opencv / opencv/opencv-python

Orb Cuda computeAsync not using updated keypoints

Open
#950 1 comment 0 reactions 1 assignee View on GitHub

@asmorkalov is already working on this.

Since May 21, 2024.

Dominant language
Python
Stars
5.4k
Forks
1k
Avg merge
22h 17m
Merged PRs (30d)
3

Description

I am using the ORB cuda CV2 detector. I need to filter the keypoint returned from detect and then compute the descriptors using the updated keypoints.

Unfortunately it seems that the computeAsync uses the keypoints received from the detect.
The number of keypoints returned from detectAsync is 3000 (max number defined in orb cuda create). The filtered keypoints is 1700 but the number of descriptors is 3000.

I know that I can use detectAndComputeAsync and filter after but is much time consuming.

I am using opencV 4.8.0 with python 3.8 on windows 64bit PC.
thanks,
Iliya

Code example
##################################

            #detect keypoints
            cuMat1 = cv2.cuda_GpuMat()
            cuMat1.upload(image)
            keypoints_detected_GPU = detector.detectAsync(cuMat1, mask=None)
            keypoints_detected = detector.convert(keypoints_detected_GPU)
            
            #filter keypoints
            keypoints = FilterFunction(keypoints_detected )
            
            #upload filtered keypoints
            keypoints_np = np.array([
                [kp.pt[0] for kp in keypoints],  # x-coordinate
                [kp.pt[1] for kp in keypoints],  # y-coordinate
                [kp.response for kp in keypoints],  # response
                [kp.angle for kp in keypoints],  # angle
                [kp.octave for kp in keypoints],  # octave
                [kp.size for kp in keypoints],  # size
            ], dtype=np.float32)
            
            keypointsGpu = cv2.cuda_GpuMat()
            keypointsGpu.upload(keypoints_np)

            #Compute descriptor
            keypointsGpuCompute, descriptorsGpuCompute = detector.computeAsync(cuMat1, keypointsGpu)
            keypoints_np1 = keypointsGpuCompute.download()
            
            keypoints_list = []
            num_keypoints = keypoints_np1.shape[1]
            
            for i in range(num_keypoints):
                x = keypoints_np1[0, i]
                y = keypoints_np1[1, i]
                response = keypoints_np1[2, i]
                angle = keypoints_np1[3, i]
                octave = keypoints_np1[4, i]
                size = keypoints_np1[5, i]
            
                # Create cv2.KeyPoint object and append to the list
                kp = cv2.KeyPoint(x, y, size, angle, response, int(octave), -1)
                keypoints_list.append(kp)
            keypoints = keypoints_list

            #download descriptors
            descriptors = descriptorsGpuCompute.download()

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Assessment

This issue has not been assessed yet.

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.