>首先使用以下命令得到 bbox 或 segmentation 的 json 格式文件。 python tools/test.py --format-only --eval-options "jsonfile_prefix=out/out_resul" 样例 (1)得到每一类的 COCO bbox 误差结果,并保存分析结果图像至指定目录 python tools/analysis_tools/coco_error_analysis.py results.bbox.json out/ ...
AI检测代码解析 ./tools/dist_test.sh configs/pointpillars/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d.py work_dirs/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class/latest.pth 8 --out work_dirs/pp-nus/results_eval.pkl --format-only --eval-options 'jsonfile_prefix=work_dirs/pp-nus/resul...
./tools/dist_test.sh \ configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py \ checkpoints/mask_rcnn_r50_fpn_1x_coco_20200205-d4b0c5d6.pth \ 8 \ -format-only \ --options "jsonfile_prefix=./mask_rcnn_test-dev_results" 这行命令生成两个 JSON 文件 mask_rcnn_test-dev_results.bbox...
0# 表示一个val epoch 或者 train epoch内,iter的次数# 经过一个val_iter或者train_iter都加1,经过一个epoch后就归零ifmax_epochsisnotNoneandmax_itersisnotNone:raiseValueError('Only one of `max_epochs` or `max_iters` can be set.')# 不能同时指定self._max_epochs=max_epochs# EpochBasedRunner看...
运行后会报错:RuntimeError: grad can be implicitly created only for scalar outputs。这是因为张量y为非标量所致。 如何避免类似错误呢?我们手工计算Y的导数。已知: 如何求 呢? Y为一个向量,如果我们想办法把这个向量转变成一个标量不就好了?比如我们可以对Y求和,然后用求和得到的标量在对X求导,这样不会对结...
det_inferencer.py inference.py configs datasets engine evaluation models structures testing utils visualization __init__.py registry.py version.py projects requirements resources tests tools .gitignore .owners.yml .pre-commit-config-zh-cn.yaml ...
1#submissionCUDA_VISIBLE_DEVICES=0 PORT=29500 \ ./tools/dist_test.sh configs/rretinanet/rretinanet_obb_r50_fpn_1x_dota_v3.py \ work_dirs/rretinanet_obb_r50_fpn_1x_dota_v3/epoch_12.pth 1 --format-only\ --eval-options submission_dir=work_dirs/rretinanet_obb_r50_fpn_1x_dota_v3/...
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mmdet3d将detr3d的output,整理成kitti format时涉及的格式变换 mmdet3d将整理好的output,转换成waymo format,从而做evaluation和submission时,涉及的格式变换。 其中1~3主要是数据之间的坐标系变换,4~6主要是gt labels和predicted bounding box的格式变换。
Images scales for resizing.multiscale_mode (str): Either "range" or "value".ratio_range (tuple[float]): (min_ratio, max_ratio)keep_ratio (bool): Whether to keep the aspect ratio when resizing theimage."""def__init__(self,img_scale=None,multiscale_mode='range',ratio_range=None,keep...