136 lines
3.6 KiB
Markdown
136 lines
3.6 KiB
Markdown
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### opencv to ncnn
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* cv::Mat CV_8UC3 -> ncnn::Mat 3 channel + swap RGB/BGR
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```cpp
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// cv::Mat a(h, w, CV_8UC3);
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ncnn::Mat in = ncnn::Mat::from_pixels(a.data, ncnn::Mat::PIXEL_BGR2RGB, a.cols, a.rows);
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```
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* cv::Mat CV_8UC3 -> ncnn::Mat 3 channel + keep RGB/BGR order
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```cpp
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// cv::Mat a(h, w, CV_8UC3);
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ncnn::Mat in = ncnn::Mat::from_pixels(a.data, ncnn::Mat::PIXEL_RGB, a.cols, a.rows);
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```
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* cv::Mat CV_8UC3 -> ncnn::Mat 1 channel + do RGB2GRAY/BGR2GRAY
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```cpp
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// cv::Mat rgb(h, w, CV_8UC3);
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ncnn::Mat inrgb = ncnn::Mat::from_pixels(rgb.data, ncnn::Mat::PIXEL_RGB2GRAY, rgb.cols, rgb.rows);
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// cv::Mat bgr(h, w, CV_8UC3);
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ncnn::Mat inbgr = ncnn::Mat::from_pixels(bgr.data, ncnn::Mat::PIXEL_BGR2GRAY, bgr.cols, bgr.rows);
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```
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* cv::Mat CV_8UC1 -> ncnn::Mat 1 channel
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```cpp
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// cv::Mat a(h, w, CV_8UC1);
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ncnn::Mat in = ncnn::Mat::from_pixels(a.data, ncnn::Mat::PIXEL_GRAY, a.cols, a.rows);
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```
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* cv::Mat CV_32FC1 -> ncnn::Mat 1 channel
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* **You could construct ncnn::Mat and fill data into it directly to avoid data copy**
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```cpp
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// cv::Mat a(h, w, CV_32FC1);
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ncnn::Mat in(a.cols, a.rows, 1, (void*)a.data);
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in = in.clone();
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```
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* cv::Mat CV_32FC3 -> ncnn::Mat 3 channel
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* **You could construct ncnn::Mat and fill data into it directly to avoid data copy**
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```cpp
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// cv::Mat a(h, w, CV_32FC3);
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ncnn::Mat in_pack3(a.cols, a.rows, 1, (void*)a.data, (size_t)4u * 3, 3);
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ncnn::Mat in;
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ncnn::convert_packing(in_pack3, in, 1);
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```
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* std::vector < cv::Mat > + CV_32FC1 -> ncnn::Mat multiple channels
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* **You could construct ncnn::Mat and fill data into it directly to avoid data copy**
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```cpp
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// std::vector<cv::Mat> a(channels, cv::Mat(h, w, CV_32FC1));
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int channels = a.size();
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ncnn::Mat in(a[0].cols, a[0].rows, channels);
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for (int p=0; p<in.c; p++)
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{
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memcpy(in.channel(p), (const uchar*)a[p].data, in.w * in.h * sizeof(float));
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}
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```
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### ncnn to opencv
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* ncnn::Mat 3 channel -> cv::Mat CV_8UC3 + swap RGB/BGR
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* **You may need to call in.substract_mean_normalize() first to scale values from 0..1 to 0..255**
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```cpp
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// ncnn::Mat in(w, h, 3);
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cv::Mat a(in.h, in.w, CV_8UC3);
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in.to_pixels(a.data, ncnn::Mat::PIXEL_BGR2RGB);
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```
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* ncnn::Mat 3 channel -> cv::Mat CV_8UC3 + keep RGB/BGR order
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* **You may need to call in.substract_mean_normalize() first to scale values from 0..1 to 0..255**
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```cpp
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// ncnn::Mat in(w, h, 3);
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cv::Mat a(in.h, in.w, CV_8UC3);
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in.to_pixels(a.data, ncnn::Mat::PIXEL_RGB);
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```
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* ncnn::Mat 1 channel -> cv::Mat CV_8UC1
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* **You may need to call in.substract_mean_normalize() first to scale values from 0..1 to 0..255**
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```cpp
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// ncnn::Mat in(w, h, 1);
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cv::Mat a(in.h, in.w, CV_8UC1);
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in.to_pixels(a.data, ncnn::Mat::PIXEL_GRAY);
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```
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* ncnn::Mat 1 channel -> cv::Mat CV_32FC1
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* **You could consume or manipulate ncnn::Mat data directly to avoid data copy**
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```cpp
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// ncnn::Mat in;
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cv::Mat a(in.h, in.w, CV_32FC1);
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memcpy((uchar*)a.data, in.data, in.w * in.h * sizeof(float));
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```
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* ncnn::Mat 3 channel -> cv::Mat CV_32FC3
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* **You could consume or manipulate ncnn::Mat data directly to avoid data copy**
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```cpp
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// ncnn::Mat in(w, h, 3);
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ncnn::Mat in_pack3;
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ncnn::convert_packing(in, in_pack3, 3);
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cv::Mat a(in.h, in.w, CV_32FC3);
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memcpy((uchar*)a.data, in_pack3.data, in.w * in.h * 3 * sizeof(float));
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```
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* ncnn::Mat multiple channels -> std::vector < cv::Mat > + CV_32FC1
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* **You could consume or manipulate ncnn::Mat data directly to avoid data copy**
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```cpp
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// ncnn::Mat in(w, h, channels);
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std::vector<cv::Mat> a(in.c);
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for (int p=0; p<in.c; p++)
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{
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a[p] = cv::Mat(in.h, in.w, CV_32FC1);
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memcpy((uchar*)a[p].data, in.channel(p), in.w * in.h * sizeof(float));
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}
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```
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