-
The SPHINX model leverages COCO object detection, pose estimation, and LVIS object detection annotations during fine-tuning. Notably, test datasets like RefCOCO and POPE, which are part of the COCO da…
-
I have downloaded everything but when I try the demo I get the same bounding box but the wrong labels:
![ycb out](https://github.com/mlzxy/devit/assets/12383906/52b01c89-0b09-4864-b528-e4ae1ab1863d)
…
-
-
The following is my config file
```
_BASE_: Base-COCO-InstanceSegmentation.yaml
MODEL:
BACKBONE:
NAME: "D2SwinTransformer"
SWIN:
EMBED_DIM: 128
DEPTHS: [ 2, 2, 18, 2 ]
NUM…
-
Hi,
I'm currently trying to reproduce the results from a paper, but I've noticed some discrepancies with the paper's results.
For COCO:
```bash
CUDA_VISIBLE_DEVICES=0,1,2,3 vit=l task=ovd da…
-
could you provide code about evaluation of the task of open-vocabulary object detection on the LVIS? I don't seem to find code of that
-
Hi authors, thanks for the awesome work! I noticed that in Objaverse paper you mentioned there are 10K homes generated with ProcTHOR populated with objects from OBJAVERSE-LVIS. I wonder if the scripts…
-
## Instructions To Reproduce the 🐛 Bug:
I use visualize_json_results.py to visualize the results for faster rcnn on lvis_v0.5_val dataset, however I can only get results for 12 pictures and get the f…
-
I appreciate your wonderful work! the demo is excellent!
However when I try to reproduce the result using your default settings (just running accelerate launch --config_file 8gpu.yaml train_mvdiffusi…
-
I would like to fine-tune YOLO World for segmentation. However, I cannot find how to prepare a dataset for fine-tuning in your documents (https://github.com/AILab-CVC/YOLO-World/blob/master/docs/data.…