dmlc--dgl
cbee427839
* add working scripts * add frcnn training script * remove redundent files * refactor validation computation, will optimize sgdet and training * validation finally finished * f-rcnn training * test reldn * rm file * update reldn training * data preprocess to h5 * temp * use coco json * fix conflict * new obj dataset for detection * update training * before cleanup * remove abundant files * add arg parse to train * cleanup code file * update * fix * add readme * add ipynb as demo * add demo pic * update readme * add demo script * improve paths * improve readme * add docstrings * fix args description * update readme * add models from s3 * update README Co-authored-by: Minjie Wang <minjie.wang@nyu.edu>
5 行
327 B
Bash
5 行
327 B
Bash
MXNET_CUDNN_AUTOTUNE_DEFAULT=0 python validate_reldn.py \
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--pretrained-faster-rcnn-params faster_rcnn_resnet101_v1d_visualgenome/faster_rcnn_resnet101_v1d_custom_best.params \
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--reldn-params params_resnet101_v1d_reldn/model-8.params \
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--faster-rcnn-params params_resnet101_v1d_reldn/detector_feat.features-8.params
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