FreeAnchor
FreeAnchor: Learning to Match Anchors for Visual Object Detection (NeurIPS 2019)
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Download Latest Version (.zip)- free_anchor_R-101-FPN_1x.yaml
- free_anchor_R-101-FPN_e2x.yaml
- free_anchor_R-101-FPN_j2x.yaml
- free_anchor_R-50-FPN_1x.yaml
- free_anchor_X-101-FPN_e2x.yaml
- free_anchor_X-101-FPN_j2x.yaml
- predictor.py
- README.md
- webcam.py
- __init__.py
- defaults.py
- paths_catalog.py
- nms_cpu.cpp
- ROIAlign_cpu.cpp
- vision.h
- nms.cu
- ROIAlign_cuda.cu
- ROIPool_cuda.cu
- SigmoidFocalLoss_cuda.cu
- vision.h
- nms.h
- ROIAlign.h
- ROIPool.h
- SigmoidFocalLoss.h
- vision.cpp
- __init__.py
- coco.py
- concat_dataset.py
- list_dataset.py
- __init__.py
- distributed.py
- grouped_batch_sampler.py
- iteration_based_batch_sampler.py
- __init__.py
- build.py
- transforms.py
- __init__.py
- build.py
- collate_batch.py
- __init__.py
- inference.py
- trainer.py
- __init__.py
- _utils.py
- batch_norm.py
- misc.py
- nms.py
- roi_align.py
- roi_pool.py
- sigmoid_focal_loss.py
- smooth_l1_loss.py
- __init__.py
- backbone.py
- fpn.py
- resnet.py
- __init__.py
- detectors.py
- generalized_rcnn.py
- multi_scale_wrapper.py
- retinanet.py
- box_head.py
- inference.py
- loss.py
- roi_box_feature_extractors.py
- roi_box_predictors.py
- inference.py
- loss.py
- mask_head.py
- roi_mask_feature_extractors.py
- roi_mask_predictors.py
- roi_heads.py
- __init__.py
- anchor_generator.py
- free_anchor_loss.py
- inference.py
- loss.py
- retinanet.py
- retinanet_infer.py
- retinanet_loss.py
- rpn.py
- balanced_positive_negative_sampler.py
- box_coder.py
- matcher.py
- poolers.py
- utils.py
- __init__.py
- build.py
- lr_scheduler.py
- bounding_box.py
- boxlist_ops.py
- image_list.py
- segmentation_mask.py
- c2_model_loading.py
- checkpoint.py
- collect_env.py
- comm.py
- env.py
- imports.py
- logger.py
- metric_logger.py
- miscellaneous.py
- model_serialization.py
- model_zoo.py
- README.md
- __init__.py
- __init__.py
- inference_for_NR.py
- without_nms_postprocessor.py
- checkpoint.py
- test_data_samplers.py
- eval_NR.py
- multi_scale_test.py
- parse_log.py
- test_net.py
- train_net.py
- architecture.png
- INSTALL.md
- LICENSE
- README.md
- setup.py
# Installation Guide
1. Get the code
git clone https://github.com/zhangxiaosong18/FreeAnchor
Downloads the entire project code from GitHub to your computer.
cd FreeAnchor
Moves into the project folder you just downloaded.
2. Python
Easy RecommendedPrerequisites
python -m torch.distributed.launch --nproc_per_node=$NGPUS tools/train_net.py --config-file "path/to/config/file.yaml"
Runs the Python script (or module).
python -m torch.distributed.launch --nproc_per_node=$NGPUS tools/test_net.py --config-file "path/to/config/file.yaml" MODEL.WEIGHT "path/to/.pth file" DATASETS.TEST "('coco_test-dev',)"
Runs the Python script (or module).
python -m torch.distributed.launch --nproc_per_node=$NGPUS tools/multi_scale_test.py --config-file "path/to/config/file.yaml" MODEL.WEIGHT "path/to/.pth file" DATASETS.TEST "('coco_test-dev',)"
Runs the Python script (or module).
python -m torch.distributed.launch --nproc_per_node=$NGPUS tools/eval_NR.py --config-file "path/to/config/file.yaml" MODEL.WEIGHT "path/to/.pth file"
Runs the Python script (or module).
If it runs without errors and prints output in the terminal, it worked.
Pulled directly from this repo's README.
// repository documentation
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