tensorflow / tensorflow/tflite-support
Possibility of channel-by-channel image normalization when adding metadata
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- Dominant language
- C++
- Stars
- 441
- Forks
- 146
- PR merge metrics
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Description
My model is trained on a certain mean and std:
mean = [151.2405, 119.5950, 107.8395]
std = [63.0105, 56.4570, 55.0035]
The problem is that the attempt to add these values to the metadata fails at the verification stage in mediapipe studio: "Error: UNIMPLEMENTED: Per-channel image normalization is not available.; Initialize was not ok; StartGraph failed."
Did I understand correctly that there is no possibility of channel-by-channel normalization? Are there any plans to add it? Unfortunately, if I normalize all channels with one number, the quality of my model deteriorates significantly.
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Research direction
The reported entry point is metadata verification in MediaPipe Studio, where per-channel image normalization currently fails. Start by tracing that verification and graph-start path; done means metadata with separate mean and std values for each channel verifies successfully and the graph starts.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp, tensorflow
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100