init

finetune/mmseg/apis/utils.py

@@ -0,0 +1,41 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+from collections import defaultdict
+from typing import Sequence, Union
+
+import numpy as np
+from mmengine.dataset import Compose
+from mmengine.model import BaseModel
+
+ImageType = Union[str, np.ndarray, Sequence[str], Sequence[np.ndarray]]
+
+
+def _preprare_data(imgs: ImageType, model: BaseModel):
+
+    cfg = model.cfg
+    for t in cfg.test_pipeline:
+        if t.get('type') == 'LoadAnnotations':
+            cfg.test_pipeline.remove(t)
+
+    is_batch = True
+    if not isinstance(imgs, (list, tuple)):
+        imgs = [imgs]
+        is_batch = False
+
+    if isinstance(imgs[0], np.ndarray):
+        cfg.test_pipeline[0]['type'] = 'LoadImageFromNDArray'
+
+    # TODO: Consider using the singleton pattern to avoid building
+    # a pipeline for each inference
+    pipeline = Compose(cfg.test_pipeline)
+
+    data = defaultdict(list)
+    for img in imgs:
+        if isinstance(img, np.ndarray):
+            data_ = dict(img=img)
+        else:
+            data_ = dict(img_path=img)
+        data_ = pipeline(data_)
+        data['inputs'].append(data_['inputs'])
+        data['data_samples'].append(data_['data_samples'])
+
+    return data, is_batch