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name: "PNet" | |
input: "data" | |
input_dim: 1 | |
input_dim: 3 | |
input_dim: 12 | |
input_dim: 12 | |
layer { | |
name: "conv1" | |
type: "Convolution" |
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name: "ONet" | |
input: "data" | |
input_dim: 1 | |
input_dim: 3 | |
input_dim: 48 | |
input_dim: 48 | |
################################## | |
layer { | |
name: "conv1" | |
type: "Convolution" |
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name: "RNet" | |
input: "data" | |
input_dim: 1 | |
input_dim: 3 | |
input_dim: 24 | |
input_dim: 24 | |
########################## | |
###################### |
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# Enter your network definition here. | |
# Use Shift+Enter to update the visualization. | |
# Faster-resnet-101-FPN | |
name: "ResNet-101-FPN" | |
layer { | |
name: 'input-data' | |
type: 'Python' | |
top: 'data' | |
top: 'im_info' | |
top: 'gt_boxes' |
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name: "VGG_ILSVRC_16_layers" | |
layer { | |
name: 'input-data' | |
type: 'Python' | |
top: 'data' | |
top: 'im_info' | |
top: 'gt_boxes' | |
python_param { | |
module: 'roi_data_layer.layer' | |
layer: 'RoIDataLayer' |
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name: "ResNet101" | |
layer { | |
name: 'input-data' | |
type: 'Python' | |
top: 'data' | |
top: 'im_info' | |
top: 'gt_boxes' | |
python_param { | |
module: 'roi_data_layer.layer' |
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name: "ResNet101" | |
layer { | |
name: 'input-data' | |
type: 'Python' | |
top: 'data' | |
top: 'im_info' | |
top: 'gt_boxes' | |
python_param { | |
module: 'roi_data_layer.layer' |