zhreshold closed pull request #10427: [MXNET-288] Fix ssd example URL: https://github.com/apache/incubator-mxnet/pull/10427
This is a PR merged from a forked repository. As GitHub hides the original diff on merge, it is displayed below for the sake of provenance: As this is a foreign pull request (from a fork), the diff is supplied below (as it won't show otherwise due to GitHub magic): diff --git a/example/ssd/README.md b/example/ssd/README.md index 5759fca611f..0b970923e44 100644 --- a/example/ssd/README.md +++ b/example/ssd/README.md @@ -69,9 +69,13 @@ insanely slow. Using CUDNN is optional, but highly recommended. ### Try the demo * Download the pretrained model: [`ssd_resnet50_0712.zip`](https://github.com/zhreshold/mxnet-ssd/releases/download/v0.6/resnet50_ssd_512_voc0712_trainval.zip), and extract to `model/` directory. + * Run ``` -# cd /path/to/mxnet-ssd +# cd /path/to/incubator-mxnet/example/ssd +# download the test images +python data/demo/download_demo_images.py +# run the demo python demo.py --gpu 0 # play with examples: python demo.py --epoch 0 --images ./data/demo/dog.jpg --thresh 0.5 @@ -102,20 +106,20 @@ The suggested directory structure is to store `VOC2007` and `VOC2012` directorie in the same `VOCdevkit` folder. * Then link `VOCdevkit` folder to `data/VOCdevkit` by default: ``` -ln -s /path/to/VOCdevkit /path/to/mxnet/example/ssd/data/VOCdevkit +ln -s /path/to/VOCdevkit /path/to/incubator-mxnet/example/ssd/data/VOCdevkit ``` Use hard link instead of copy could save us a bit disk space. * Create packed binary file for faster training: ``` -# cd /path/to/mxnet/example/ssd +# cd /path/to/incubator-mxnet/example/ssd bash tools/prepare_pascal.sh # or if you are using windows python tools/prepare_dataset.py --dataset pascal --year 2007,2012 --set trainval --target ./data/train.lst -python tools/prepare_dataset.py --dataset pascal --year 2007 --set test --target ./data/val.lst --shuffle False +python tools/prepare_dataset.py --dataset pascal --year 2007 --set test --target ./data/val.lst --no-shuffle ``` * Start training: ``` -# cd /path/to/mxnet/example/ssd +# cd /path/to/incubator-mxnet/example/ssd python train.py ``` * By default, this example will use `batch-size=32` and `learning_rate=0.002`. @@ -129,23 +133,23 @@ python train.py --gpus 0,1,2,3 --batch-size 32 ### Evalute trained model Make sure you have val.rec as validation dataset. It's the same one as used in training. Use: ``` -# cd /path/to/mxnet/example/ssd +# cd /path/to/incubator-mxnet/example/ssd python evaluate.py --gpus 0,1 --batch-size 128 --epoch 0 ``` ### Convert model to deploy mode This simply removes all loss layers, and attach a layer for merging results and non-maximum suppression. Useful when loading python symbol is not available. ``` -# cd /path/to/mxnet/example/ssd +# cd /path/to/incubator-mxnet/example/ssd python deploy.py --num-class 20 ``` ### Convert caffe model -Converter from caffe is available at `/path/to/mxnet/example/ssd/tools/caffe_converter` +Converter from caffe is available at `/path/to/incubator-mxnet/example/ssd/tools/caffe_converter` This is specifically modified to handle custom layer in caffe-ssd. Usage: ``` -cd /path/to/mxnet/example/ssd/tools/caffe_converter +cd /path/to/incubator-mxnet/example/ssd/tools/caffe_converter make python convert_model.py deploy.prototxt name_of_pretrained_caffe_model.caffemodel ssd_converted # you will use this model in deploy mode without loading from python symbol(layer names inconsistent) ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
