1996scarlet / faster-mobile-retinaface Goto Github PK

Hi Scarlet,

First of all, thanks for the great work.
I tried your algorithm yesterday and it was super simple to use.
I have some questions.

I can get the speed boost but I cannot get the same result on Wider face.
When I m trying to detect small and big faces at the same time, it doesn 't seem to work.

Do you have sample that we could test on in full HD ?

Thanks

Hi 1996,
When i run the command line from your code: gst-launch-1.0 -q v4l2src device=/dev/video0 ! video/x-raw, width=640, height=480 ! videoconvert ! video/x-raw, format=BGR ! fdsink | python3 face_detector.py
I am facing the issue:
[20:26:03] src/nnvm/legacy_json_util.cc:209: Loading symbol saved by previous version v1.5.0. Attempting to upgrade...
[20:26:03] src/nnvm/legacy_json_util.cc:217: Symbol successfully upgraded!
terminate called recursively
Aborted (core dumped)

Best regards,
PeterPham

here my code

    fd = MxnetDetectionModel("weights/16and32", 0,
                             scale=.4, gpu=-1, margin=0.15)
    img = cv2.imread('./images/test.jpg')
    copy = np.array(img)
    detach = fd.detect(copy)

    for res in fd._nms_wrapper(detach):
        cv2.rectangle(img, (res[0], res[1]),(res[2], res[3]), (255, 255, 0))
    cv2.imshow('face',img)
    cv2.waitKey()

and error

inferance: 0.009732400998473167
<generator object BaseDetection.non_maximum_suppression at 0x7f73341e28b8>
Traceback (most recent call last):
  File "face_detector.py", line 282, in <module>
    for res in fd._nms_wrapper(detach):
  File "face_detector.py", line 71, in non_maximum_suppression
    x1, y1, x2, y2, scores = dets.T
AttributeError: 'generator' object has no attribute 'T'

Thanks for your help!!

@1996scarlet Hi, thanks for your sharing. would you mind sharing the details of the difference between the optimized NMS and original NMS? Thanks a lot.

Hi 1996,
Which version python 2.7 or 3.6 are you using for this code?
Best regards,
PeterPham

How to change this code with opencv instead of gstreamer?
Whats difference of between gstreamer and opencv in cpu usage and speed?
My goal for this project is to have a large number of cameras for high fps processing.
For example 20 cameras
But the problem is that more than 7 cameras,my cpu usage reaches over 98% and it is not possible to add a new one.
How can I do this project on 20 cameras at a time?
490mb is model loaded by gpu for simgle camera and I probably won't get down to the gpu resource source. I think my problem is the cpu resource
gpu: 1080ti(11gb), cpu: core i7 9700k
Or at least how to choose the system I need for this project?

Do you have any conversion code from your model to onnx?

great work! in order to do more specific post-processing, most pipelines require more than the bounding box. Would it be possible to have a branch where your detector returns landmarks as well? At least for eyes, nose, mouth. Many thanks!

gst-launch-1.0 -q v4l2src device=/dev/video0 ! video/x-raw, width=640, height=480 ! videoconvert ! video/x-raw, format=BGR ! fdsink | python3 face_detector.py
WARNING: erroneous pipeline: no element "v4l2src"
[23:49:41] src/nnvm/legacy_json_util.cc:209: Loading symbol saved by previous version v1.5.0. Attempting to upgrade...
[23:49:41] src/nnvm/legacy_json_util.cc:217: Symbol successfully upgraded!

I'm try run code but it stop here. It no display camera
How to fix?
Thank you very much!!!

Thanks for great works..
Whats version used mxnet?
I cant to run this code