Wrong prediction when position of object is changed
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Description
I am doing an object detection on set of images. I am finetuning using the pytorch Object detection tutorial with my own set of images. I have 100-200 images. And 22 classes.
What I notice is that the model predicts well as long as the specific object is in a set position. For instance if object 1 is in position1, it predicts it as object 1. But when object 1 is moved to position2, it predicts it as object2. Object 1 and Object 2 look very similar except for few minute changes.
Training data: It is difficult for me to create a training data for 22 classes, with each class in 22 positions (Plus consider combinations of negative data, etc.). Is there a way to solve this?
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Research direction
No repository file, test, or entry point is identified. The report describes position-dependent predictions in a custom 22-class object-detection training setup; further reproduction details would be needed before defining a repository change or a verifiable completion condition.
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Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100