add custom dataset example (#187)

Co-authored-by: Zhaoyang Zeng <zengzhaoyang@idea.edu.cn>

Author: zengzhaoyang

configs/common/data/custom.py

@@ -0,0 +1,76 @@
+import itertools
+
+from omegaconf import OmegaConf
+
+import detectron2.data.transforms as T
+from detectron2.config import LazyCall as L
+from detectron2.data import (
+    build_detection_test_loader,
+    build_detection_train_loader,
+    get_detection_dataset_dicts,
+)
+from detectron2.data.datasets import register_coco_instances
+from detectron2.evaluation import COCOEvaluator
+
+from detrex.data import DetrDatasetMapper
+
+dataloader = OmegaConf.create()
+
+register_coco_instances("my_dataset_train", {}, '/path/to/train.json', '/path/to/train/images')
+register_coco_instances("my_dataset_test", {}, '/path/to/test.json', '/path/to/test/images')
+
+dataloader.train = L(build_detection_train_loader)(
+    dataset=L(get_detection_dataset_dicts)(names="my_dataset_train"),
+    mapper=L(DetrDatasetMapper)(
+        augmentation=[
+            L(T.RandomFlip)(),
+            L(T.ResizeShortestEdge)(
+                short_edge_length=(480, 512, 544, 576, 608, 640, 672, 704, 736, 768, 800),
+                max_size=1333,
+                sample_style="choice",
+            ),
+        ],
+        augmentation_with_crop=[
+            L(T.RandomFlip)(),
+            L(T.ResizeShortestEdge)(
+                short_edge_length=(400, 500, 600),
+                sample_style="choice",
+            ),
+            L(T.RandomCrop)(
+                crop_type="absolute_range",
+                crop_size=(384, 600),
+            ),
+            L(T.ResizeShortestEdge)(
+                short_edge_length=(480, 512, 544, 576, 608, 640, 672, 704, 736, 768, 800),
+                max_size=1333,
+                sample_style="choice",
+            ),
+        ],
+        is_train=True,
+        mask_on=False,
+        img_format="RGB",
+    ),
+    total_batch_size=16,
+    num_workers=4,
+)
+
+dataloader.test = L(build_detection_test_loader)(
+    dataset=L(get_detection_dataset_dicts)(names="my_dataset_test", filter_empty=False),
+    mapper=L(DetrDatasetMapper)(
+        augmentation=[
+            L(T.ResizeShortestEdge)(
+                short_edge_length=800,
+                max_size=1333,
+            ),
+        ],
+        augmentation_with_crop=None,
+        is_train=False,
+        mask_on=False,
+        img_format="RGB",
+    ),
+    num_workers=4,
+)
+
+dataloader.evaluator = L(COCOEvaluator)(
+    dataset_name="${..test.dataset.names}",
+)