Torchvision models#
Model providing helper funtions to create TorchVision Deep Learning models.
TorchVision pages:
Import
from ikomia.dnn.torch import models
Functions
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Create Torchvision Faster RCNN model for training or inference. |
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Create Torchvision Mask RCNN model for training or inference. |
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Create Torchvision MnasNet model for training or inference. |
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Create Torchvision ResNet model for training or inference. |
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Create Torchvision ResNeXt model for training or inference. |
Details
- ikomia.dnn.torch.models.faster_rcnn(train_mode=False, use_pretrained=True, input_size=800, classes=2)#
Create Torchvision Faster RCNN model for training or inference.
- Parameters:
model_name (str) – model name
train_mode (boolean) – True or False
use_pretrained (boolean) – True to do transfer learning from pre-trained model, False to train from scratch
input_size (int) – input image size
classes (int) – number of classes in the dataset
- Returns:
model object
- ikomia.dnn.torch.models.mask_rcnn(train_mode=False, use_pretrained=True, input_size=800, classes=2)#
Create Torchvision Mask RCNN model for training or inference.
- Parameters:
model_name (str) – model name
train_mode (boolean) – True or False
use_pretrained (boolean) – True to do transfer learning from pre-trained model, False to train from scratch
input_size (int) – input image size
classes (int) – number of classes in the dataset
- Returns:
model object
- ikomia.dnn.torch.models.mnasnet(train_mode=False, use_pretrained=False, feature_extract=False, classes=2)#
Create Torchvision MnasNet model for training or inference.
- Parameters:
model_name (str) – model name
train_mode (boolean) – True or False
use_pretrained (boolean) – True to do transfer learning from pre-trained model, False to train from scratch
feature_extract (boolean) – transfer learning only, True to keep pre-trained features (train last layers only), False to train all layers
classes (int) – number of classes in the dataset
- Returns:
model object
- ikomia.dnn.torch.models.resnet(model_name='resnet50', train_mode=False, use_pretrained=False, feature_extract=False, classes=2)#
Create Torchvision ResNet model for training or inference.
- Parameters:
model_name (str) – model name
train_mode (boolean) – True or False
use_pretrained (boolean) – True to do transfer learning from pre-trained model, False to train from scratch
feature_extract (boolean) – transfer learning only, True to keep pre-trained features (train last layers only), False to train all layers
classes (int) – number of classes in the dataset
- Returns:
model object
- ikomia.dnn.torch.models.resnext(model_name='resnext50', train_mode=False, use_pretrained=False, feature_extract=False, classes=2)#
Create Torchvision ResNeXt model for training or inference.
- Parameters:
model_name (str) – model name
train_mode (boolean) – True or False
use_pretrained (boolean) – True to do transfer learning from pre-trained model, False to train from scratch
feature_extract (boolean) – transfer learning only, True to keep pre-trained features (train last layers only), False to train all layers
classes (int) – number of classes in the dataset
- Returns:
model object