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From: marc nicole <mk1853387@gmail.com>
Newsgroups: comp.lang.python
Subject: Re: Predicting an object over an pretrained model is not working
Date: Wed, 31 Jul 2024 12:27:07 +0200
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Bytes: 7242

I suppose the meaning of those numbers comes from this line
predicts_dict[class_name].append([int(xmin), int(ymin), int(xmax), int(ymax),
P[index]]) as well as the yolo inference call. But i was expecting zeros
for all classes except smallball. Because the image only shows that, and
that a train and a sheep wont have any target position or any probability
whatsoever in the image weirdobject.jpg


On Wed, 31 Jul 2024, 00:19 dn via Python-list, <python-list@python.org>
wrote:

> On 31/07/24 06:18, marc nicole via Python-list wrote:
> > Hello all,
> >
> > I want to predict an object by given as input an image and want to have
> my
> > model be able to predict the label. I have trained a model using
> tensorflow
> > based on annotated database where the target object to predict was added
> to
> > the pretrained model. the code I am using is the following where I set
> the
> > target object image as input and want to have the prediction output:
>
> ...
>
>
> > WHile I expect only the dict to contain the small_ball key
>
> > How's that is possible? where's the prediction output?How to fix the
> code?
>
>
> To save us lots of reading and study to be able to help you, please advise:
>
> 1 what are the meanings of all these numbers?
>
> > 'sheep': [[233.0, 92.0, 448.0, -103.0,
> >> 5.3531270027160645], [167.0, 509.0, 209.0, 101.0, 4.947688579559326],
> >> [0.0, 0.0, 448.0, 431.0, 3.393721580505371]]
>
> 2 (assuming it hasn't) why the dict has not been sorted into a
> meaningful order
>
> 3 how can one tell that the image is more likely to be a sheep than a
> train?
>
> --
> Regards,
> =dn
> --
> https://mail.python.org/mailman/listinfo/python-list
>