Comments (3)
The use case I had was very narrow & so I wrote the minimal code. Having said that, I thought it would generalise ok; I can't think of why labels wouldn't be picked up... The code is pretty short for merge, should be pretty easy to debug; specifically printing out from_db.imgs()
& into_db.has_labels(img)
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It's ok, I rewrite the script to generate a unique Id by image, and the merge script to merge imgs and labels table.
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I'd be curious to see why it didn't work for you / what you come up with since creating a unique id per image and then copying labels across is what merge does now...
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Related Issues (20)
- default config HOT 4
- To distinguish hornet and bees HOT 2
- minimal example running on NCS HOT 14
- Train.py error: looking for the same images in test as in labels ? HOT 4
- Detecting hornets HOT 5
- Merging mistake in README HOT 1
- Typo in Rasp pi setup HOT 5
- Help Getting Started HOT 10
- ValueError: too many values to unpack (expected 2) HOT 12
- add a requirements.txt
- Only read image files from folders (train.py, data.py, label_ui.py) HOT 1
- Skip files without labels HOT 1
- Running into RAM issues with a relatively small dataset HOT 7
- ValueError: A `Concatenate` layer requires inputs with matching shapes ... HOT 2
- How do you save database HOT 2
- Is did you handle new data HOT 2
- Not reading Temp Sensor HOT 1
- Performance issues in /data.py (by P3) HOT 2
- Error when running run_sample_training_pipeline.sh HOT 9
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