Python-一个用于图像分类的一体化深度学习工具包

[{"title":"（ 60 个子文件 434KB ） Python-一个用于图像分类的一体化深度学习工具包","children":[{"title":"mxnet-finetuner-master","children":[{"title":"Dockerfile <span style='color:#111;'> 1.76KB </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 215B </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 16.86KB </span>","children":null,"spread":false},{"title":"docs","children":[{"title":"use_se_resnext.md <span style='color:#111;'> 874B </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 316B </span>","children":null,"spread":false},{"title":"benchmark.md <span style='color:#111;'> 3.51KB </span>","children":null,"spread":false},{"title":"train_from_scratch.md <span style='color:#111;'> 1012B </span>","children":null,"spread":false},{"title":"setup.md <span style='color:#111;'> 750B </span>","children":null,"spread":false},{"title":"pretrained_models.md <span style='color:#111;'> 5.43KB </span>","children":null,"spread":false},{"title":"use_densenet.md <span style='color:#111;'> 954B </span>","children":null,"spread":false},{"title":"freeze_layers.md <span style='color:#111;'> 1.56KB </span>","children":null,"spread":false}],"spread":true},{"title":".dockerignore <span style='color:#111;'> 50B </span>","children":null,"spread":false},{"title":"model","children":[{"title":".gitkeep <span style='color:#111;'> 0B </span>","children":null,"spread":false}],"spread":true},{"title":"setup.sh <span style='color:#111;'> 2.11KB </span>","children":null,"spread":false},{"title":"common","children":[{"title":"util.py <span style='color:#111;'> 2.22KB </span>","children":null,"spread":false},{"title":"fit.py <span style='color:#111;'> 12.72KB </span>","children":null,"spread":false},{"title":"modelzoo.py <span style='color:#111;'> 6.05KB </span>","children":null,"spread":false}],"spread":true},{"title":"classify_example","children":[{"title":"classify_example.ipynb <span style='color:#111;'> 477.99KB </span>","children":null,"spread":false}],"spread":true},{"title":"images","children":[{"title":"test","children":[{"title":".gitkeep <span style='color:#111;'> 0B </span>","children":null,"spread":false}],"spread":true},{"title":"valid","children":[{"title":".gitkeep <span style='color:#111;'> 0B </span>","children":null,"spread":false}],"spread":true},{"title":"train","children":[{"title":".gitkeep <span style='color:#111;'> 0B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"data","children":[{"title":"test","children":[{"title":".gitkeep <span style='color:#111;'> 0B </span>","children":null,"spread":false}],"spread":true},{"title":"valid","children":[{"title":".gitkeep <span style='color:#111;'> 0B </span>","children":null,"spread":false}],"spread":true},{"title":"train","children":[{"title":".gitkeep <span style='color:#111;'> 0B </span>","children":null,"spread":false}],"spread":false}],"spread":true},{"title":"Makefile <span style='color:#111;'> 603B </span>","children":null,"spread":false},{"title":"util","children":[{"title":"predict.py <span style='color:#111;'> 5.19KB </span>","children":null,"spread":false},{"title":"compose-template-nvidia-docker2.mo <span style='color:#111;'> 738B </span>","children":null,"spread":false},{"title":"sample_config.yml <span style='color:#111;'> 5.20KB </span>","children":null,"spread":false},{"title":"train_loss.py <span style='color:#111;'> 5.23KB </span>","children":null,"spread":false},{"title":"export_model.sh <span style='color:#111;'> 2.94KB </span>","children":null,"spread":false},{"title":"compose-template.mo <span style='color:#111;'> 1.06KB </span>","children":null,"spread":false},{"title":"move_images.sh <span style='color:#111;'> 1.11KB </span>","children":null,"spread":false},{"title":"finetune.sh <span style='color:#111;'> 13.66KB </span>","children":null,"spread":false},{"title":"caltech101_prepare.sh <span style='color:#111;'> 2.15KB </span>","children":null,"spread":false},{"title":"functions.py <span style='color:#111;'> 486B </span>","children":null,"spread":false},{"title":"functions <span style='color:#111;'> 9.94KB </span>","children":null,"spread":false},{"title":"classification_report.py <span style='color:#111;'> 1.67KB </span>","children":null,"spread":false},{"title":"test.sh <span style='color:#111;'> 3.92KB </span>","children":null,"spread":false},{"title":"ensemble.sh <span style='color:#111;'> 3.91KB </span>","children":null,"spread":false},{"title":"ensemble.py <span style='color:#111;'> 6.05KB </span>","children":null,"spread":false},{"title":"vendor","children":[{"title":"mo <span style='color:#111;'> 28.62KB </span>","children":null,"spread":false}],"spread":false},{"title":"slack_file_upload.py <span style='color:#111;'> 1.02KB </span>","children":null,"spread":false},{"title":"export_tmpl","children":[{"title":"mxnet_vision_service_center_crop.mo <span style='color:#111;'> 2.38KB </span>","children":null,"spread":false},{"title":"mms_app_cpu.conf.mo <span style='color:#111;'> 498B </span>","children":null,"spread":false},{"title":"mms_app_gpu.conf.mo <span style='color:#111;'> 470B </span>","children":null,"spread":false},{"title":"signature.mo <span style='color:#111;'> 368B </span>","children":null,"spread":false},{"title":"mxnet_vision_service.mo <span style='color:#111;'> 2.26KB </span>","children":null,"spread":false}],"spread":false},{"title":"log_accuracy.sh <span style='color:#111;'> 81B </span>","children":null,"spread":false},{"title":"gen_test.sh <span style='color:#111;'> 1.84KB </span>","children":null,"spread":false},{"title":"train_imagenet.py <span style='color:#111;'> 1.63KB </span>","children":null,"spread":false},{"title":"compare_results.py <span style='color:#111;'> 891B </span>","children":null,"spread":false},{"title":"save_model.sh <span style='color:#111;'> 2.69KB </span>","children":null,"spread":false},{"title":"num_layers.sh <span style='color:#111;'> 317B </span>","children":null,"spread":false},{"title":"counter.sh <span style='color:#111;'> 1.44KB </span>","children":null,"spread":false},{"title":"train_accuracy.py <span style='color:#111;'> 6.01KB </span>","children":null,"spread":false},{"title":"gen_train.sh <span style='color:#111;'> 4.32KB </span>","children":null,"spread":false},{"title":"fine-tune.py <span style='color:#111;'> 6.12KB </span>","children":null,"spread":false},{"title":"confusion_matrix.py <span style='color:#111;'> 2.83KB </span>","children":null,"spread":false}],"spread":false},{"title":"logs","children":[{"title":".gitkeep <span style='color:#111;'> 0B </span>","children":null,"spread":false}],"spread":true},{"title":"docker-entrypoint.sh <span style='color:#111;'> 1.24KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]