Merge branch 'main' of https://github.com/IDEA-Research/detrex

docs/source/tutorials/Installation.md

@@ -28,7 +28,89 @@ $ python -m pip install -e detectron2
 $ pip install -e .
 ```
 
-To **rebuild** detrex that's built from a local clone, use `rm -rf build/` to clean the old build first.
+- To **rebuild** detrex that's built from a local clone, use `rm -rf build/` to clean the old build first.
+- To ensure proper installation of the customized CUDA operator, make sure your environment has the [CUDA runtime](https://developer.nvidia.com/cuda-downloads) correctly installed and verify that the `CUDA_HOME` **environment parameter** is set to the `CUDA` dir. If not, you can manually set it using the command `export CUDA_HOME=/usr/local/cuda-11.3` (this is just an example).
+
+## Verify the installation
+To verify whether detrex is installed correctly, we provide some sample codes for users to run an inference demo to confirm it. Note that if you've not installed CUDA operator (e.g. `MultiScaleDeformableAttention`) correctly, You can still train the model that does not use the customized CUDA operator (e.g. `DAB-DETR`, `DN-DETR`, etc).
+
+**Step 1.** Download the pretrained weights and demo image.
+```bash
+cd detrex
+
+# download pretrained DAB-DETR model
+wget https://github.com/IDEA-Research/detrex-storage/releases/download/v0.1.0/dab_detr_r50_50ep.pth
+
+# download pretrained DINO model
+wget https://github.com/IDEA-Research/detrex-storage/releases/download/v0.2.1/dino_r50_4scale_12ep.pth
+
+# download the demo image
+wget https://github.com/IDEA-Research/detrex-storage/releases/download/v0.2.1/idea.jpg
+```
+
+**Step 2.** Verify the inference demo.
+
+Option (a). Inference pretrained weights on demo image.
+```bash
+python demo/demo.py --config-file projects/dab_detr/configs/dab_detr_r50_50ep.py \
+                    --input "./idea.jpg" \
+                    --output "./demo_output.jpg" \
+                    --opts train.init_checkpoint="./dab_detr_r50_50ep.pth"
+```
+You can check the `demo_output.jpg` and see the detected objects on chair, plants, etc.
+
+To verify if the customized CUDA operator is correctly installed, you can inference the demo image with DINO pretrained weights as:
+```bash
+python demo/demo.py --config-file projects/dino/configs/dino_r50_4scale_12ep.py \
+                    --input "./idea.jpg" \
+                    --output "./demo_output.jpg" \
+                    --opts train.init_checkpoint="./dino_r50_4scale_12ep.pth"
+```
+
+The visualization results will be like:
+
+![](assets/demo_output.jpg)
+
+Option (b): You can also verify the inference results on standard dataset like **COCO 2017 `val`**:
+
+To evaluate `DAB-DETR` using single node with 4 gpus:
+```bash
+export DETECTRON2_DATASETS=/path/to/datasets
+
+python tools/train_net.py --config-file projects/dab_detr/configs/dab_detr_r50_50ep.py \
+                          --num-gpus 4 \
+                          --eval-only \
+                          train.init_checkpoint="./dab_detr_r50_50ep.pth"
+```
+
+Expected results:
+
+```bash
+Evaluation results for bbox:
+|   AP   |  AP50  |  AP75  |  APs   |  APm   |  APl   |
+|:------:|:------:|:------:|:------:|:------:|:------:|
+| 43.277 | 63.895 | 45.884 | 23.399 | 47.059 | 62.113 |
+```
+
+To evaluate `DINO` using single node with 4 gpus:
+
+```bash
+export DETECTRON2_DATASETS=/path/to/datasets
+
+python tools/train_net.py --config-file projects/dino/configs/dino_r50_4scale_12ep.py \
+                          --num-gpus 4 \
+                          --eval-only \
+                          train.init_checkpoint="./dino_r50_4scale_12ep.pth"
+```
+
+Expected results:
+
+```bash
+Evaluation results for bbox:
+|   AP   |  AP50  |  AP75  |  APs   |  APm   |  APl   |
+|:------:|:------:|:------:|:------:|:------:|:------:|
+| 49.193 | 66.649 | 53.800 | 32.295 | 52.485 | 63.567 |
+```
 
 ## Common Installation Issues
 If you meet some installation problems with `detectron2`, please see [detectron2 installation issues](https://detectron2.readthedocs.io/en/latest/tutorials/install.html#common-installation-issues) for more details.

setup.py

@@ -216,10 +216,10 @@ def gen_packages_items():
 
     setup(
         name="detrex",
-        version="0.1.0",
+        version="0.2.1",
         author="International Digital Economy Academy",
         url="https://github.com/rentainhe/detrex",
-        description="IDEA open source toolbox for visual recognition tasks",
+        description="IDEA open source toolbox for transformer-based instance recognition tasks",
         license=license,
         install_requires=parse_requirements("requirements.txt"),
         packages=find_packages(