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README.md
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@@ -31,13 +31,12 @@ It combines a ConvNeXt visual encoder with a Qwen-2.5 language model, connected
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## Uses
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The model is trained for precise low-level geometric perception tasks which is able to
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- Point-on-line detection
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- Point-on-circle detection
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- Angle classification
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- Length comparison
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- Geometric annotation understanding
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Please refer to our [repo](https://github.com/euclid-multimodal/Euclid) for full input format.
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### Limitations and Applications
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## Uses
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+
The model is trained for precise low-level geometric perception tasks which is able to perform
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- Point-on-line detection
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36 |
- Point-on-circle detection
|
37 |
- Angle classification
|
38 |
- Length comparison
|
39 |
- Geometric annotation understanding
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|
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Please refer to our [repo](https://github.com/euclid-multimodal/Euclid) for full input format.
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### Limitations and Applications
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