mirror of https://github.com/alibaba/MNN.git
				
				
				
			
		
			
				
	
	
		
			37 lines
		
	
	
		
			1.1 KiB
		
	
	
	
		
			C++
		
	
	
	
			
		
		
	
	
			37 lines
		
	
	
		
			1.1 KiB
		
	
	
	
		
			C++
		
	
	
	
| //
 | |
| //  ShapeDetectionOutput.cpp
 | |
| //  MNN
 | |
| //
 | |
| //  Created by MNN on 2019/01/10.
 | |
| //  Copyright © 2018, Alibaba Group Holding Limited
 | |
| //
 | |
| 
 | |
| #include "shape/SizeComputer.hpp"
 | |
| #include "core/Macro.h"
 | |
| namespace MNN {
 | |
| 
 | |
| // Size Computer
 | |
| class DetectionOutputComputer : public SizeComputer {
 | |
|     virtual bool onComputeSize(const MNN::Op *op, const std::vector<Tensor *> &inputs,
 | |
|                                const std::vector<Tensor *> &outputs) const override {
 | |
|         MNN_ASSERT(3 <= inputs.size());
 | |
|         MNN_ASSERT(1 == outputs.size());
 | |
| 
 | |
|         // set dims
 | |
|         auto &output    = outputs[0]->buffer();
 | |
|         auto maxNumber = op->main_as_DetectionOutput()->keepTopK();
 | |
| 
 | |
|         output.dim[0].extent = 1;
 | |
|         output.dim[1].extent = 1;
 | |
|         output.dim[2].extent = maxNumber;
 | |
|         output.dim[3].extent = 6; // maximum width
 | |
|         TensorUtils::getDescribe(outputs[0])->dimensionFormat = MNN_DATA_FORMAT_NC4HW4;
 | |
|         output.type = halide_type_of<float>();
 | |
| 
 | |
|         return true;
 | |
|     }
 | |
| };
 | |
| 
 | |
| REGISTER_SHAPE(DetectionOutputComputer, OpType_DetectionOutput);
 | |
| } // namespace MNN
 |