hello Alexander,
I'd like to make my tracker stronger, trying some haarcascades on the fly. Anything like this :
cascades 1 to 3 are different cascades files;
if self.cascade_1:
faces = self.cascade_1.detectMultiScale(input_image, **self.haar_params)
# If that fails, check the profile template
if len(faces) == 0 and self.cascade_3:
faces = self.cascade_3.detectMultiScale(input_image, **self.haar_params)
# If that also fails, check a the other frontal template
if len(faces) == 0 and self.cascade_2:
faces = self.cascade_2.detectMultiScale(input_image, **self.haar_params)
Is it possible to do it with your lib ?
cv2gpu.init_gpu_detector(self.cascade_1)
tried with different instances, doesn't work !
a = cv2gpu
a.init_gpu_detector(cascade_file_gpu_1)
b = cv2gpu
b.init_gpu_detector(cascade_file_gpu_2)
c = cv2gpu
c.init_gpu_detector(cascade_file_gpu_3)
hello Alexander, I'd like to make my tracker stronger, trying some haarcascades on the fly. Anything like this :
cascades 1 to 3 are different cascades files;
Is it possible to do it with your lib ? cv2gpu.init_gpu_detector(self.cascade_1)