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Lane detection model for mobile device via MNN project

C++ 92.57% C 4.33% Python 1.58% CMake 1.03% Shell 0.50%

lane-detection semantic-segmentation deep-learning mnn

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cmake c++11 issue

When I make build, I got the following issue:

lanenet_model.cpp:427:10: error: ‘iota’ is not a member of ‘std’
std::iota(indexes.begin(), indexes.end(), 0);
^~~~

My g++ version: g++ (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0

CMakefile has set CPP_11 flag on

Do you know how to fix this?

Thanks

为什么在安卓上只能运行模型的部分，导致无法获取最终结果

你好，首先感谢你的工作。按照你的说明，我成功在linux上跑通了模型，当我想移植到安卓上发现始终无法获得最终结果，在调试的过程中发现以下情况：

在linux上运行 _m_lanenet_model->runSessionWithCallBack(_m_lanenet_session, beforeCallBack, AfterCallBack, true);
可以获取到所有op的name，

LaneNet_1/bisenetv2_frontend/detail_branch/stage_1/conv_block_1_repeat_1/3x3_conv/conv/Conv2D LaneNet_1/bisenetv2_frontend/detail_branch/stage_1/conv_block_2_repeat_1/3x3_conv/conv/Conv2D LaneNet_1/bisenetv2_frontend/detail_branch/stage_2/conv_block_1_repeat_1/3x3_conv/conv/Conv2D LaneNet_1/bisenetv2_frontend/detail_branch/stage_2/conv_block_2_repeat_1/3x3_conv/conv/Conv2D LaneNet_1/bisenetv2_frontend/detail_branch/stage_2/conv_block_2_repeat_2/3x3_conv/conv/Conv2D LaneNet_1/bisenetv2_frontend/detail_branch/stage_3/conv_block_1_repeat_1/3x3_conv/conv/Conv2D LaneNet_1/bisenetv2_frontend/detail_branch/stage_3/conv_block_2_repeat_1/3x3_conv/conv/Conv2D LaneNet_1/bisenetv2_frontend/detail_branch/stage_3/conv_block_2_repeat_2/3x3_conv/conv/Conv2D LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/detail_branch/3x3_dw_conv_block/depthwise_conv_output LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/detail_branch/1x1_conv_block/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_1/se_block_1_repeat_1/stem_block/conv_block_1/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_1/se_block_1_repeat_1/stem_block/downsample_branch_left/1x1_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_1/se_block_1_repeat_1/stem_block/downsample_branch_left/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_1/se_block_1_repeat_1/stem_block/downsample_branch_right/maxpooling_block LaneNet_1/bisenetv2_frontend/semantic_branch/stage_1/se_block_1_repeat_1/stem_block/concate_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_1/se_block_1_repeat_1/stem_block/final_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/input_project_dw_conv_block/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/input_project_1x1_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/depthwise_conv_block_1/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/depthwise_conv_block_2/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/1x1_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/ge_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/depthwise_conv_block/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/1x1_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/ge_output___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/1x1_conv_block/bn/FusedBatchNorm___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/ge_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/ge_output___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/input_project_dw_conv_block/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/input_project_dw_conv_block/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/input_project_1x1_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_3/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/ge_output___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/depthwise_conv_block_1/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/depthwise_conv_block_2/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/1x1_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/ge_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/depthwise_conv_block/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/1x1_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/ge_output___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/1x1_conv_block/bn/FusedBatchNorm___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/ge_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/ge_output___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/input_project_dw_conv_block/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/input_project_dw_conv_block/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/input_project_1x1_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_4/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/ge_output___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/depthwise_conv_block_1/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/depthwise_conv_block_2/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/1x1_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/ge_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/depthwise_conv_block/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/1x1_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_1_repeat_1/gather_expansion_block/stride_equal_two_module/ge_output___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/1x1_conv_block/bn/FusedBatchNorm___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/ge_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_1/gather_expansion_block/stride_equal_one_module/ge_output___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_2/gather_expansion_block/stride_equal_one_module/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_2/gather_expansion_block/stride_equal_one_module/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_2/gather_expansion_block/stride_equal_one_module/depthwise_conv_block/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_2/gather_expansion_block/stride_equal_one_module/1x1_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_2/gather_expansion_block/stride_equal_one_module/1x1_conv_block/bn/FusedBatchNorm___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_2/gather_expansion_block/stride_equal_one_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_2/gather_expansion_block/stride_equal_one_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_2/gather_expansion_block/stride_equal_one_module/ge_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_2/gather_expansion_block/stride_equal_one_module/ge_output___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_3/gather_expansion_block/stride_equal_one_module/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_3/gather_expansion_block/stride_equal_one_module/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_3/gather_expansion_block/stride_equal_one_module/depthwise_conv_block/depthwise_conv_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_3/gather_expansion_block/stride_equal_one_module/1x1_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_3/gather_expansion_block/stride_equal_one_module/1x1_conv_block/bn/FusedBatchNorm___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_3/gather_expansion_block/stride_equal_one_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_3/gather_expansion_block/stride_equal_one_module/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ge_block_2_repeat_3/gather_expansion_block/stride_equal_one_module/ge_output LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ce_block_3_repeat_1/context_embedding_block/global_avg_pooling LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ce_block_3_repeat_1/context_embedding_block/global_avg_pooling___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ce_block_3_repeat_1/context_embedding_block/bn/FusedBatchNorm LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ce_block_3_repeat_1/context_embedding_block/bn/FusedBatchNorm LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ce_block_3_repeat_1/context_embedding_block/conv_block_1/conv/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ce_block_3_repeat_1/context_embedding_block/conv_block_1/relu___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ce_block_3_repeat_1/context_embedding_block/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ce_block_3_repeat_1/context_embedding_block/fused_features LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ce_block_3_repeat_1/context_embedding_block/fused_features___tr4LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ce_block_3_repeat_1/context_embedding_block/final_conv_block/Conv2D LaneNet_1/bisenetv2_frontend/semantic_branch/stage_5/ce_block_3_repeat_1/context_embedding_block/final_conv_block/Conv2D LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/semantic_branch/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/semantic_branch/semantic_upsample_features LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/semantic_branch/semantic_upsample_sigmoid LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/detail_branch/1x1_conv_block/Conv2D___tr4LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/guided_detail_features LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/semantic_branch/semantic_upsample_sigmoid___tr4LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/guided_detail_features LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/guided_detail_features LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/detail_branch/3x3_conv_block/conv/Conv2D LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/detail_branch/avg_pooling_block LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/semantic_branch/3x3_dw_conv_block/depthwise_conv_output LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/semantic_branch/1x1_conv_block/Conv2D LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/semantic_branch/semantic_remain_sigmoid LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/detail_branch/avg_pooling_block___tr4LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/guided_semantic_features LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/semantic_branch/semantic_remain_sigmoid___tr4LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/guided_semantic_features LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/guided_semantic_features LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/guided_semantic_features___tr4LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/guided_upsample_features LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/guided_upsample_features LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/guided_upsample_features___tr4LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/fused_features LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/fused_features LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/fused_features___tr4LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/aggregation_feature_output/conv/Conv2D LaneNet_1/bisenetv2_frontend/aggregation_branch/guided_aggregation_block/aggregation_features/aggregation_feature_output/conv/Conv2D LaneNet_1/bisenetv2_frontend/binary_segmentation_branch/conv_3x3/conv/Conv2D LaneNet_1/bisenetv2_frontend/binary_segmentation_branch/conv_1x1/conv/Conv2D LaneNet_1/bisenetv2_frontend/binary_segmentation_branch/final_conv/conv/Conv2D LaneNet_1/bisenetv2_frontend/binary_segmentation_branch/binary_logits LaneNet_1/bisenetv2_frontend/binary_segmentation_branch/binary_logits___tr4LaneNet_1/bisenetv2_backend/binary_seg/Softmax LaneNet_1/bisenetv2_backend/binary_seg/Softmax LaneNet_1/bisenetv2_backend/binary_seg/ArgMax lanenet/Cast lanenet/final_binary_output LaneNet_1/bisenetv2_frontend/instance_segmentation_branch/conv_3x3/conv/Conv2D LaneNet_1/bisenetv2_frontend/instance_segmentation_branch/conv_1x1/conv/Conv2D LaneNet_1/bisenetv2_frontend/instance_segmentation_branch/instance_logits LaneNet_1/bisenetv2_backend/instance_seg/pix_bn/FusedBatchNorm LaneNet_1/bisenetv2_backend/instance_seg/pix_relu LaneNet_1/bisenetv2_backend/instance_seg/pix_embedding_conv/Conv2D LaneNet_1/bisenetv2_backend/instance_seg/pix_embedding_conv/Conv2D___tr4lanenet/final_pixel_embedding_output lanenet/final_pixel_embedding_output

但是，在安卓上运行runSessionWithCallBack（）时，只能打印前26个tensor name，说明后面都没有运行，请问这是什么情况？

为什么在visualize_instance_segmentation_result中color_map有7类，而最后结果只显示0、1、2三类

非常感谢您的开源项目，谢谢。从中学到很多，在看代码的过程中有点疑问，就是为什么在visualize_instance_segmentation_result中color_map有7类，而最后结果只显示0、1、2三类？

Lanenet with VULKAN support

@MaybeShewill-CV Hi.
I am planning to use MNN-LaneNet with VULKAN backend. Is it possible to make this repo with VULKAN backend ? I read cmakelists.txt but there is no any thing about vulkan backend.
I built MNN project and used libMNN.so in my MNN_LaneNet project but MNN_LaneNet is slower when i use VULKAN backend.

with mnn_config.type = MNN_FORWARD_CPU result :

detect, 211, cost time: 0.246000 ms
detect, 146, cost time: 0.838000 ms
detect, 153, cost time: 872.728027 ms
detect, 204, cost time: 29.430002 ms

with mnn_config.type = MNN_FORWARD_VULKAN result :

Vulkan don't support 2, ArgMax: lanenet_model/vgg_backend/binary_seg/ArgMax
Vulkan don't support 9, Cast: lanenet/Cast
detect, 146, cost time: 0.755000 ms
detect, 153, cost time: 2487.019043 ms
detect, 204, cost time: 31.821001 ms

MNNConverter_TOOL_PATH

Hello,I don't know the MNNConverter_TOOL_PATH?I had make the mnn,but i don't find the tool_path?can you give me the examples?

Convert MNN Model error

python ./tools/freeze_lanenet_model.py it can output tusimple_lanenet.pb, I can parse this model file, and visualize well. but convert mnn model err:
==== output_shape is not consistent with inferred output shape in MNN. ====
====(height,width): (32,64) vs (1024,1024)
====Converte Tensorflow's Op lanenet_model/vgg_frontend/vgg16_decode_module/binary_seg_decode/decode_stage_4_fuse/deconv/deconv/conv2d_transpose , type = Conv2DBackpropInput, failed, may be some node is not const
==== output_shape is not consistent with inferred output shape in MNN. ====
====(height,width): (32,64) vs (1024,1024)
====Converte Tensorflow's Op lanenet_model/vgg_frontend/vgg16_decode_module/binary_seg_decode/decode_stage_4_fuse/deconv/deconv/conv2d_transpose , type = Conv2DBackpropInput, failed, may be some node is not const
==== output_shape is not consistent with inferred output shape in MNN. ====
====(height,width): (32,64) vs (1024,1024)
====Converte Tensorflow's Op lanenet_model/vgg_frontend/vgg16_decode_module/binary_seg_decode/decode_stage_4_fuse/deconv/deconv/conv2d_transpose , type = Conv2DBackpropInput, failed, may be some node is not const
1=1 in onComputeInfo, 389
How should i do, thx !

ckpt file 下载链接失效

使用https://www.dropbox.com/sh/yndoipxt6nbhg5g/AAAPxZDDO2N0HP0YonetamJoa?dl=0下载，提示文件已删除，请问下有其他的下载链接吗？

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