val")):
|
| 48 |
+
num_file_val = len(os.listdir(os.path.join(dataset_path, "val")))
|
| 49 |
+
else:
|
| 50 |
+
num_file_val = 0
|
| 51 |
+
|
| 52 |
+
if os.path.exists(os.path.join(dataset_path, "test")):
|
| 53 |
+
num_file_test = len(os.listdir(os.path.join(dataset_path, "test")))
|
| 54 |
+
else:
|
| 55 |
+
num_file_test = 0
|
| 56 |
+
|
| 57 |
+
print("Total files generated:", num_file_train + num_file_val + num_file_test)
|
| 58 |
+
print("Total files target:", (train_cnt + val_cnt + test_cnt) * cnt * 2)
|
| 59 |
+
|
| 60 |
+
print(
|
| 61 |
+
f"{(num_file_train + num_file_val + num_file_test) / ((train_cnt + val_cnt + test_cnt) * cnt * 2) * 100:.2f}% completed"
|
| 62 |
+
)
|