Datasets:
File size: 2,007 Bytes
5e1ef3a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | import os
import json
from tqdm import tqdm
import re
def build_final_metadata():
base_data_dir = "data"
output_jsonl = os.path.join(base_data_dir, "metadata.jsonl")
entries = []
for var_idx in range(1, 7):
var_dir = os.path.join(base_data_dir, f"Variation_{var_idx}")
if not os.path.exists(var_dir): continue
for lvl_idx in range(1, 4):
lvl_dir = os.path.join(var_dir, f"Color_Level_{lvl_idx}")
if not os.path.exists(lvl_dir): continue
#print(f"Processing Variation {var_idx}, Color_Level {lvl_idx}...")
files = [f for f in os.listdir(lvl_dir) if f.endswith(".png")]
# Use lambda to extract the numerical parts and sort them.
files.sort(key=lambda f: int(re.search(r'\d+', f).group()))
for f in tqdm(files):
id_name = f.replace(".png", "")
txt_file = os.path.join(lvl_dir, f"{id_name}.txt")
# Read the corresponding txt content as a prompt
prompt_content = ""
if os.path.exists(txt_file):
with open(txt_file, "r", encoding="utf-8") as tf:
prompt_content = tf.read().strip()
rel_path = f"Variation_{var_idx}/Color_Level_{lvl_idx}/{f}"
entries.append({
"file_name": rel_path,
"text": prompt_content,
"variation": var_idx,
"color_level": lvl_idx,
"id": id_name,
"split": "test"
})
with open(output_jsonl, "w", encoding="utf-8") as out:
for entry in entries:
out.write(json.dumps(entry, ensure_ascii=False) + "\n")
print(f"total {len(entries)} entries in {output_jsonl}")
if __name__ == "__main__":
build_final_metadata() |