Add ncnn deployment examples

[zhiqwang]

• Add ONNX export tools
• Add ncnn C++ inference examples
• Add ncnn Python inference examples

[codecov]

Codecov Report

Merging #145 (d941d94) into master (947956f) will increase coverage by 0.15%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master     #145      +/-   ##
==========================================
+ Coverage   84.34%   84.49%   +0.15%     
==========================================
  Files          11       12       +1     
  Lines         811      819       +8     
==========================================
+ Hits          684      692       +8     
  Misses        127      127              

Flag	Coverage Δ
unittests	84.49% <100.00%> (+0.15%)	⬆️

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Impacted Files	Coverage Δ
test/test_models_common.py	100.00% <100.00%> (ø)

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[zhiqwang]

Exported natively by ncnnoptimize is

Reshape                  Reshape_259              1 1 671 689 0=6400 1=-1 2=3
Permute                  Transpose_260            1 1 689 h1 0=1
Convolution              Conv_261                 1 1 644_splitncnn_0 691 0=255 1=1 5=1 6=65280
Reshape                  Reshape_275              1 1 691 709 0=1600 1=-1 2=3
Permute                  Transpose_276            1 1 709 h2 0=1
Convolution              Conv_277                 1 1 670 711 0=255 1=1 5=1 6=130560
Reshape                  Reshape_291              1 1 711 729 0=400 1=-1 2=3
Permute                  Transpose_292            1 1 729 h3 0=1

[zhiqwang]

Exported natively by onnx2ncnn is

185 212
Input            images                   0 1 images
Split            splitncnn_input0         1 4 images images_splitncnn_0 images_splitncnn_1 images_splitncnn_2 images_splitncnn_3
Crop             Slice_4                  1 1 images_splitncnn_3 365 -23309=1,0 -23310=1,2147483647 -23311=1,1
Crop             Slice_9                  1 1 365 370 -23309=1,0 -23310=1,2147483647 -23311=1,2
Crop             Slice_14                 1 1 images_splitncnn_2 375 -23309=1,1 -23310=1,2147483647 -23311=1,1
Crop             Slice_19                 1 1 375 380 -23309=1,0 -23310=1,2147483647 -23311=1,2
Crop             Slice_24                 1 1 images_splitncnn_1 385 -23309=1,0 -23310=1,2147483647 -23311=1,1
Crop             Slice_29                 1 1 385 390 -23309=1,1 -23310=1,2147483647 -23311=1,2
Crop             Slice_34                 1 1 images_splitncnn_0 395 -23309=1,1 -23310=1,2147483647 -23311=1,1
Crop             Slice_39                 1 1 395 400 -23309=1,1 -23310=1,2147483647 -23311=1,2
Concat           Concat_40                4 1 370 380 390 400 401 0=0

[zhiqwang]

We don't use this function yet, but we'll put it here for now and see how to call this part later, or do some experiments with it.

cc @xiguadong

[zhiqwang]

The whole process of exporting PyTorch to ONNX and then to ncnn is currently a bit cumbersome. We have verified the feasibility of the whole process in this PR, and we will continue to explore whether we can simplify the process next. For now, I'm merging this branch to facilitate the subsequent work.

[zhiqwang]

The whole work is just in the beginning of deploying yolort with ncnn. If you have some new ideas, you can add them to this thread as well.

cc @xiguadong .