Newer
Older
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
# Adding New Data Transforms
1. Write a new pipeline in any file, e.g., `my_pipeline.py`. It takes a dict as input and return a dict.
```python
from mmseg.datasets import TRANSFORMS
@TRANSFORMS.register_module()
class MyTransform:
def __call__(self, results):
results['dummy'] = True
return results
```
2. Import the new class.
```python
from .my_pipeline import MyTransform
```
3. Use it in config files.
```python
crop_size = (512, 1024)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize',
scale=(2048, 1024),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='PhotoMetricDistortion'),
dict(type='MyTransform'),
dict(type='PackSegInputs'),
]
```