Open s-JoL opened 5 years ago
~/workspace/xxx/yyy/utils/k_nearest_gaussian_kernel.py in gaussian_filter_density(img, points) 45 print(pt2d, sigma, gt_count, distances) 46 density += scipy.ndimage.filters.gaussian_filter( ---> 47 pt2d, sigma, mode='constant') 48 print('done.') 49 return density ~/miniconda3/envs/pytorch1.0/lib/python3.7/site-packages/scipy/ndimage/filters.py in gaussian_filter(input, sigma, order, output, mode, cval, truncate) 287 for axis, sigma, order, mode in axes: 288 gaussian_filter1d(input, sigma, axis, order, output, --> 289 mode, cval, truncate) 290 input = output 291 else: ~/miniconda3/envs/pytorch1.0/lib/python3.7/site-packages/scipy/ndimage/filters.py in gaussian_filter1d(input, sigma, axis, order, output, mode, cval, truncate) 202 sd = float(sigma) 203 # make the radius of the filter equal to truncate standard deviations --> 204 lw = int(truncate * sd + 0.5) 205 # Since we are calling correlate, not convolve, revert the kernel 206 weights = _gaussian_kernel1d(sigma, order, lw)[::-1] OverflowError: cannot convert float infinity to integer
I also have this problem ,can you solve it?
Excuse me, I also met this problem, how did you solve it?