Change directory structure

data/__init__.py

@@ -0,0 +1,6 @@
+"""Defines data structure and related functions."""
+from collections import namedtuple
+
+
+MarkingPoint = namedtuple('MarkingPoint', ['x', 'y', 'direction', 'shape'])
+Slot = namedtuple('Slot', ['x1', 'y1', 'x2', 'y2'])

data/data_process.py

@@ -1,11 +1,8 @@
-from collections import namedtuple
+"""Defines data structure and related function to process these data."""
 import math
 import torch
 import config
-
-
-MarkingPoint = namedtuple('MarkingPoint', ['x', 'y', 'direction', 'shape'])
-Slot = namedtuple('Slot', ['x1', 'y1', 'x2', 'y2'])
+from . import MarkingPoint
 
 
 def generate_objective(marking_points_batch, device):

data/dataset.py

@@ -1,11 +1,11 @@
-# -*- coding: utf-8 -*-
+"""Defines the parking slot dataset for directional marking point detection."""
 import json
 import os
 import os.path
 import cv2 as cv
 from torch.utils.data import Dataset
 from torchvision import transforms
-from data import MarkingPoint
+from . import MarkingPoint
 
 
 class ParkingSlotDataset(Dataset):

evaluate.py

@@ -1,15 +1,12 @@
 """Evaluate directional marking point detector."""
 import torch
 from torch.utils.data import DataLoader
-from precision_recall import calc_average_precision
-from precision_recall import calc_precision_recall
 import config
-from data import generate_objective
-from data import get_predicted_points
-from data import match_marking_points
-from dataset import ParkingSlotDataset
-from detector import DirectionalPointDetector
-from log import Logger
+from data.data_process import generate_objective, get_predicted_points, match_marking_points
+from data.dataset import ParkingSlotDataset
+from model.detector import DirectionalPointDetector
+from util.log import Logger
+from util.precision_recall import calc_average_precision, calc_precision_recall
 
 
 def evaluate_detector(args):

inference.py

@@ -5,9 +5,9 @@ import numpy as np
 import torch
 from torchvision.transforms import ToTensor
 import config
-from data import get_predicted_points
-from detector import DirectionalPointDetector
-from utils import Timer
+from data.data_process import get_predicted_points
+from model.detector import DirectionalPointDetector
+from util import Timer
 
 
 def plot_marking_points(image, marking_points):

model/detector.py

@@ -1,7 +1,7 @@
-# -*- coding: utf-8 -*-
+"""Defines the detector network structure."""
 import torch
 from torch import nn
-from network import define_halve_unit, define_detector_block
+from model.network import define_halve_unit, define_detector_block
 
 
 class YetAnotherDarknet(nn.modules.Module):

model/network.py

@@ -1,4 +1,4 @@
-"""Common network struture unit definition."""
+"""Universal network struture unit definition."""
 from torch import nn
 
 

train.py

@@ -3,12 +3,11 @@ import random
 import torch
 from torch.utils.data import DataLoader
 import config
-from data import get_predicted_points
-from data import generate_objective
-from dataset import ParkingSlotDataset
-from detector import DirectionalPointDetector
-from log import Logger
-from utils import tensor2im
+from data.data_process import get_predicted_points, generate_objective
+from data.dataset import ParkingSlotDataset
+from model.detector import DirectionalPointDetector
+from util.log import Logger
+from util import tensor2im
 
 
 def plot_prediction(logger, image, marking_points, prediction):

util/precision_recall.py

@@ -1,4 +1,4 @@
-"""Universal procedure of calculating average precision defined in VOC"""
+"""Universal procedure of calculating precision and recall."""
 
 
 def match_gt_with_preds(ground_truth, predictions, match_labels):