z-xiong / lighttrack-ncnn Goto Github PK
View Code? Open in Web Editor NEWNcnn version demo of [CVPR21] LightTrack: Finding Lightweight Neural Network for Object Tracking via One-Shot Architecture Search
Ncnn version demo of [CVPR21] LightTrack: Finding Lightweight Neural Network for Object Tracking via One-Shot Architecture Search
(base) dwarf@dwarf:~/LightTrack-ncnn-main/install/lighttrack_demo$ ./LightTrack 0
terminate called after throwing an instance of 'cv::Exception'
what(): OpenCV(4.5.4) /home/dwarf/opencv/modules/core/src/matrix_wrap.cpp:123: error: (-213:The function/feature is not implemented) Unknown/unsupported array type in function 'getMat_'
Aborted (core dumped)
请问一下我编译好后,调用摄像头的时候报错了,请问这个该怎么解决呀?如果使用视频请问对于格式有要求吗
#if NCNN_VULKAN and USE_GPU
std::cout << NCNN_VULKAN << std::endl;
ex_backbone.set_vulkan_compute(true);
#endif
// net_init.opt.use_vulkan_compute= true;
// net_init.set_vulkan_device(0);
net_init.opt.use_fp16_packed = true;
net_init.opt.use_fp16_storage = true;
net_init.opt.use_fp16_arithmetic = true;
net_init.opt.use_int8_storage = true;
net_backbone.opt.use_fp16_packed = true;
net_backbone.opt.use_fp16_storage = true;
net_backbone.opt.use_fp16_arithmetic = true;
net_backbone.opt.use_int8_storage = true;
net_neck_head.opt.use_fp16_packed = true;
net_neck_head.opt.use_fp16_storage = true;
net_neck_head.opt.use_fp16_arithmetic = true;
net_neck_head.opt.use_int8_storage = true;
我增加了这些部分,但gpu推理失败了
错误信息为
compile spir-v module failed
ERROR: 0:10: 'constant_id' : only allowed when generating SPIR-V
ERROR: 0:10: '' : compilation terminated
ERROR: 2 compilation errors. No code generated.
出错位置为
ex_backbone.extract("output.1", xf);
你好,我这里遇到如下的报错:
Update stage ---- output cls_score and bbox_pred extracting cost time : 6 ms
Update stage ---- postprocess cost time : 0 ms
pscore_window max score is: nan
通过单步调试发现, cls_score_data, bbox_pred_data1,bbox_pred_data2, bbox_pred_data3, bbox_pred_data4都是 NaN
` float* cls_score_data = (float*)cls_score.data;
cls_score_sigmoid.clear();
int cols = cls_score.w;
int rows = cls_score.h;
for (int i = 0; i < cols*rows; i++) // 18 * 18
{
cls_score_sigmoid.push_back(sigmoid(cls_score_data[i]));
}
std::vector<float> pred_x1(cols*rows, 0), pred_y1(cols*rows, 0), pred_x2(cols*rows, 0), pred_y2(cols*rows, 0);
float* bbox_pred_data1 = bbox_pred.channel(0);
float* bbox_pred_data2 = bbox_pred.channel(1);
float* bbox_pred_data3 = bbox_pred.channel(2);
float* bbox_pred_data4 = bbox_pred.channel(3);`
难道是在网络的输出地方就出错了?
ex_neck_head.extract("output.1", cls_score); // [c, w, h] = [1, 18, 18] ex_neck_head.extract("output.2", bbox_pred); // [c, w, h] = [4, 18, 18]
rknn = RKNN(verbose=True)
# pre-process config
print('--> Config model')
rknn.config(mean_values=[[0, 0, 0]], std_values=[[255, 255, 255]])
print('done')
# Load ONNX model
print('--> Loading model')
ret = rknn.load_onnx(model=ONNX_MODEL)
if ret != 0:
print('Load model failed!')
exit(ret)
print('done')
请问能加个联系方式吗。
想问下,官方训练好的模型是那个模型。
We have uploaded the pre-trained weights of the SuperNets(for both ImageNet classification and object tracking) to Google Drive. Users can use them as initialization for future research on efficient object tracking.
是网盘提供的这个文件吗。
大佬,这个按照你README中的提示,没办法编译啊,提示找不到文件,还请大佬详细指教哈
您好,我在替换了lib/models/super_model_DP.py和tracking/torch2onnx.py后,无论是转换backbone还是neck_head模型,程序都会在torch.onnx.export内突然结束,没有明显的报错,只有Process finished with exit code 132 (interrupted by signal 4: SIGILL),前面的读模型都是正常的,也能print(siam_net)
super_model_DP.py代码
torch2onnx.py代码
运行结果
我通过单步调试发现程序在F.conv2d()函数内突然中止了,不清楚是否跟我的LightTrack环境有关,我没有完全安装官方的安装脚本的库,只装了pytorch,cuda,cudnn,torchvision等转换格式必要的库,因为按照官方脚本有些库装不上。
如能解答,不胜感激
想问一下,如何训练自己的数据集,实现移动端的目标检测+跟踪?
您好,想问您仓库中的预训练模型是从官方仓库中导出的吗?
大佬您好,我按照您的步骤去做了,出现了以下问题
1、显示没有vulkan头文件。我将压缩包里的include头文件复制过去解决了这个问题。
2、上一步解决过后,还是编译错误,libopencv_world.so链接报错。请问是哪里有问题呢?
大佬你好,我想请问下您这个项目里面是对LightTrack的三部分模型都做了int8量化吗?
怎么会有这么牛逼的大神啊,竟然用c++实现如此复杂的功能啊,太强了
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.