Comments (2)
Hello, @joy91269
If you find that the generated description of our model is not so accurate for your domain data, you can consider finetuning the model with your own dataset. To do this, ensure your data is formatted in accordance with the osprey-724k dataset we've provided.
When you wish to conduct inference on a collection of images, you'll need to run the demo code on your local machine. Additionally, you should craft a script that processes each image, feeding the each mask region into the model to obtain the corresponding answers.
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I send you a email to your @zju.edu.com to ask more detail things.
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Related Issues (20)
- Loss 0 during Stage 3 Training? + Stage 2 Model HOT 1
- The checkpoint-final of stage2 HOT 2
- error when load Osprey-724K/osprey_detail_description.json HOT 4
- error report when evaluate Open-Vocabulary Segmentation for cityscapes HOT 1
- Addign Open Vocabulary Segmentation to Demo HOT 2
- Mask-level Ferret? HOT 2
- Can not load the page for the online demo HOT 3
- About the LoRA implement in the code. HOT 5
- can not access your dataset HOT 2
- online demo is not work HOT 2
- 关于模型训练 HOT 1
- 如何使用HQ-SAM自动化生产mask数据 HOT 4
- 关于token数量的问题 HOT 2
- about the training log HOT 1
- How to finetune Osprey on RefCOCOg? HOT 1
- 训练过程中使用到的数据集 HOT 1
- How to use Osprey-Chat to generate a short description for all masks of an image? HOT 1
- Expecting value: line 1 column 1 (char 0) HOT 2
- Inference Scripts HOT 1
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