Limit the verision of mmdet to 3.0.0rc5 to fix CI

.circleci/test.yml

@@ -37,8 +37,6 @@ jobs:
         type: string
       torchvision:
         type: string
-      mmcv:
-        type: string
     docker:
       - image: cimg/python:<< parameters.python >>
     resource_class: large
@@ -63,13 +61,15 @@ jobs:
           name: Install mmtrack dependencies
           command: |
             pip install -U openmim
-            python -m pip install git+https://github.com/votchallenge/toolkit.git
             python -m pip install git+ssh://[email protected]/open-mmlab/mmengine.git@main
-            python -m pip install << parameters.mmcv >>
-            python -m pip install git+ssh://[email protected]/open-mmlab/[email protected]
+            mim install 'mmcv >= 2.0.0rc1'
+            # TODO: fix bc-breaking from mmdet detr-refactor
+            # python -m pip install git+ssh://[email protected]/open-mmlab/[email protected]
+            mim install 'mmdet == 3.0.0rc5'
             python -m pip install git+ssh://[email protected]/open-mmlab/[email protected]
             python -m pip install -r requirements.txt
             python -m pip install git+https://github.com/JonathonLuiten/TrackEval.git
+            python -m pip install git+https://github.com/votchallenge/toolkit.git
             python -m pip install git+https://github.com/TAO-Dataset/tao.git
       - run:
           name: Build and install
@@ -91,8 +91,6 @@ jobs:
       cudnn:
         type: integer
         default: 7
-      mmcv:
-        type: string
     machine:
       image: ubuntu-2004-cuda-11.4:202110-01
       # docker_layer_caching: true
@@ -117,8 +115,10 @@ jobs:
             docker exec mmtrack apt-get -y install git
             docker exec mmtrack pip install -e /mmengine
             docker exec mmtrack pip install -U openmim
-            docker exec mmtrack pip install << parameters.mmcv >>
-            docker exec mmtrack pip install -e /mmdetection
+            docker exec mmtrack mim install 'mmcv >= 2.0.0rc1'
+            # TODO: fix bc-breaking from mmdet detr-refactor
+            # docker exec mmtrack pip install -e /mmdetection
+            docker exec mmtrack mim install 'mmdet == 3.0.0rc5'
             docker exec mmtrack pip install -e /mmclassification
             docker exec mmtrack pip install -r requirements.txt
             docker exec mmtrack python -m pip install git+https://github.com/JonathonLuiten/TrackEval.git
@@ -157,16 +157,14 @@ workflows:
           name: minimum_version_cpu
           torch: 1.7.0
           torchvision: 0.8.1
-          python: 3.6.9  # The lowest python 3.6.x version available on CircleCI images
-          mmcv: https://download.openmmlab.com/mmcv/dist/cpu/torch1.6.0/mmcv-2.0.0rc1-cp36-cp36m-manylinux1_x86_64.whl
+          python: 3.7.4  # The lowest python 3.7.x version available on CircleCI images
           requires:
             - lint
       - build_cpu:
           name: maximum_version_cpu
           torch: 1.13.0
           torchvision: 0.14.0
           python: 3.9.0
-          mmcv: https://download.openmmlab.com/mmcv/dist/cpu/torch1.9.0/mmcv-2.0.0rc1-cp39-cp39-manylinux1_x86_64.whl
           requires:
             - minimum_version_cpu
       - hold:
@@ -179,7 +177,6 @@ workflows:
           # Use double quotation mark to explicitly specify its type
           # as string instead of number
           cuda: "10.2"
-          mmcv: https://download.openmmlab.com/mmcv/dist/cu102/torch1.8.0/mmcv-2.0.0rc1-cp37-cp37m-manylinux1_x86_64.whl
           requires:
             - hold
   merge_stage_test:
@@ -192,7 +189,6 @@ workflows:
           torch: 1.8.1
           # Use double quotation mark to explicitly specify its type
           # as string instead of number
-          mmcv: https://download.openmmlab.com/mmcv/dist/cu102/torch1.8.0/mmcv-2.0.0rc1-cp37-cp37m-manylinux1_x86_64.whl
           cuda: "10.2"
           filters:
             branches:

docs/en/user_guides/2_dataset_prepare.md

@@ -39,6 +39,7 @@ Please download the datasets from the official websites. It is recommended to sy
 - The `annotations` under `lvis` contains the official annotations of lvis-v0.5 which can be downloaded according to [here](https://github.com/lvis-dataset/lvis-api/issues/23#issuecomment-894963957). The synset mapping file `coco_to_lvis_synset.json` used in `./tools/dataset_converters/tao/merge_coco_with_lvis.py` script can be found [here](https://github.com/TAO-Dataset/tao/tree/master/data).
 
 - For users in China, the following datasets can be downloaded from [OpenDataLab](https://opendatalab.com/) with high speed:
+
   - [MOT17](https://opendatalab.com/MOT17/download)
   - [CrowdHuman](https://opendatalab.com/CrowdHuman/download)
   - [LVIS](https://opendatalab.com/LVIS/download)

mmtrack/models/track_heads/mask2former_head.py

@@ -673,7 +673,7 @@ def predict_by_feat(self,
         if len(mask_cls_results) > 0:
             scores = F.softmax(mask_cls_results, dim=-1)[:, :-1]
             labels = torch.arange(self.num_classes).unsqueeze(0).repeat(
-                self.num_queries, 1).flatten(0, 1)
+                self.num_queries, 1).flatten(0, 1).to(scores.device)
             # keep top-10 predictions
             scores_per_image, topk_indices = scores.flatten(0, 1).topk(
                 10, sorted=False)

tests/test_datasets/test_transforms/test_loading.py

@@ -52,4 +52,4 @@ def test_repr(self):
                                    'with_label=False, with_instance_id=True, '
                                    'with_mask=False, with_seg=False, '
                                    "poly2mask=True, imdecode_backend='cv2', "
-                                   "file_client_args={'backend': 'disk'})")
+                                   'file_client_args=None)')