worlabel/ai/app/utils/file_utils.py
2024-09-18 16:27:14 +09:00

176 lines
5.5 KiB
Python

import os
import shutil
import yaml
from PIL import Image
from schemas.train_request import TrainDataInfo
def get_dataset_root_path(project_id):
"""데이터셋 루트 절대 경로 반환"""
return os.path.join(os.getcwd(), 'datasets', 'train')
def make_dir(path:str, init: bool):
"""
path : 디렉토리 경로
init : 폴더를 초기화 할지 여부
"""
if (os.path.exists(path) and init):
shutil.rmtree(path)
os.makedirs(path, exist_ok=True)
def make_yml(path:str):
data = {
"train": f"{path}/train",
"val": f"{path}/val",
"nc": 80,
"names":
{
0: "person",
1: "bicycle",
2: "car",
3: "motorcycle",
4: "airplane",
5: "bus",
6: "train",
7: "truck",
8: "boat",
9: "traffic light",
10: "fire hydrant",
11: "stop sign",
12: "parking meter",
13: "bench",
14: "bird",
15: "cat",
16: "dog",
17: "horse",
18: "sheep",
19: "cow",
20: "elephant",
21: "bear",
22: "zebra",
23: "giraffe",
24: "backpack",
25: "umbrella",
26: "handbag",
27: "tie",
28: "suitcase",
29: "frisbee",
30: "skis",
31: "snowboard",
32: "sports ball",
33: "kite",
34: "baseball bat",
35: "baseball glove",
36: "skateboard",
37: "surfboard",
38: "tennis racket",
39: "bottle",
40: "wine glass",
41: "cup",
42: "fork",
43: "knife",
44: "spoon",
45: "bowl",
46: "banana",
47: "apple",
48: "sandwich",
49: "orange",
50: "broccoli",
51: "carrot",
52: "hot dog",
53: "pizza",
54: "donut",
55: "cake",
56: "chair",
57: "couch",
58: "potted plant",
59: "bed",
60: "dining table",
61: "toilet",
62: "tv",
63: "laptop",
64: "mouse",
65: "remote",
66: "keyboard",
67: "cell phone",
68: "microwave",
69: "oven",
70: "toaster",
71: "sink",
72: "refrigerator",
73: "book",
74: "clock",
75: "vase",
76: "scissors",
77: "teddy bear",
78: "hair drier",
79: "toothbrush"
}
}
with open(os.path.join(path, "dataset.yaml"), 'w') as f:
yaml.dump(data, f)
def process_directories(dataset_root_path:str):
"""학습을 위한 디렉토리 생성"""
make_dir(dataset_root_path, init=False)
make_dir(os.path.join(dataset_root_path, "train"), init=True)
make_dir(os.path.join(dataset_root_path, "val"), init=True)
if os.path.exists(os.path.join(dataset_root_path, "result")):
shutil.rmtree(os.path.join(dataset_root_path, "result"))
make_yml(dataset_root_path)
def process_image_and_label(data:TrainDataInfo, dataset_root_path:str, child_path:str):
"""이미지 저장 및 레이블 파일 생성"""
# 이미지 저장
img = Image.open(data.image_url)
# 파일명에서 확장자를 제거하여 img_title과 img_ext 생성
img_title, img_ext = os.path.splitext(os.path.basename(data.image_url))
# 이미지 파일 저장 (확장자를 그대로 사용)
img.save(os.path.join(dataset_root_path, child_path, img_title + img_ext))
# 레이블 -> 학습용 레이블 데이터 파싱(detection)
label = data.label
with open(os.path.join(dataset_root_path, child_path, f"{img_title}.txt"), "w") as train_label_txt:
for shape in label.shapes:
train_label = []
x1 = shape.points[0][0]
y1 = shape.points[0][1]
x2 = shape.points[1][0]
y2 = shape.points[1][1]
train_label.append(str(shape.group_id)) # label Id
train_label.append(str((x1 + x2) / 2 / label.imageWidth)) # 중심 x 좌표
train_label.append(str((y1 + y2) / 2 / label.imageHeight)) # 중심 y 좌표
train_label.append(str((x2 - x1) / label.imageWidth)) # 너비
train_label.append(str((y2 - y1) / label.imageHeight )) # 높이
train_label_txt.write(" ".join(train_label)+"\n")
def join_path(path, *paths):
"""os.path.join()과 같은 기능, os import 하기 싫어서 만듦"""
return os.path.join(path, *paths)
def get_model_paths(project_id:int):
path = os.path.join("resources","projects",str(project_id), "models")
if not os.path.exists(path):
raise FileNotFoundError()
files = os.listdir(path)
return [os.path.join(path, file) for file in files if file.endswith(".pt")]
def delete_file(path):
if not os.path.exists(path):
raise FileNotFoundError()
os.remove(path)
def save_file(path, file):
# 경로에서 디렉토리 부분만 추출 (파일명을 제외한 경로)
dir_path = os.path.dirname(path)
os.makedirs(dir_path, exist_ok=True)
with open(path, "wb") as buffer:
shutil.copyfileobj(file.file, buffer)
def get_file_name(path):
if not os.path.exists(path):
raise FileNotFoundError()
return os.path.basename(path)