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 [229].  
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#include <opencv2/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 [229]. 
◆ descriptorExtractor()
      
        
          | cv::cnn_3dobj::descriptorExtractor::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. 
- 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 | ( |  | ) |  | 
      
 
Get device ID information for feature extraction. 
 
 
◆ getDeviceType()
      
        
          | String cv::cnn_3dobj::descriptorExtractor::getDeviceType | ( |  | ) |  | 
      
 
Get device type information for feature extraction. 
 
 
◆ loadNet()
      
        
          | void cv::cnn_3dobj::descriptorExtractor::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. 
- 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 | ( | 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. 
- Parameters
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◆ setDeviceType()
      
        
          | void cv::cnn_3dobj::descriptorExtractor::setDeviceType | ( | const String & | device_type | ) |  | 
      
 
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: