kpick.classifier package

Subpackages

• kpick.classifier.cifar_classification_models package
  • Submodules
  • kpick.classifier.cifar_classification_models.alexnet module
  • kpick.classifier.cifar_classification_models.densenet module
  • kpick.classifier.cifar_classification_models.preresnet module
  • kpick.classifier.cifar_classification_models.resnet module
  • kpick.classifier.cifar_classification_models.resnet_roi module
  • kpick.classifier.cifar_classification_models.resnext module
  • kpick.classifier.cifar_classification_models.vgg module
  • kpick.classifier.cifar_classification_models.wrn module
  • Module contents
• kpick.classifier.classification_utils package
  • Subpackages
    • kpick.classifier.classification_utils.progress package
      • Subpackages
      • Submodules
      • kpick.classifier.classification_utils.progress.setup module
      • kpick.classifier.classification_utils.progress.test_progress module
      • Module contents
  • Submodules
  • kpick.classifier.classification_utils.eval module
  • kpick.classifier.classification_utils.logger module
  • kpick.classifier.classification_utils.misc module
  • kpick.classifier.classification_utils.visualize module
  • Module contents
• kpick.classifier.models package
  • Submodules
  • kpick.classifier.models.mobilenet module
  • kpick.classifier.models.resnet module
  • Module contents

Submodules

kpick.classifier.basic_classification_models module

class kpick.classifier.basic_classification_models.MobileNetV2(*args: Any, **kwargs: Any)

Bases: Module

forward(x)

kpick.classifier.basic_classification_models.Net(model_name, **kwargs)

class kpick.classifier.basic_classification_models.ResNet(*args: Any, **kwargs: Any)

Bases: Module

forward(x)

class kpick.classifier.basic_classification_models.SimpleNet(*args: Any, **kwargs: Any)

Bases: Module

forward(x)

kpick.classifier.classifier_base module

class kpick.classifier.classifier_base.BasCifarClassfier

Bases: object

adjust_learning_rate(epoch)

arrays2tensors(ims, transform)

get_data(net_args)

get_model(net_args, net_train_args=None)

init(net_args=None, net_train_args=None, train=False)

load_model(model, checkpoint_path, input_shape=None, run_tensorRT=False, fc2conv=False)

load_model_gpu(model, checkpoint_path, fc2conv=False)

model2trt(input_shape)

predict_array(im, transform)

predict_arrays(ims, Dataset, transform, print_info=True)

predict_arrays_m(ims, transform, print_info=True)

predict_rgbd(rgbd)

predict_rgbds(rgbds)

resume()

save_checkpoint(state, is_best)

test()

train()

trainval()

class kpick.classifier.classifier_base.RGBDLoader(args, rgbds, transform)

Bases: object

kpick.classifier.classifier_base_org module

class kpick.classifier.classifier_base_org.BasCifarClassfier(args=None, cfg_path=None, name='unnamed', train=False)

Bases: BasObj

adjust_learning_rate(epoch)

arrays2tensors(ims, transform)

get_data()

get_model()

load_model(run_tensorRT=False, input_shape=None)

predict_array(im, transform)

predict_arrays(ims, Dataset, transform, print_info=True)

predict_arrays_m(ims, transform, print_info=True)

predict_rgbd(rgbd)

predict_rgbds(rgbds)

resume()

save_checkpoint(state, is_best)

test()

train()

trainval()

class kpick.classifier.classifier_base_org.RGBDLoader(args, rgbds, transform)

Bases: object

kpick.classifier.roi_classifier module

class kpick.classifier.roi_classifier.RoiCifarClassfier

Bases: BasCifarClassfier

crop_and_concate_roi_tensor(im_tensors, box_tensors, ind_tensors, scaling, isSameSize=False)

forward(tensors, model)

init(net_args, net_train_args=None, train=False)

predict_tensor_rois(im_tensors, boxes, model, net_args, scaling, inds=None, isSameSize=False)

test_conv()

Module contents