Hello Everyone, I am learning the reins of Oak - D Lite for some personal projects. I trained a yolov3 tiny model to detect a cup and converted it into a .blob file and was able to perform some detections on it - (attached pic below). I was trying to derive stereo depth, and hence added those pipeline links as well and I was able to derive depth, however, the values do not seem to be accurate at all, and would really like some help.

This is what I have done so far in deriving depth:
1) Added all the stereo depth pipelines in addition to the RGB camera
2) The Yolo model spit out some bounding box values, which then I used to find the center point
3) Using the center point coordinates, I asked for the depth frame value at those cells(I have converted the depth frame from the Oak camera into a NumPy array)

I have attached the picture below, the blue dot at the center is where I am trying to derive depth. It gives me a depth value of 425 mm, whereas I am close to 150-200mm of the cup.

  • erik replied to this.

    Hi Dinesh ,
    Could you display the disparity frame as well? By default, min depth perception of OAK-D Lite is 35cm (docs here), so 15cm won't be perceived. You could also check our similar demo here; calc-spatials-on-host
    Thoughts?
    Thanks, Erik

    Hey Erik, I did notice that the camera was reading a little better when it was around 45cms away. I will be sure to post a disparity and depth map pic soon