Open lidapengpeng opened 2 weeks ago
Hi @lidapengpeng
We use a uniform transformation method for the input image, so the users don't have to refine the input image size for detection. And I was wondering the scenarios in which you need to specify the size of the input image. Regarding the setting of the box threshold, we generally recommend using a fixed threshold for more stable detection results. However, it is true that there may be a need to adjust the box threshold in actual use. We will optimize our API calls to support the setting of this parameter.
@lidapengpeng We have already update our SDK
API, you can set box threshold by setting bbox_threshold
, here is an example:
dds-sdk
firstpip install dds-cloudapi-sdk --upgrade
bbox_threshold
when calling APItask = DetectionTask(
image_url=image_url,
prompts=[TextPrompt(text=TEXT_PROMPT)],
targets=[DetectionTarget.BBox], # detect bbox
model=DetectionModel.GDino1_5_Pro,
bbox_threshold=0.1,
)
After actually testing various detectors, I found that Grounding DINO is indeed SOTA and performs very well on my own data!
When I called the API, I found that the input image resolution could not specify the size. Secondly, when outputting the results, I found that the bbox threshold score would only be output when it is above 0.2. I wanted to modify the threshold, such as greater than 0.1 manually, but I couldn't find where. Can you give me some suggestions for setting this parameter?