How to calculate net-scale-factor and offset

Accelerated Computing Intelligent Video Analytics DeepStream SDK
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• Hardware Platform (Jetson / GPU) Jetson
• DeepStream Version 6.1
• JetPack Version (valid for Jetson only) 5.0.2
• TensorRT Version 8.4.1.50
• Issue Type( questions, new requirements, bugs) question

Hello,

I’m currently working on implementing a detector and classifier in DeepStream, but I’ve encountered a particular problem. My classifier, which is built using TAO and utilizes Efficientnet-B0, performs admirably when used independently outside of the DeepStream environment. However, when I integrate it into the pipeline, I’m experiencing a noticeable decrease in performance. I suspect this issue might be related to the net scale factor and offset. To address this, I plan to fine-tune the net scale factor and offset parameters in a configuration file named “config_infer_secondary.txt” to optimize the classifier’s performance within the DeepStream pipeline. Could you provide guidance on how to accurately set these parameters in that file?

I used following technique but no improvement

for data in data_loader:
     image, _ = data
    for c in range(3):
        channel_mean[c] += image[0, c, :, :].mean()
        channel_std_dev[c] += image[0, c, :, :].std()

channel_mean /= len(train_dataset)
channel_std_dev /= len(train_dataset)

# Calculate unscaled standard deviation and its mean
unscaled_std = channel_std_dev * 255
unscaled_std_mean = unscaled_std.mean()

# Calculate net scale factor and offsets
net_scale_factor = 1 / unscaled_std_mean
offsets = (channel_mean * 255).tolist()
3

You are using numpy functions, please refer to document. numpy.std — NumPy v1.26 Manual
numpy.mean — NumPy v1.26 Manual

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ya but this is what i tried as per my best understanding of this numbers
I am looking for official document which explains how to calculate net-scale-factor and offests

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There formula is in Gst-nvinfer — DeepStream 6.3 Release documentation

y = net scale factor*(x-mean)

6

Thank you for your response
I am looking for formula to calculate net-scale-factor
as per my knowledge this formula shows how the net-scale-factor is used

regards

7

Please read the document, especially the first two paragraphs.

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Sorry I am still confused

The paragraph says “net-scale-factor is the pixel scaling factor specified in the configuration file. It is a float.” but how do I calculate it to include in my configuration file ?

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It should be the same as the scale factor used in the preprocessing of the training. Which parameters you used in training, please use the same parameters in inferencing.

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in the training mean and std of training data was used
net-scale-factor and offsets are required while DeepStream inference

Thank you

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There is no update from you for a period, assuming this is not an issue anymore. Hence we are closing this topic. If need further support, please open a new one. Thanks

Current DeepStream gst-nvinfer internal preprocessing algorithm does not support deviation for normalization. You may implement by yourself.

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