Hello,
I have a segmentation UNET model that I have trained with TAO on 3 classes: "building", "floor", "other". I used:
toolkit_version: 3.22.05
deepstream_version: 6.0
jetpack_version: 4.6.1-b110
I have already modified the model to train on 3 classes instead of 2, the evaluation worked and gave satisfactory results on the validation and test data, I have modified the config file and the labels.txt file for this repo, but the output is always binary (e.g. using 2 colors).
The evaluation process went good, providing a Segmentation accuracy of 87% on validation data.
I have converted the model using the following command for the tlt-converter:
Also, I am using this config file for the ./ds-tao-segmentation:
[property]
gpu-id=0
net-scale-factor=0.007843
model-color-format=0
offsets=127.5;127.5;127.5
labelfile-path=./unet_labels.txt
##Replace following path to your model file
model-engine-file=/home/jetson/Downloads/segmentator.engine
#current DS cannot parse onnx etlt model, so you need to
#convert the etlt model to TensoRT engine first use tao-convert
tlt-encoded-model=/home/jetson/Downloads/model_segmentator.etlt
tlt-model-key=tlt_encode
infer-dims=3;320;320
batch-size=1
## 0=FP32, 1=INT8, 2=FP16 mode
network-mode=2
num-detected-classes=3
interval=0
gie-unique-id=1
network-type=2
output-blob-names=softmax_1
segmentation-threshold=0.0
##specify the output tensor order, 0(default value) for CHW and 1 for HWC
segmentation-output-order=1
[class-attrs-all]
roi-top-offset=0
roi-bottom-offset=0
detected-min-w=0
detected-min-h=0
detected-max-w=0
detected-max-h=0
For visualization, however, I get a binary segmentation mask instead of a segmentation maps with 3 colors.:
Could you kindly help me how I can:
make the segmentation mask centered and cropped only to its dimensions
have a segmentation map that uses more than 2 colors
what does the model-color-format parameter from the config file do? When changing from 0 to 1 I get a slightly more complete segmentation map, with the same colors, as seen below:
Hello, I have a segmentation UNET model that I have trained with TAO on 3 classes: "building", "floor", "other". I used:
I have already modified the model to train on 3 classes instead of 2, the evaluation worked and gave satisfactory results on the validation and test data, I have modified the config file and the labels.txt file for this repo, but the output is always binary (e.g. using 2 colors).
This is the specs file used for training:
The evaluation process went good, providing a Segmentation accuracy of 87% on validation data. I have converted the model using the following command for the tlt-converter:
Also, I am using this config file for the ./ds-tao-segmentation:
with the labels.txt file as:
I am running inference using this command:
For visualization, however, I get a binary segmentation mask instead of a segmentation maps with 3 colors.:
Could you kindly help me how I can:
All the best!