File size: 3,386 Bytes
08ec965 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# link to the dataset folder, model weights and the config file.
export DETECTRON2_DATASETS=/path/to/DETECTRON2_DATASETS/
model_weights="http://dl.fbaipublicfiles.com/cutler/checkpoints/cutler_cascade_final.pth"
config_file="model_zoo/configs/CutLER-ImageNet/cascade_mask_rcnn_R_50_FPN.yaml"
num_gpus=2
echo "========== start evaluating the model on all 11 datasets =========="
test_dataset='cls_agnostic_clipart'
echo "========== evaluating ${test_dataset} =========="
python train_net.py --num-gpus ${num_gpus} \
--config-file ${config_file} \
--test-dataset ${test_dataset} --no-segm \
--eval-only MODEL.WEIGHTS ${model_weights}
test_dataset='cls_agnostic_watercolor'
echo "========== evaluating ${test_dataset} =========="
python train_net.py --num-gpus ${num_gpus} \
--config-file ${config_file} \
--test-dataset ${test_dataset} --no-segm \
--eval-only MODEL.WEIGHTS ${model_weights}
test_dataset='cls_agnostic_comic'
echo "========== evaluating ${test_dataset} =========="
python train_net.py --num-gpus ${num_gpus} \
--config-file ${config_file} \
--test-dataset ${test_dataset} --no-segm \
--eval-only MODEL.WEIGHTS ${model_weights}
test_dataset='cls_agnostic_voc'
echo "========== evaluating ${test_dataset} =========="
python train_net.py --num-gpus ${num_gpus} \
--config-file ${config_file} \
--test-dataset ${test_dataset} --no-segm \
--eval-only MODEL.WEIGHTS ${model_weights}
test_dataset='cls_agnostic_objects365'
echo "========== evaluating ${test_dataset} =========="
python train_net.py --num-gpus ${num_gpus} \
--config-file ${config_file} \
--test-dataset ${test_dataset} --no-segm \
--eval-only MODEL.WEIGHTS ${model_weights}
test_dataset='cls_agnostic_openimages'
echo "========== evaluating ${test_dataset} =========="
python train_net.py --num-gpus ${num_gpus} \
--config-file ${config_file} \
--test-dataset ${test_dataset} --no-segm \
--eval-only MODEL.WEIGHTS ${model_weights}
test_dataset='cls_agnostic_kitti'
echo "========== evaluating ${test_dataset} =========="
python train_net.py --num-gpus ${num_gpus} \
--config-file ${config_file} \
--test-dataset ${test_dataset} --no-segm \
--eval-only MODEL.WEIGHTS ${model_weights}
test_dataset='cls_agnostic_coco'
echo "========== evaluating ${test_dataset} =========="
python train_net.py --num-gpus ${num_gpus} \
--config-file ${config_file} \
--test-dataset ${test_dataset} \
--eval-only MODEL.WEIGHTS ${model_weights}
test_dataset='cls_agnostic_coco20k'
echo "========== evaluating ${test_dataset} =========="
python train_net.py --num-gpus ${num_gpus} \
--config-file ${config_file} \
--test-dataset ${test_dataset} \
--eval-only MODEL.WEIGHTS ${model_weights}
test_dataset='cls_agnostic_lvis'
echo "========== evaluating ${test_dataset} =========="
# LVIS should set TEST.DETECTIONS_PER_IMAGE=300
python train_net.py --num-gpus ${num_gpus} \
--config-file ${config_file} \
--test-dataset ${test_dataset} \
--eval-only MODEL.WEIGHTS ${model_weights} TEST.DETECTIONS_PER_IMAGE 300
test_dataset='cls_agnostic_uvo'
echo "========== evaluating ${test_dataset} =========="
python train_net.py --num-gpus ${num_gpus} \
--config-file ${config_file} \
--test-dataset ${test_dataset} \
--eval-only MODEL.WEIGHTS ${model_weights}
echo "========== evaluation is completed ==========" |