Comments (3)
Please refer to recognize-anything/models/openset_utils.py multiple_templates. We follow [1].
[1] Zang Y, Li W, Zhou K, et al. Open-vocabulary detr with conditional matching[C]//Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part IX. Cham: Springer Nature Switzerland, 2022: 106-122.
from recognize-anything.
I appreciate your prompt response. I've noticed that the prompt templates in openset_utils.py seem to be designed primarily for noun tags. However, the tag list in ram_tag_list.txt contains some adjective and verb tags that seem incompatible with these templates, resulting in potentially illogical prompts like "a photo of my red." Could you please explain this discrepancy?
from recognize-anything.
We did not consider this. I think you are right, designing different prompts for tags with different part of speech is highly likely to improve the performance of the model.
from recognize-anything.
Related Issues (20)
- The pre-trained checkpoint HOT 1
- pre_caption function
- 4M version checkpoint HOT 1
- Can i inference RAM to output text? HOT 2
- RuntimeError: checkpoint url or path is invalid HOT 1
- 一个tag对应tag_chinese多个标签,如"table"==“桌子/表格”,如何过滤标签 HOT 6
- Error while running inference_ram_plus.py HOT 2
- generative tagging HOT 1
- Is `loss_t2t` in RAM necessary? Can I just remove it? HOT 7
- Finetuning question HOT 7
- Some questions about fine-tuning recognize-anything model HOT 1
- Relax transformers dependency version HOT 3
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- about training 4M dataset and the loss converge slowly HOT 3
- A question on embedding
- NameError: name '_C' is not defined HOT 1
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