Enable DINO to OTX - Step 2. Upgrade Deformable DETR to DINO (#2266)

* Add DINO

* Modify docstrings

* Add mmengine to detection requirements

* Add unit tests

* Add intg test

* Update CHANGELOG.md

* Change description of config files for DINO

* Modify unit tests

* Reflect reviews

* Reflect Reviews

* Update unit tests

Author: jaegukhyun

CHANGELOG.md

@@ -10,6 +10,7 @@ All notable changes to this project will be documented in this file.
 - Add custom max iou assigner to prevent CPU OOM when large annotations are used (<https://github.com/openvinotoolkit/training_extensions/pull/2228>)
 - Auto train type detection for Semi-SL, Self-SL and Incremental: "--train-type" now is optional (https://github.com/openvinotoolkit/training_extensions/pull/2195)
 - Add new object detector Deformable DETR (<https://github.com/openvinotoolkit/training_extensions/pull/2249>)
+- Add new object detecotr DINO(<https://github.com/openvinotoolkit/training_extensions/pull/2266>)
 
 ### Enhancements
 

otx/algorithms/detection/adapters/mmdet/models/__init__.py

@@ -3,6 +3,6 @@
 # SPDX-License-Identifier: Apache-2.0
 #
 
-from . import assigners, backbones, dense_heads, detectors, heads, losses, necks, roi_heads
+from . import assigners, backbones, dense_heads, detectors, heads, layers, losses, necks, roi_heads
 
-__all__ = ["assigners", "backbones", "dense_heads", "detectors", "heads", "losses", "necks", "roi_heads"]
+__all__ = ["assigners", "backbones", "dense_heads", "detectors", "heads", "layers", "losses", "necks", "roi_heads"]

otx/algorithms/detection/adapters/mmdet/models/detectors/__init__.py

@@ -5,6 +5,7 @@
 
 from .custom_atss_detector import CustomATSS
 from .custom_deformable_detr_detector import CustomDeformableDETR
+from .custom_dino_detector import CustomDINO
 from .custom_maskrcnn_detector import CustomMaskRCNN
 from .custom_maskrcnn_tile_optimized import CustomMaskRCNNTileOptimized
 from .custom_single_stage_detector import CustomSingleStageDetector
@@ -18,6 +19,7 @@
 __all__ = [
     "CustomATSS",
     "CustomDeformableDETR",
+    "CustomDINO",
     "CustomMaskRCNN",
     "CustomSingleStageDetector",
     "CustomTwoStageDetector",

otx/algorithms/detection/adapters/mmdet/models/detectors/custom_dino_detector.py

@@ -0,0 +1,89 @@
+"""OTX DINO Class for mmdetection detectors."""
+
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+#
+
+from mmdet.models.builder import DETECTORS
+
+from otx.algorithms.common.adapters.mmcv.hooks.recording_forward_hook import (
+    ActivationMapHook,
+    FeatureVectorHook,
+)
+from otx.algorithms.common.adapters.mmdeploy.utils import is_mmdeploy_enabled
+from otx.algorithms.common.utils.logger import get_logger
+from otx.algorithms.detection.adapters.mmdet.models.detectors import CustomDeformableDETR
+
+logger = get_logger()
+
+
+@DETECTORS.register_module()
+class CustomDINO(CustomDeformableDETR):
+    """Custom DINO detector."""
+
+    def __init__(self, *args, task_adapt=None, **kwargs):
+        super().__init__(*args, task_adapt=task_adapt, **kwargs)
+        self._register_load_state_dict_pre_hook(
+            self.load_state_dict_pre_hook,
+        )
+
+    @staticmethod
+    def load_state_dict_pre_hook(ckpt_dict, *args, **kwargs):
+        """Modify mmdet3.x version's weights before weight loading."""
+
+        if list(ckpt_dict.keys())[0] == "level_embed":
+            logger.info("----------------- CustomDINO.load_state_dict_pre_hook() called")
+            # This ckpt_dict comes from mmdet3.x
+            ckpt_dict["bbox_head.transformer.level_embeds"] = ckpt_dict.pop("level_embed")
+            replaced_params = {}
+            for param in ckpt_dict:
+                new_param = None
+                if "encoder" in param or "decoder" in param:
+                    new_param = "bbox_head.transformer." + param
+                    new_param = new_param.replace("self_attn", "attentions.0")
+                    new_param = new_param.replace("cross_attn", "attentions.1")
+                    new_param = new_param.replace("ffn", "ffns.0")
+                elif param == "query_embedding.weight":
+                    new_param = "bbox_head." + param
+                elif param == "dn_query_generator.label_embedding.weight":
+                    new_param = "bbox_head.transformer." + param
+                elif "memory_trans" in param:
+                    new_param = "bbox_head.transformer." + param
+                    new_param = new_param.replace("memory_trans_fc", "enc_output")
+                    new_param = new_param.replace("memory_trans_norm", "enc_output_norm")
+                if new_param is not None:
+                    replaced_params[param] = new_param
+
+            for origin, new in replaced_params.items():
+                ckpt_dict[new] = ckpt_dict.pop(origin)
+
+
+if is_mmdeploy_enabled():
+    from mmdeploy.core import FUNCTION_REWRITER
+
+    @FUNCTION_REWRITER.register_rewriter(
+        "otx.algorithms.detection.adapters.mmdet.models.detectors.custom_dino_detector.CustomDINO.simple_test"
+    )
+    def custom_dino__simple_test(ctx, self, img, img_metas, **kwargs):
+        """Function for custom_dino__simple_test."""
+        height = int(img_metas[0]["img_shape"][0])
+        width = int(img_metas[0]["img_shape"][1])
+        img_metas[0]["batch_input_shape"] = (height, width)
+        img_metas[0]["img_shape"] = (height, width, 3)
+        feats = self.extract_feat(img)
+        gt_bboxes = [None] * len(feats)
+        gt_labels = [None] * len(feats)
+        hidden_states, references, enc_output_class, enc_output_coord, _ = self.bbox_head.forward_transformer(
+            feats, gt_bboxes, gt_labels, img_metas
+        )
+        cls_scores, bbox_preds = self.bbox_head(hidden_states, references)
+        bbox_results = self.bbox_head.get_bboxes(
+            cls_scores, bbox_preds, enc_output_class, enc_output_coord, img_metas=img_metas, **kwargs
+        )
+
+        if ctx.cfg["dump_features"]:
+            feature_vector = FeatureVectorHook.func(feats)
+            saliency_map = ActivationMapHook.func(cls_scores)
+            return (*bbox_results, feature_vector, saliency_map)
+
+        return bbox_results

otx/algorithms/detection/adapters/mmdet/models/heads/__init__.py

@@ -6,23 +6,27 @@
 from .cross_dataset_detector_head import CrossDatasetDetectorHead
 from .custom_anchor_generator import SSDAnchorGeneratorClustered
 from .custom_atss_head import CustomATSSHead, CustomATSSHeadTrackingLossDynamics
+from .custom_dino_head import CustomDINOHead
 from .custom_fcn_mask_head import CustomFCNMaskHead
 from .custom_retina_head import CustomRetinaHead
 from .custom_roi_head import CustomRoIHead
 from .custom_ssd_head import CustomSSDHead
 from .custom_vfnet_head import CustomVFNetHead
 from .custom_yolox_head import CustomYOLOXHead
+from .detr_head import DETRHeadExtension
 
 __all__ = [
     "CrossDatasetDetectorHead",
     "SSDAnchorGeneratorClustered",
     "CustomATSSHead",
+    "CustomDINOHead",
     "CustomFCNMaskHead",
     "CustomRetinaHead",
     "CustomSSDHead",
     "CustomRoIHead",
     "CustomVFNetHead",
     "CustomYOLOXHead",
+    "DETRHeadExtension",
     # Loss dynamics tracking
     "CustomATSSHeadTrackingLossDynamics",
 ]