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Output problem with ONNX inference #80

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Ranclus opened this issue Jan 25, 2024 · 7 comments
Open

Output problem with ONNX inference #80

Ranclus opened this issue Jan 25, 2024 · 7 comments

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@Ranclus
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Ranclus commented Jan 25, 2024

The output tensor is tensor: float32[1,25200,21]. What is the meaning of the 21 values for each detection? I can't find the information, and without that, I can't use the model. Pls

@iperov
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iperov commented Feb 3, 2024

traditionally, Yolo repositories have the dirtiest code

@Ranclus
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Ranclus commented Feb 3, 2024

Yes (Although not only the yolo ones. But the IA ones). I'm not even asking about the code. Just how to use it.

@iperov
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iperov commented Feb 3, 2024

are you serious? how are you going to use it without understanding the code?

@Ranclus
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Ranclus commented Feb 3, 2024

Why would I need to actually understand this particular code JUST to use it? You only need to know what's the input, and what's the output. Everything else is unnecesary for the sole purpose of using the model. For now, I know whats the input, so, I do the inference. But I don't know how to interpret the output.

I am surprised that this information isn't always the first thing displayed on the main page of the repositories.

@iperov
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iperov commented Feb 3, 2024

lmao ok

@wangsouza
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The output tensor is tensor: float32[1,25200,21]. What is the meaning of the 21 values for each detection? I can't find the information, and without that, I can't use the model. Pls

I have the same problem.
I think 21 corresponds to: 1 channel, 4 bounding box, 1 score, 15 landmarks

@potapov-dm
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5 for bbox (x_min, y_min, x_max, y_max, confidence), 1 for class, 15 for landmarks (x_1, y_1, landmark_confidence_1, ...). Not sure about order.

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