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Functions1,032 in github.com/MegaScenes/nvs

⨍ Functions 1,032◇ Types & classes 170
Method__init__
assume sequential frames and a deterministic transform
ldm/data/backup_simple.py:137
Method__init__
(self, root_dir, batch_size, total_view, train=None, validation=None, test=None, num_workers=
ldm/data/backup_simple.py:169
Method__init__
Create a dataset from a folder of images. If you pass in a root directory it will be searched for images ending in ext (ext can be a l
ldm/data/backup_simple.py:209
Method__init__
Create a dataset from a folder of images. If you pass in a root directory it will be searched for images ending in ext (ext can be a l
ldm/data/backup_simple.py:330
Method__init__
(self, ds, extra_label="sksbspic")
ldm/data/backup_simple.py:417
Method__init__
(self, ret_file, *args, **kwargs)
ldm/data/backup_simple.py:509
Method__init__
(self, root_dir='datasets/RTMV/google_scanned',\ first_K=64, resolution=256, load_target=Fals
ldm/data/nerf_like.py:44
Method__init__
(self, root_dir='datasets/GoogleScannedObjects',\ split='val', first_K=5, resolution=256, loa
ldm/data/nerf_like.py:85
Method__init__
(self, root_dir='data/nerf_wild',\ first_K=33, resolution=256, load_target=False)
ldm/data/nerf_like.py:128
Method__init__
(self, embed_dim, *args, **kwargs)
ldm/models/autoencoder.py:266
Method__init__
(self, ddconfig, lossconfig, embed_dim, ck
ldm/models/autoencoder.py:287
Method__init__
(self, *args, vq_interface=False, **kwargs)
ldm/models/autoencoder.py:429
Method__init__
(self, model, schedule="linear", **kwargs)
ldm/models/diffusion/ddim.py:14
Method__init__
(self, diffusion_path, num_classes, ckpt_path=None,
ldm/models/diffusion/classifier.py:30
Method__init__
(self, first_stage_config, cond_stage_config, num_timesteps
ldm/models/diffusion/ddpm.py:488
Method__init__
(self, diff_model_config, conditioning_key)
ldm/models/diffusion/ddpm.py:1721
Method__init__
(self, model, schedule="linear", **kwargs)
ldm/models/diffusion/plms.py:13
Method__init__
(self, first_stage_config, cond_stage_config, num_timesteps
ldm/models/diffusion/backup_ddpm.py:486
Method__init__
(self, diff_model_config, conditioning_key)
ldm/models/diffusion/backup_ddpm.py:1451
Method__init__
(self, *args, low_scale_config, low_scale_key="LR", **kwargs)
ldm/models/diffusion/backup_ddpm.py:1487
Method__init__
(self, finetune_keys=("model.diffusion_model.input_blocks.0.0.weight",
ldm/models/diffusion/backup_ddpm.py:1628
Method__init__
(self, cond_stage_key, *args, **kwargs)
ldm/models/diffusion/backup_ddpm.py:1794
Method__init__
(self, *args, low_scale_key="LR", **kwargs)
ldm/models/diffusion/backup_ddpm.py:1817
Method__init__
(self, *args, low_scale_key="LR", **kwargs)
ldm/models/diffusion/backup_ddpm.py:1909
Method__init__
(self, first_stage_config, cond_stage_config, num_timesteps
ldm/models/diffusion/all_functions_ddpm.py:488
Method__init__
(self, diff_model_config, conditioning_key)
ldm/models/diffusion/all_functions_ddpm.py:1572
Method__init__
(self, input_size, num_layers, mode='ir', drop_ratio=0.4, affine=True)
ldm/thirdp/psp/model_irse.py:12
Method__init__
(self, in_channel, depth, stride)
ldm/thirdp/psp/helpers.py:78
Method__init__
(self, in_channel, depth, stride)
ldm/thirdp/psp/helpers.py:100
Method__init__
(self, model_path)
ldm/thirdp/psp/id_loss.py:8
Method__init__
(self, quantize=False, masked=False, kid_subset=1000, device='cpu')
evaluation/gen_metrics.py:16
Method__init__
(self)
evaluation/utils.py:5
Method__init__
(self, quantize=False, masked=False, device="cuda")
evaluation/recon_metrics.py:28
Method__iter__
(self)
ldm/modules/evaluate/adm_evaluator.py:485
Method__iter__
(self)
ldm/data/laion.py:73
Method__iter__
(self)
ldm/data/base.py:24
Method__len__
(self)
dataloader/paired_dataset.py:51
Method__len__
(self)
ldm/modules/evaluate/adm_evaluator.py:482
Method__len__
(self)
ldm/data/simple.py:157
Method__len__
(self)
ldm/data/imagenet.py:39
Method__len__
(self)
ldm/data/imagenet.py:336
Method__len__
(self)
ldm/data/lsun.py:36
Method__len__
(self)
ldm/data/dummy.py:11
Method__len__
(self)
ldm/data/dummy.py:27
Method__len__
(self)
ldm/data/coco.py:98
Method__len__
(self)
ldm/data/backup_simple.py:62
Method__len__
(self)
ldm/data/backup_simple.py:151
Method__len__
(self)
ldm/data/backup_simple.py:245
Method__len__
(self)
ldm/data/backup_simple.py:373
Method__len__
(self)
ldm/data/backup_simple.py:445
Method__len__
(self)
ldm/data/backup_simple.py:491
Method__len__
(self)
ldm/data/nerf_like.py:52
Method__len__
(self)
ldm/data/nerf_like.py:95
Method__len__
(self)
ldm/data/nerf_like.py:136
Method__setstate__
(self, state)
ldm/util.py:191
Method_add_tags
(self, x)
ldm/data/laion.py:58
Method_filter_predicate
(self, x)
ldm/data/laion.py:67
Method_forward
(self, x, context=None)
ldm/modules/attention.py:216
Method_forward
(self, x, emb)
ldm/modules/diffusionmodules/openaimodel.py:257
Method_forward
(self, x)
ldm/modules/diffusionmodules/openaimodel.py:320
Method_predict_eps_from_xstart
(self, x_t, t, pred_xstart)
ldm/models/diffusion/ddpm.py:1153
Method_predict_eps_from_xstart
(self, x_t, t, pred_xstart)
ldm/models/diffusion/backup_ddpm.py:996
Method_predict_eps_from_xstart
(self, x_t, t, pred_xstart)
ldm/models/diffusion/all_functions_ddpm.py:1054
Method_prepare
(self)
ldm/data/imagenet.py:150
Method_prepare
(self)
ldm/data/imagenet.py:216
Method_prior_bpd
Get the prior KL term for the variational lower-bound, measured in bits-per-dim. This term can't be optimized, as it only dep
ldm/models/diffusion/ddpm.py:1157
Method_prior_bpd
Get the prior KL term for the variational lower-bound, measured in bits-per-dim. This term can't be optimized, as it only dep
ldm/models/diffusion/backup_ddpm.py:1000
Method_prior_bpd
Get the prior KL term for the variational lower-bound, measured in bits-per-dim. This term can't be optimized, as it only dep
ldm/models/diffusion/all_functions_ddpm.py:1058
Method_punsafe_to_class
(self, punsafe)
ldm/data/laion.py:64
Method_rescale_annotations
(self, bboxes, crop_coordinates)
ldm/models/diffusion/ddpm.py:1039
Method_rescale_annotations
(self, bboxes, crop_coordinates)
ldm/models/diffusion/backup_ddpm.py:888
Method_rescale_annotations
(self, bboxes, crop_coordinates)
ldm/models/diffusion/all_functions_ddpm.py:940
Functionadd_Poisson_noise
(img)
ldm/modules/image_degradation/bsrgan_light.py:408
Functionadd_resize
(img, sf=4)
ldm/modules/image_degradation/bsrgan_light.py:343
Functionadd_sharpening
USM sharpening. borrowed from real-ESRGAN Input image: I; Blurry image: B. 1. K = I + weight * (I - B) 2. Mask = 1 if abs(I - B) > thresho
ldm/modules/image_degradation/bsrgan_light.py:299
Functionadd_speckle_noise
(img, noise_level1=2, noise_level2=25)
ldm/modules/image_degradation/bsrgan_light.py:390
Functionanalytic_kernel
Calculate the X4 kernel from the X2 kernel (for proof see appendix in paper)
ldm/modules/image_degradation/bsrgan_light.py:49
Functionanalytic_kernel
Calculate the X4 kernel from the X2 kernel (for proof see appendix in paper)
ldm/modules/image_degradation/bsrgan.py:49
Functionangles_to_matrix
Compute the rotation matrix from euler angles for a mini-batch
dataloader/data_helpers.py:409
Functionangles_to_matrix
Compute the rotation matrix from euler angles for a mini-batch
ldm/data/data_helpers.py:320
Functionaugment_img_np3
(img, mode=0)
ldm/modules/image_degradation/utils_image.py:441
Functionaugment_img_tensor
Kai Zhang (github: https://github.com/cszn)
ldm/modules/image_degradation/utils_image.py:422
Functionaugment_img_tensor4
Kai Zhang (github: https://github.com/cszn)
ldm/modules/image_degradation/utils_image.py:401
Functionaugment_imgs
(img_list, hflip=True, rot=True)
ldm/modules/image_degradation/utils_image.py:469
Functionbetas_for_alpha_bar
Create a beta schedule that discretizes the given alpha_t_bar function, which defines the cumulative product of (1-beta) over time from t = [
ldm/modules/diffusionmodules/util.py:77
Functionblur
x: image, NxcxHxW k: kernel, Nx1xhxw
ldm/modules/image_degradation/bsrgan_light.py:128
Functionblur
x: image, NxcxHxW k: kernel, Nx1xhxw
ldm/modules/image_degradation/bsrgan.py:128
Functioncalculate_fvd
Returns a list of ops that compute metrics as funcs of activations. Args: real_activations: <float32>[num_samples, embedding_size] generate
ldm/modules/evaluate/frechet_video_distance.py:135
Functioncalculate_psnr
(img1, img2, border=0)
ldm/modules/image_degradation/utils_image.py:621
Functioncalculate_ssim
calculate SSIM the same outputs as MATLAB's img1, img2: [0, 255]
ldm/modules/image_degradation/utils_image.py:642
Functioncentral_crop
(raw_im)
ldm/data/common.py:8
Functioncentral_crop_v2
(image)
ldm/data/common.py:20
Functionchannel_convert
(in_c, tar_type, img_list)
ldm/modules/image_degradation/utils_image.py:597
Functionclassical_degradation
blur + downsampling Args: x: HxWxC image, [0, 1]/[0, 255] k: hxw, double sf: down-scale factor Return: downsa
ldm/modules/image_degradation/bsrgan_light.py:284
Functionclassical_degradation
blur + downsampling Args: x: HxWxC image, [0, 1]/[0, 255] k: hxw, double sf: down-scale factor Return: downsa
ldm/modules/image_degradation/bsrgan.py:284
Functionclipval
(value, min_value, max_value)
dataloader/data_helpers.py:451
Functioncompute_T
(batch, precomputed_scale)
dataloader/data_helpers.py:599
Functioncompute_T
(config, depth_model, batch, precomputed_scale=None, return_aux=False)
ldm/data/common.py:252
Functioncompute_fvd
(ref_input, sample_input, bs=32, ref_stats=None, sample_stats=None,
ldm/modules/evaluate/torch_frechet_video_distance.py:155
Functioncompute_perceptual_similarity_from_list
(pred_imgs_list, tgt_imgs_list, take_every_other,
ldm/modules/evaluate/evaluate_perceptualsim.py:416
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