Comments (2)
Please refer to RAM/Tag2Text with Grounded-SAM. RAM/Tag2Text provides image tags, while Grounded-SAM generates corresponding bounding boxes and masks.
from recognize-anything.
Please refer to RAM/Tag2Text with Grounded-SAM. RAM/Tag2Text provides image tags, while Grounded-SAM generates corresponding bounding boxes and masks.
the detection results from RAM/Tag2Text with Grounded-SAM is different from you.
from recognize-anything.
Related Issues (20)
- Demo: batch_inference.py: error: the following arguments are required: --checkpoint, --dataset HOT 2
- parse_tag HOT 2
- Woo, it's so amazing for your rapid implementation!您好,请问现在caption的接口有开放的计划吗? HOT 1
- Question about RAM HOT 1
- loss_tag is too large HOT 1
- Question about class thresholds HOT 2
- How can I repleace tag_list with my customize vocabulary HOT 2
- 模型训练问题 HOT 6
- Question when finetuning Tag2Text Configuration HOT 1
- 中文tag文本中很多尾缀有个空格,是有什么代表含义么? HOT 1
- How to fine-tune Tag2Text with custom tags? HOT 8
- Weights for SWIN_B/SWIN_T HOT 2
- Wrong pre-trained weights for image encoder HOT 2
- available images for trained data HOT 2
- 是否有训练tiny版本的RAM++可以开源使用呢,现有模型如果太大,如果只有tagging的能力,对比多模态大模型的理解优势是不是不明显 HOT 2
- Tags categories HOT 1
- Number of tags and class_num is different by 1 HOT 2
- Visualization Map RAM
- 请问如何使用预训练模型进行微调,增加了一个类别 HOT 1
- Concat label embed RAM++ HOT 5
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from recognize-anything.