def main():
for series_name in config["folders"]:
charactor_dirs = fs.list_dirs(record_dir)
pbar = tqdm(charactor_dirs)
for charactor_name in pbar:
print("CHARACTOR -> ", charactor_name)
try:
if len(
config["rejected_charactors"]
) > 0 and charactor_name in config["rejected_charactors"]:
pbar.update(1)
continue
if len(
config["available_charactors"]
) > 0 and charactor_name not in config["available_charactors"]:
pbar.update(1)
continue
chara_crop_dir = prepare(charactor_name, series_name)
chara_record_dir = os.path.join(record_dir, charactor_name,
series_name)
record_pathes = fs.list_entries(chara_record_dir)
joblib.Parallel(n_jobs=JOB_NUM)([
joblib.delayed(process)(
src_record_path=record_path,
chara_crop_dir=chara_crop_dir,
) for record_path in record_pathes
])
except Exception as e:
print("main ERROR: ")
print(traceback.format_exc())
pbar.update(1)
def main():
class_mapping = fs.load_json(class_mapping_file_path)
for series_name in tqdm(CLIP_TARGET_FOLDER_NAMES):
movie_pathes = fs.list_entries(os.path.join(movie_dir, series_name))
joblib.Parallel(n_jobs=JOB_NUM)([
joblib.delayed(process)(movie_path=movie_path,
output_dir=clip_output_dir,
class_mapping=class_mapping)
for movie_path in movie_pathes
])
def main():
class_mapping = fs.load_json(class_mapping_file_path)
for series_name in config["folders"]:
record_dir_format = os.path.join(resource_dir, "records", "{}", series_name)
movies = fs.list_entries(os.path.join(movie_dir, series_name))
params = [(movie, record_dir_format) for movie in movies]
joblib.Parallel(n_jobs=JOB_NUM)([joblib.delayed(process)(
movie_path=param[0],
record_dir_format=param[1],
class_mapping=class_mapping
) for param in params])
def prepare(dataset_dir_path, input_data_dir_path):
if os.path.exists(input_data_dir_path):
return
os.makedirs(input_data_dir_path, exist_ok=True)
classification_dirs = fs.list_entries(dataset_dir_path)
for classification_dir in classification_dirs:
dirname = os.path.basename(classification_dir)
if dirname.startswith("_"):
continue
src = classification_dir
dst = os.path.join(input_data_dir_path, dirname)
shutil.copytree(src, dst)
def make_train_data(classes):
print(classes)
ret = {}
for c in classes:
ret[c["name"]] = []
img_file_pathes = fs.list_entries(c["path"])
class_dir_path = os.path.join(train_data_dir_path, c["name"])
os.makedirs(class_dir_path, exist_ok=True)
for filepath in img_file_pathes:
try:
image = Image()
image.load_image_from_filepath(filepath)
image.transform_image_for_predict_with(config["image_size_px"])
dst_filepath = os.path.join(class_dir_path, fs.get_filename(filepath))
image.write_to(dst_filepath)
print(dst_filepath)
ret[c["name"]].append(dst_filepath)
except Exception as e:
print(e)
return ret