MerlenMaven commited on
Commit
74da4ed
·
verified ·
1 Parent(s): 610438b

Delete fer2013.py

Browse files
Files changed (1) hide show
  1. fer2013.py +0 -75
fer2013.py DELETED
@@ -1,75 +0,0 @@
1
- import csv
2
- import pathlib
3
- from typing import Any, Callable, Optional, Tuple
4
-
5
- import torch
6
- from PIL import Image
7
-
8
- from .utils import check_integrity, verify_str_arg
9
- from .vision import VisionDataset
10
-
11
-
12
- class FER2013(VisionDataset):
13
- """`FER2013
14
- <https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge>`_ Dataset.
15
-
16
- Args:
17
- root (string): Root directory of dataset where directory
18
- ``root/fer2013`` exists.
19
- split (string, optional): The dataset split, supports ``"train"`` (default), or ``"test"``.
20
- transform (callable, optional): A function/transform that takes in an PIL image and returns a transformed
21
- version. E.g, ``transforms.RandomCrop``
22
- target_transform (callable, optional): A function/transform that takes in the target and transforms it.
23
- """
24
-
25
- _RESOURCES = {
26
- "train": ("train.csv", "3f0dfb3d3fd99c811a1299cb947e3131"),
27
- "test": ("test.csv", "b02c2298636a634e8c2faabbf3ea9a23"),
28
- }
29
-
30
- def __init__(
31
- self,
32
- root: str,
33
- split: str = "train",
34
- transform: Optional[Callable] = None,
35
- target_transform: Optional[Callable] = None,
36
- ) -> None:
37
- self._split = verify_str_arg(split, "split", self._RESOURCES.keys())
38
- super().__init__(root, transform=transform, target_transform=target_transform)
39
-
40
- base_folder = pathlib.Path(self.root) / "fer2013"
41
- file_name, md5 = self._RESOURCES[self._split]
42
- data_file = base_folder / file_name
43
- if not check_integrity(str(data_file), md5=md5):
44
- raise RuntimeError(
45
- f"{file_name} not found in {base_folder} or corrupted. "
46
- f"You can download it from "
47
- f"https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge"
48
- )
49
-
50
- with open(data_file, "r", newline="") as file:
51
- self._samples = [
52
- (
53
- torch.tensor([int(idx) for idx in row["pixels"].split()], dtype=torch.uint8).reshape(48, 48),
54
- int(row["emotion"]) if "emotion" in row else None,
55
- )
56
- for row in csv.DictReader(file)
57
- ]
58
-
59
- def __len__(self) -> int:
60
- return len(self._samples)
61
-
62
- def __getitem__(self, idx: int) -> Tuple[Any, Any]:
63
- image_tensor, target = self._samples[idx]
64
- image = Image.fromarray(image_tensor.numpy())
65
-
66
- if self.transform is not None:
67
- image = self.transform(image)
68
-
69
- if self.target_transform is not None:
70
- target = self.target_transform(target)
71
-
72
- return image, target
73
-
74
- def extra_repr(self) -> str:
75
- return f"split={self._split}"