Skip to content

NEGATIVE BOUNDING BOXES #29

@robertokcanale

Description

@robertokcanale

Hi,
I am training my own Keras model to use YOLO3 for inference, but i get negative and wierd bounding boxes, if any at all. I am trying to segment a hand-pressure image into PALM THUMB FINGERS (0,1,2 respectively for the classes). I use labelImg for annotation and then i convert it to xmin ymin xmax ymax class_id
I follow all the steps for custom training (with a small dataset of 200 images) but i get the following error:

Found 1 boxes for img
[ -49.221752 -130.95093 -45.08555 188.86354 ] 0.31854975

Or better, I get negative positions for my bounding boxes, why is that?

I attach a photo of my hand, its annotation in .txt, the whole train file for my script, my classes, and the image I get out of it.

155 png_screenshot_12 03 2021
1
1.txt
my_classes.txt
train.txt

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions

      pFad - Phonifier reborn

      Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

      Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


      Alternative Proxies:

      Alternative Proxy

      pFad Proxy

      pFad v3 Proxy

      pFad v4 Proxy