Hello, in the documentation, the output shape of the landmark is described as The net outputs a blob with the shape: [1, 70], containing row-vector of 70 floating point values for 35 landmarks' normed coordinates in the form (x0, y0, x1, y1, ..., x34, y34). Howevr in my Python code I get shape as (1,57330). Can you tell me what I am doing wrong?
Lmk = cv2.dnn.readNet('facial-landmarks-35-adas-0002.xml',
# Specify target device.
Lmk.setInput(cv2.dnn.blobFromImage(frame, size=(672, 384), ddepth=cv2.CV_8U))
lmkOut = Lmk.forward()
I finally figure this out and have two important observation - can you help me answer by
1) the set input size should be (60,60) to return a shape of 70 - so the line should be Lmk.setInput(cv2.dnn.blobFromImage(frame, size=(60,60), ddepth=cv2.CV_8U)) . question is why 60 works?
2) i have a wide angle camera in my raspberry Pi and with this the face comes small relative to the whole image --> in this case the key point prediction is still within the bounding box , but do not align to the eye nose position. Do you know why this is happening?
Can you please help answer the above questions?
Thank you for contacting Intel Embedded Community.
The consultations stated in this thread should be addressed through the channels listed at the following website: