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Function render_path

script/models/rendering.py:403–458  ·  view source on GitHub ↗
(args, render_poses, hwf, chunk, render_kwargs, gt_imgs=None, savedir=None, render_factor=0, single_gt_img=False, img_ids=torch.Tensor(0))

Source from the content-addressed store, hash-verified

401
402### This is for validation ###
403def render_path(args, render_poses, hwf, chunk, render_kwargs, gt_imgs=None, savedir=None, render_factor=0, single_gt_img=False, img_ids=torch.Tensor(0)):
404 # render_kwargs['network_fn'].eval()
405
406 H, W, focal = hwf
407
408 if render_factor!=0:
409 # Render downsampled for speed
410 H = int(H//render_factor)
411 W = int(W//render_factor)
412 focal = focal/render_factor
413
414 rgbs = []
415 disps = []
416 rgb0s = []
417 psnr = []
418
419 t = time.time()
420 for i, c2w in enumerate(tqdm(render_poses)):
421 t = time.time()
422 rgb, disp, acc, extras = render(H, W, focal, chunk=chunk, c2w=c2w[:3,:4], img_idx=img_ids[i], **render_kwargs)
423 rgbs.append(rgb.cpu().numpy())
424 disps.append(disp.cpu().numpy())
425 # rgb0s.append(extras['rgb0'].cpu().numpy())
426 if i==0:
427 print(rgb.shape, disp.shape)
428
429 if gt_imgs is not None:
430 if single_gt_img:
431 p = -10. * np.log10(np.mean(np.square(rgb.cpu().numpy() - gt_imgs)))
432 else:
433 p = -10. * np.log10(np.mean(np.square(rgb.cpu().numpy() - gt_imgs[i])))
434 psnr.append(p)#print(p)
435
436 if savedir is not None:
437 # rgb8_c = to8b(rgb0s[-1]) # save coarse img
438 # filename = os.path.join(savedir, '{:03d}_coarse.png'.format(i))
439 # imageio.imwrite(filename, rgb8_c)
440
441 rgb8_f = to8b(rgbs[-1]) # save coarse+fine img
442 filename = os.path.join(savedir, '{:03d}.png'.format(i))
443 imageio.imwrite(filename, rgb8_f)
444
445 ### Need validate code
446 rgb_gt = to8b(gt_imgs[i]) # save GT img here
447 filename = os.path.join(savedir, '{:03d}_GT.png'.format(i))
448 imageio.imwrite(filename, rgb_gt)
449
450 rgb_disp = to8b(disps[-1] / np.max(disps[-1])) # save GT img here
451 filename = os.path.join(savedir, '{:03d}_disp.png'.format(i))
452 imageio.imwrite(filename, rgb_disp)
453
454 rgbs = np.stack(rgbs, 0)
455 disps = np.stack(disps, 0)
456 psnr = np.mean(psnr,0)
457 print("Mean PSNR of this run is:", psnr)
458 return rgbs, disps
459
460def render_test(args, train_dl, val_dl, hwf, start, render_kwargs_test, decoder_coarse=None, decoder_fine=None):

Callers 3

render_testFunction · 0.90
train_nerfFunction · 0.85
render_testFunction · 0.85

Calls 1

renderFunction · 0.85

Tested by

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