Predicting an object over an pretrained model is not working

[dn]

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