The repo is about our recent work on object detection in aerial image, the paper of the work "Clustered Object Detection in Aerial Image" (ICCV2019) and its supplementatry are available here or ResearchGate. If you think this project is useful for you, feel free to leave a star. (^^)

1. The work is implemented based on Caffe2 , please install it according to the corresponding instruction.
2. Clone the repo

git clone https://github.com/fyangneil/Clustered-Object-Detection-in-Aerial-Image.git.

Please follow the instruction in Detectron to install the repo.

Here, we use VisDrone dataset as an example to demonstrate the process to generate cluster region ground truth.

1. run "./detectron/ops/add_cluster_annotation.m" to generate cluster ground truth and add it to original object annotation files.
2. run "./detectron/ops/visdrone2cocoformat.m" to convert VisDrone format annotation to COCO format.

cd $ROOT_DIR/ClusDet
python ./tools/train_net.py \
    --cfg ./configs/e2e_faster_rcnn_R-50-FPN_CPNet_1x_1GPU.yaml \
    OUTPUT_DIR ./trainedmodel/faster_rcnn_R-50-FPN_CPNet_1x_1GPU

python tools/test_net.py \
    --cfg ./configs/e2e_faster_rcnn_R-50-FPN_CPNet_1x_1GPU.yaml \
    TEST.WEIGHTS ./trainedmodel/faster_rcnn_R-50-FPN_CPNet_1x_1GPU/train/coco_2014_train/generalized_rcnn/model_final.pkl \
    NUM_GPUS 1

crop cluster regions by running

python detectron/ops/crop_cluster_proposals.py

Please Change the corresponding path when used on your computer.

python ./tools/train_net.py \
  --cfg ./configs/e2e_faster_rcnn_R-50-FPN_1x_1GPU.yaml \
  OUTPUT_DIR ./trainedmodel/faster_rcnn_R-50-FPN_1x_1GPU

python tools/test_net.py \
    --cfg ./configs/e2e_faster_rcnn_R-50-FPN_1x_1GPU.yaml \
    TEST.WEIGHTS ./trainedmodel/faster_rcnn_R-50-FPN_1x_1GPU/train/coco_2014_train/generalized_rcnn/model_final.pkl \
    NUM_GPUS 1

run "./detectron/ops/fuse_global_cluster_detections.m"

If you want to crop the image evenly, run "./detectron/ops/evenly_image_partition.m"

If you have any questions regarding the code, please feel free to contact me fyang@temple.edu

@InProceedings{Yang_2019_ICCV, author = {Yang, Fan and Fan, Heng and Chu, Peng and Blasch, Erik and Ling, Haibin}, title = {Clustered Object Detection in Aerial Images}, booktitle = {The IEEE International Conference on Computer Vision (ICCV)}, month = {October}, year = {2019} }