intelligent-control-lab / kinect_smoothing Goto Github PK

Hi,
I have depth images in .bmp format.

Is that I have to convert my images to .pkl format? or is there any way to use the images directly?

Hi,

I am currently using this approach for real-time Kinect camera depth image smoothing. I collected 45 frames and send them into smoothing algorithm and then the algorithm got stuck at there forever. I changed to use just 2 frames but it didn't help at all. I wonder if I made any mistakes anywhere. Thanks for any hints.

Hello, I have tried some methods in this project ,and I find this project using so much 'for loop' ,it is too expensive ,to deal with　an image may cost serveral seconds.

Neither of these two methods seems to have obvious results. Is this reasonable?
Top: original vs Bottom: Denoising_Filter(flag="modeling", theta=60)

When I converted my depth images to .pkl file and ran the code, it gives me this error.

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-13-4693c0abb786> in <module>
      1 hole_filter = HoleFilling_Filter(flag='min')
----> 2 hf_image_frame = hole_filter.smooth_image_frames(image_frame)
      3 print('hole filled image frames (filled invalid values)')
      4 plot_image_frame(hf_image_frame)

~/Desktop/Research Project/Matlab Code/Kinect_Smoothing-master/kinect_smoothing/depth_image_smoothing.py in smooth_image_frames(self, image_frames)
    167                                 imgs=[imgs]
    168                         for img in imgs:
--> 169                                 res_img = self.smooth_image(img)
    170                                 smoothed_frames.append(res_img)
    171                 return smoothed_frames

~/Desktop/Research Project/Matlab Code/Kinect_Smoothing-master/kinect_smoothing/depth_image_smoothing.py in smooth_image(self, image)
    149                 image = image.copy()
    150                 if self.flag in ['min','max','mean','mode']:
--> 151                         smoothed_image = self.statistical_smoothing(image)
    152                 elif self.flag in ['fmi','ns']:
    153                         smoothed_image = self.inpainting_smoothing(image)

~/Desktop/Research Project/Matlab Code/Kinect_Smoothing-master/kinect_smoothing/depth_image_smoothing.py in statistical_smoothing(self, image)
    110 		"""
    111                 smoothed = image.copy()
--> 112                 h, w = image.shape
    113                 image[image <= self.valid_depth_min] = 0
    114                 image[image >= self.valid_depth_max] = 0

ValueError: too many values to unpack (expected 2)

After installing the requirements, I ran the kinect_preprocess_example.py and got error:

multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Anaconda3\lib\multiprocessing\pool.py", line 121, in worker
result = (True, func(*args, **kwds))
File "C:\Anaconda3\lib\multiprocessing\pool.py", line 44, in mapstar
return list(map(*args))
File "G:\My Drive\research\Sarah Ostadabbas\codePool\Kinect_Smoothing\kinect_preprocess_example.py", line 50, in kinect_preprocess
action, file_name = pose_path.split('/')[:-2]
ValueError: not enough values to unpack (expected 2, got 0)
"""

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
File "G:/My Drive/research/Sarah Ostadabbas/codePool/Kinect_Smoothing/kinect_preprocess_example.py", line 70, in
kicet_preprocess_multi(data_dir, pose_save_dir, num_thread=8)
File "G:/My Drive/research/Sarah Ostadabbas/codePool/Kinect_Smoothing/kinect_preprocess_example.py", line 62, in kicet_preprocess_multi
pool.map(partial(kinect_preprocess,pose_save_dir=pose_save_dir),img_files)
File "C:\Anaconda3\lib\multiprocessing\pool.py", line 268, in map
return self._map_async(func, iterable, mapstar, chunksize).get()
File "C:\Anaconda3\lib\multiprocessing\pool.py", line 657, in get
raise self._value
ValueError: not enough values to unpack (expected 2, got 0)

Process finished with exit code 1

OS: windows 10
python: 3.7