Caffe based 3D images descriptor. A class to extract features from an image. The so obtained descriptors can be used for classification and pose estimation goals [218].
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#include "cnn_3dobj.hpp"
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| descriptorExtractor (const String &device_type, int device_id=0) |
| Set the device for feature extraction, if the GPU is used, there should be a device_id. More...
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void | extract (InputArrayOfArrays inputimg, OutputArray feature, String feature_blob) |
| Extract features from a single image or from a vector of images. If loadNet was not called before, this method invocation will fail. More...
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int | getDeviceId () |
| Get device ID information for feature extraction. More...
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String | getDeviceType () |
| Get device type information for feature extraction. More...
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void | loadNet (const String &model_file, const String &trained_file, const String &mean_file="") |
| Initiate a classification structure, the net work parameter is stored in model_file, the network structure is stored in trained_file, you can decide whether to use mean images or not. More...
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void | setDeviceId (const int &device_id) |
| Set device ID information for feature extraction. Useful to change device without the need to reload the net. Only used for GPU. More...
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void | setDeviceType (const String &device_type) |
| Set device type information for feature extraction. Useful to change device without the need to reload the net. More...
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Caffe based 3D images descriptor. A class to extract features from an image. The so obtained descriptors can be used for classification and pose estimation goals [218].
§ descriptorExtractor()
cv::cnn_3dobj::descriptorExtractor::descriptorExtractor |
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const String & |
device_type, |
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int |
device_id = 0 |
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Set the device for feature extraction, if the GPU is used, there should be a device_id.
- Parameters
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device_type | CPU or GPU. |
device_id | ID of GPU. |
§ extract()
Extract features from a single image or from a vector of images. If loadNet was not called before, this method invocation will fail.
- Parameters
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inputimg | Input images. |
feature | Output features. |
feature_blob | Layer which the feature is extracted from. |
§ getDeviceId()
int cv::cnn_3dobj::descriptorExtractor::getDeviceId |
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Get device ID information for feature extraction.
§ getDeviceType()
String cv::cnn_3dobj::descriptorExtractor::getDeviceType |
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Get device type information for feature extraction.
§ loadNet()
void cv::cnn_3dobj::descriptorExtractor::loadNet |
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const String & |
model_file, |
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const String & |
trained_file, |
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const String & |
mean_file = "" |
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) |
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Initiate a classification structure, the net work parameter is stored in model_file, the network structure is stored in trained_file, you can decide whether to use mean images or not.
- Parameters
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model_file | Path of caffemodel which including all parameters in CNN. |
trained_file | Path of prototxt which defining the structure of CNN. |
mean_file | Path of mean file(option). |
§ setDeviceId()
void cv::cnn_3dobj::descriptorExtractor::setDeviceId |
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const int & |
device_id | ) |
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Set device ID information for feature extraction. Useful to change device without the need to reload the net. Only used for GPU.
- Parameters
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§ setDeviceType()
void cv::cnn_3dobj::descriptorExtractor::setDeviceType |
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const String & |
device_type | ) |
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Set device type information for feature extraction. Useful to change device without the need to reload the net.
- Parameters
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The documentation for this class was generated from the following file:
- /build/master-contrib_docs-lin64/opencv_contrib/modules/cnn_3dobj/include/opencv2/cnn_3dobj.hpp