Comments (4)
@0xNOY thanks very much. So I should change topk_instance to 10, e.g, which means top10?
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Yes, in the demo, only one object is output in the expression prompt mode. To output multiple objects, you need to change the value of the variable topK_instance
in line 174 of app/app.py.
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could you please explain more details about the grouding mode and category mode in the tokenization stage? It seems that we can input multi categoires an once in a prompt, but only one expression in a prompt? Could both modes be the same?
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@AllenDun Thank you for your interest! In our setting, if the input is an expression, the model will only find the single most relevant object, as topK=1 is a fixed parameter set by design. If you want to find multiple objects at the same time, you can try using the 'categories' -> 'custom-list' mode, which supports a list of arbitrary category names separated by commas. In this mode, you can freely set the TopK, and you can input multiple categories at once.
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Related Issues (20)
- 关于coco指标复现的问题 HOT 2
- Would it be possible to open up the source code of the inference script instead of the gradio script? HOT 8
- The training code HOT 7
- 关于训练中数据采样的问题? HOT 1
- 跨图检测 HOT 1
- COCO performance after finetuning HOT 1
- DETRs with Hybrid Matching HOT 1
- Detail about object detection decoder.
- Open Source the test code and weight files about TAO dataset
- 缺少这么多文件怎么破?OSError: Error no file named pytorch_model.bin, tf_model.h5, model.ckpt.index or flax_model.msgpack found in directory projects/GLEE/clip_vit_base_patch32. HOT 1
- Tutorial for Zero-shot Testing or Fine-tuning GLEE on New Datasets HOT 1
- No module named 'projects.GLEE' HOT 2
- Failure cases
- How to run the demo locally and correctly? HOT 4
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- 是否能像SAM或CLIP那样直接调用
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