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Semantic Segmentation
# FCN-Alexnet Patches for TensorRT
There exist a couple non-essential layers included in the original FCN-Alexnet which aren't supported in TensorRT and should be deleted from the `deploy.prototxt` included in the snapshot.
At the end of `deploy.prototxt`, delete the deconv and crop layers:
```
layer {
name: "upscore"
type: "Deconvolution"
bottom: "score_fr"
top: "upscore"
param {
lr_mult: 0.0
}
convolution_param {
num_output: 21
bias_term: false
kernel_size: 63
group: 21
stride: 32
weight_filler {
type: "bilinear"
}
}
}
layer {
name: "score"
type: "Crop"
bottom: "upscore"
bottom: "data"
top: "score"
crop_param {
axis: 2
offset: 18
}
}
```
And on line 24 of `deploy.prototxt`, change `pad: 100` to `pad: 0`.
Finally, copy the `fpv-labels.txt` and `fpv-deploy-colors.txt` from the aerial dataset to your model snapshot folder on Jetson. Your FCN-Alexnet model snapshot is now compatible with TensorRT. Now we can run it on Jetson and perform inference on images.
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