Hotfix: fix wrong domain in tiling rotated detection (#3141)

* domain=rotated_detection in tile_pipeline

* update tile pipeline

src/otx/algorithms/detection/configs/rotated_detection/efficientnetb2b_maskrcnn/tile_pipeline.py

@@ -1,7 +1,95 @@
-"""Tiling Pipeline of EfficientNetB2B model for Instance-Seg Task."""
+"""Tiling Pipeline of EfficientNetB2B model."""
 
 # Copyright (C) 2023 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
+# pylint: disable=invalid-name
 
-_base_ = ["../../base/data/tiling/efficientnet_iseg_tile_pipeline.py"]
+img_size = (512, 512)
+
+tile_cfg = dict(
+    tile_size=400, min_area_ratio=0.9, overlap_ratio=0.2, iou_threshold=0.45, max_per_img=1500, filter_empty_gt=True
+)
+
+img_norm_cfg = dict(mean=(103.53, 116.28, 123.675), std=(1.0, 1.0, 1.0), to_rgb=True)
+
+train_pipeline = [
+    dict(type="Resize", img_scale=img_size, keep_ratio=False),
+    dict(type="RandomFlip", flip_ratio=0.5),
+    dict(type="Normalize", **img_norm_cfg),
+    dict(type="Pad", size_divisor=32),
+    dict(type="DefaultFormatBundle"),
+    dict(
+        type="Collect",
+        keys=["img", "gt_bboxes", "gt_labels", "gt_masks"],
+        meta_keys=[
+            "filename",
+            "ori_filename",
+            "ori_shape",
+            "img_shape",
+            "pad_shape",
+            "scale_factor",
+            "flip",
+            "flip_direction",
+            "img_norm_cfg",
+        ],
+    ),
+]
+
+test_pipeline = [
+    dict(
+        type="MultiScaleFlipAug",
+        img_scale=img_size,
+        flip=False,
+        transforms=[
+            dict(type="Resize", keep_ratio=False),
+            dict(type="RandomFlip"),
+            dict(type="Normalize", **img_norm_cfg),
+            dict(type="Pad", size_divisor=32),
+            dict(type="ImageToTensor", keys=["img"]),
+            dict(type="Collect", keys=["img"]),
+        ],
+    )
+]
+
+__dataset_type = "OTXDetDataset"
+
+train_dataset = dict(
+    type="ImageTilingDataset",
+    dataset=dict(
+        type=__dataset_type,
+        pipeline=[
+            dict(type="LoadImageFromOTXDataset", enable_memcache=True),
+            dict(type="LoadAnnotationFromOTXDataset", domain="rotated_detection", with_bbox=True, with_mask=True),
+        ],
+    ),
+    pipeline=train_pipeline,
+    **tile_cfg
+)
+
+val_dataset = dict(
+    type="ImageTilingDataset",
+    dataset=dict(
+        type=__dataset_type,
+        pipeline=[
+            dict(type="LoadImageFromOTXDataset", enable_memcache=True),
+            dict(type="LoadAnnotationFromOTXDataset", domain="rotated_detection", with_bbox=True, with_mask=True),
+        ],
+    ),
+    pipeline=test_pipeline,
+    **tile_cfg
+)
+
+test_dataset = dict(
+    type="ImageTilingDataset",
+    dataset=dict(
+        type=__dataset_type,
+        test_mode=True,
+        pipeline=[dict(type="LoadImageFromOTXDataset")],
+    ),
+    pipeline=test_pipeline,
+    **tile_cfg
+)
+
+
+data = dict(train=train_dataset, val=val_dataset, test=test_dataset)

src/otx/algorithms/detection/configs/rotated_detection/resnet50_maskrcnn/tile_pipeline.py

@@ -1,7 +1,95 @@
-"""Tiling Pipeline of Resnet model for Instance-Seg Task."""
+"""Tiling Pipeline for Rotated-Detection Task."""
 
-# Copyright (C) 2023 Intel Corporation
+# Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
+# pylint: disable=invalid-name
 
-_base_ = ["../../base/data/tiling/base_iseg_tile_pipeline.py"]
+img_size = (512, 512)
+
+tile_cfg = dict(
+    tile_size=400, min_area_ratio=0.9, overlap_ratio=0.2, iou_threshold=0.45, max_per_img=1500, filter_empty_gt=True
+)
+
+img_norm_cfg = dict(mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+
+train_pipeline = [
+    dict(type="Resize", img_scale=img_size, keep_ratio=True),
+    dict(type="RandomFlip", flip_ratio=0.5),
+    dict(type="Normalize", **img_norm_cfg),
+    dict(type="Pad", size=img_size),
+    dict(type="DefaultFormatBundle"),
+    dict(
+        type="Collect",
+        keys=["img", "gt_bboxes", "gt_labels", "gt_masks"],
+        meta_keys=[
+            "filename",
+            "ori_filename",
+            "ori_shape",
+            "img_shape",
+            "pad_shape",
+            "scale_factor",
+            "flip",
+            "flip_direction",
+            "img_norm_cfg",
+        ],
+    ),
+]
+
+test_pipeline = [
+    dict(
+        type="MultiScaleFlipAug",
+        img_scale=img_size,
+        flip=False,
+        transforms=[
+            dict(type="Resize", keep_ratio=True),
+            dict(type="RandomFlip"),
+            dict(type="Normalize", **img_norm_cfg),
+            dict(type="Pad", size=img_size),
+            dict(type="ImageToTensor", keys=["img"]),
+            dict(type="Collect", keys=["img"]),
+        ],
+    )
+]
+
+__dataset_type = "OTXDetDataset"
+
+train_dataset = dict(
+    type="ImageTilingDataset",
+    dataset=dict(
+        type=__dataset_type,
+        pipeline=[
+            dict(type="LoadImageFromOTXDataset", enable_memcache=True),
+            dict(type="LoadAnnotationFromOTXDataset", domain="rotated_detection", with_bbox=True, with_mask=True),
+        ],
+    ),
+    pipeline=train_pipeline,
+    **tile_cfg
+)
+
+val_dataset = dict(
+    type="ImageTilingDataset",
+    dataset=dict(
+        type=__dataset_type,
+        pipeline=[
+            dict(type="LoadImageFromOTXDataset", enable_memcache=True),
+            dict(type="LoadAnnotationFromOTXDataset", domain="rotated_detection", with_bbox=True, with_mask=True),
+        ],
+    ),
+    pipeline=test_pipeline,
+    **tile_cfg
+)
+
+test_dataset = dict(
+    type="ImageTilingDataset",
+    dataset=dict(
+        type=__dataset_type,
+        test_mode=True,
+        pipeline=[dict(type="LoadImageFromOTXDataset")],
+    ),
+    pipeline=test_pipeline,
+    **tile_cfg
+)
+
+
+data = dict(train=train_dataset, val=val_dataset, test=test_dataset)