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Functions1,032 in github.com/MegaScenes/nvs

⨍ Functions 1,032◇ Types & classes 170
↓ 2 callersFunctionget_render_poses
https://github.com/vt-vl-lab/3d-photo-inpainting/blob/60ce4fcc5f8dc37a2b65bb72ef6287addc024bbf/utils.py#L839
dataloader/util_3dphoto.py:320
↓ 2 callersFunctionget_shift_poses
(shift_amount=0.06)
dataloader/util_3dphoto.py:364
↓ 2 callersFunctiongroup_dict_by_key
(cond, d)
ldm/modules/x_transformer.py:93
↓ 2 callersFunctiongroupby_prefix_and_trim
(prefix, d)
ldm/modules/x_transformer.py:110
↓ 2 callersFunctionimgname_to_depthname
(aligned_depth_path, imgname)
dataloader/util_3dphoto.py:438
↓ 2 callersFunctionimgnames_to_warpname
(imgname1, imgname2)
dataloader/util_3dphoto.py:425
↓ 2 callersMethodinit_from_ckpt
(self, path, ignore_keys=list(), only_model=False)
ldm/models/diffusion/ddpm.py:197
↓ 2 callersMethodinit_from_ckpt
(self, path, ignore_keys=list(), only_model=False)
ldm/models/diffusion/backup_ddpm.py:197
↓ 2 callersMethodinit_from_ckpt
(self, path, ignore_keys=list(), only_model=False)
ldm/models/diffusion/all_functions_ddpm.py:197
↓ 2 callersFunctionintrinsics_to_matrix
(intrinsics)
dataloader/data_helpers.py:727
↓ 2 callersFunctionload_image
(img_fpath, scale_factor=1, ensure_multiple_of=1, ensure_min_size=-1)
dataloader/util_3dphoto.py:226
↓ 2 callersFunctionlog_image_table
(grid, test=False)
train.py:163
↓ 2 callersFunctionmake_ddim_sampling_parameters
(alphacums, ddim_timesteps, eta, verbose=True)
ldm/modules/diffusionmodules/util.py:63
↓ 2 callersFunctionmake_ddim_timesteps
(ddim_discr_method, num_ddim_timesteps, num_ddpm_timesteps, verbose=True)
ldm/modules/diffusionmodules/util.py:46
↓ 2 callersMethodmanifold_radii
(self, features: np.ndarray)
ldm/modules/evaluate/adm_evaluator.py:270
↓ 2 callersFunctionmesh_warping
(fname, fname2, aligned_depth, imgname_dict1, imgname_dict2, target_res=256, n=None)
dataloader/util_3dphoto.py:393
↓ 2 callersFunctionmkdir
(path)
ldm/modules/image_degradation/utils_image.py:153
↓ 2 callersFunctionnorm_thresholding
(x0, value)
ldm/models/diffusion/sampling_util.py:42
↓ 2 callersFunctionnormalize_tensor
(in_feat, eps=1e-10)
ldm/modules/evaluate/evaluate_perceptualsim.py:18
↓ 2 callersMethodp_sample
(self, x, c, t, clip_denoised=False, repeat_noise=False, return_codebook_ids=False, quantize_
ldm/models/diffusion/ddpm.py:1259
↓ 2 callersMethodp_sample
(self, x, c, t, clip_denoised=False, repeat_noise=False, return_codebook_ids=False, quantize_
ldm/models/diffusion/backup_ddpm.py:1083
↓ 2 callersMethodp_sample
(self, x, c, t, clip_denoised=False, repeat_noise=False, return_codebook_ids=False, quantize_
ldm/models/diffusion/all_functions_ddpm.py:1160
↓ 2 callersMethodp_sample_ddim
(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,
ldm/models/diffusion/ddim.py:195
↓ 2 callersMethodpairwise_distances
Evaluate pairwise distances between two batches of feature vectors.
ldm/modules/evaluate/adm_evaluator.py:415
↓ 2 callersFunctionposenc_nerf
Concatenate x and its positional encodings, following NeRF.
dataloader/data_helpers.py:210
↓ 2 callersMethodpredict_start_from_noise
(self, x_t, t, noise)
ldm/models/diffusion/backup_ddpm.py:267
↓ 2 callersMethodpreprocess_image
(self, image_path, segmentation_path=None)
ldm/data/coco.py:101
↓ 2 callersMethodprogressive_denoising
(self, cond, shape, verbose=True, callback=None, quantize_denoised=False, img_ca
ldm/models/diffusion/backup_ddpm.py:1114
↓ 2 callersMethodq_posterior
(self, x_start, x_t, t)
ldm/models/diffusion/ddpm.py:273
↓ 2 callersMethodq_posterior
(self, x_start, x_t, t)
ldm/models/diffusion/backup_ddpm.py:273
↓ 2 callersMethodq_posterior
(self, x_start, x_t, t)
ldm/models/diffusion/all_functions_ddpm.py:273
↓ 2 callersFunctionrandom_crop
(lq, hq, sf=4, lq_patchsize=64)
ldm/modules/image_degradation/bsrgan.py:427
↓ 2 callersMethodread_activations
(self, npz_path: str)
ldm/modules/evaluate/adm_evaluator.py:159
↓ 2 callersMethodread_statistics
( self, npz_path: str, activations: Tuple[np.ndarray, np.ndarray] )
ldm/modules/evaluate/adm_evaluator.py:186
↓ 2 callersMethodregister_schedule
(self, given_betas=None, beta_schedule="linear", timesteps=1000, linear_start=1e-4,
ldm/models/diffusion/ddpm.py:127
↓ 2 callersMethodregister_schedule
(self, given_betas=None, beta_schedule="linear", timesteps=1000, linear_start=1e-4,
ldm/models/diffusion/backup_ddpm.py:127
↓ 2 callersMethodregister_schedule
(self, given_betas=None, beta_schedule="linear", timesteps=1000, linear_start=1e-4,
ldm/models/diffusion/all_functions_ddpm.py:127
↓ 2 callersFunctionresize_depth
(depth, trgt_H, trgt_W)
dataloader/util_3dphoto.py:36
↓ 2 callersFunctionrotation_x
Compute the rotation matrices for a batch of x-axis (roll) rotations.
ldm/data/data_helpers.py:304
↓ 2 callersFunctionrotation_y
Compute the rotation matrices for a batch of y-axis (elevation) rotations.
ldm/data/data_helpers.py:288
↓ 2 callersFunctionrotation_z
Compute the rotation matrices for a batch of z-axis (azimuth) rotations.
ldm/data/data_helpers.py:272
↓ 2 callersMethodsample
(self, batch_size=16, return_intermediates=False)
ldm/models/diffusion/backup_ddpm.py:319
↓ 2 callersMethodsample
(self, batch_size=16, return_intermediates=False)
ldm/models/diffusion/all_functions_ddpm.py:319
↓ 2 callersFunctionsave_outputs
(refimg, outputs, warps, posetype)
video_script.py:155
↓ 2 callersFunctionshift_pixel
shift pixel for super-resolution with different scale factors Args: x: WxHxC or WxH sf: scale factor upper_left: shift dir
ldm/modules/image_degradation/bsrgan_light.py:99
↓ 2 callersFunctionshift_pixel
shift pixel for super-resolution with different scale factors Args: x: WxHxC or WxH sf: scale factor upper_left: shift dir
ldm/modules/image_degradation/bsrgan.py:99
↓ 2 callersMethodstep
Performs a single optimization step. Args: closure (callable, optional): A closure that reevaluates the model and
ldm/util.py:197
↓ 2 callersFunctiontimestep_embedding
Create sinusoidal timestep embeddings. :param timesteps: a 1-D Tensor of N indices, one per batch element. These may be
ldm/modules/diffusionmodules/util.py:151
↓ 2 callersMethodto_rgb
(self, x)
ldm/models/autoencoder.py:419
↓ 2 callersMethodupdate
Compute reconstruction metrics. Args: ref (numpy array): _description_ trg (_type_): _description_ mask
evaluation/recon_metrics.py:68
↓ 1 callersMethod__getitem__
(self, index)
ldm/data/backup_simple.py:494
↓ 1 callersMethod__init__
Apply classifier guidance Specify a guidance scale as either a scalar Or a schedule as a list of tuples t = 0->1 and scale, e.g.
ldm/guidance.py:24
↓ 1 callersMethod__len__
(self)
ldm/data/base.py:20
↓ 1 callersFunction_augment
(img)
ldm/modules/image_degradation/utils_image.py:475
↓ 1 callersMethod_compute_hash
(url, text)
ldm/data/laion.py:50
↓ 1 callersFunction_create_feature_graph
(input_batch)
ldm/modules/evaluate/adm_evaluator.py:608
↓ 1 callersFunction_create_softmax_graph
(input_batch)
ldm/modules/evaluate/adm_evaluator.py:625
↓ 1 callersMethod_filter_relpaths
(self, relpaths)
ldm/data/imagenet.py:48
↓ 1 callersFunction_get_paths_from_images
(path)
ldm/modules/image_degradation/utils_image.py:74
↓ 1 callersFunction_is_in_graph
Checks whether a given tensor does exists in the graph.
ldm/modules/evaluate/frechet_video_distance.py:57
↓ 1 callersMethod_load
(self)
ldm/data/imagenet.py:93
↓ 1 callersMethod_load_caption_file
(self, filename)
ldm/data/backup_simple.py:499
↓ 1 callersMethod_load_sample
(self, index)
ldm/data/backup_simple.py:73
↓ 1 callersFunction_numpy_partition
(arr, kth, **kwargs)
ldm/modules/evaluate/adm_evaluator.py:658
↓ 1 callersFunction_open_npy_file
(path: str, arr_name: str)
ldm/modules/evaluate/adm_evaluator.py:586
↓ 1 callersMethod_prepare
(self)
ldm/data/imagenet.py:45
↓ 1 callersMethod_prepare_human_to_integer_label
(self)
ldm/data/imagenet.py:80
↓ 1 callersMethod_prepare_idx_to_synset
(self)
ldm/data/imagenet.py:74
↓ 1 callersMethod_prepare_synset_to_human
(self)
ldm/data/imagenet.py:66
↓ 1 callersFunction_read_bytes
Copied from: https://github.com/numpy/numpy/blob/fb215c76967739268de71aa4bda55dd1b062bc2e/numpy/lib/format.py#L788-L886 Read from file-like
ldm/modules/evaluate/adm_evaluator.py:556
↓ 1 callersFunction_update_shapes
(pool3)
ldm/modules/evaluate/adm_evaluator.py:639
↓ 1 callersFunctionadd_margin
(pil_img, color, size=256)
ldm/util.py:40
↓ 1 callersFunctionadd_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.py:299
↓ 1 callersFunctionall_logging_disabled
A context manager that will prevent any logging messages triggered during the body from being processed. :param highest_level: the maxim
ldm/extras.py:12
↓ 1 callersFunctionanisotropic_Gaussian
generate an anisotropic Gaussian kernel Args: ksize : e.g., 15, kernel size theta : [0, pi], rotation angle range l1
ldm/modules/image_degradation/bsrgan_light.py:65
↓ 1 callersFunctionanisotropic_Gaussian
generate an anisotropic Gaussian kernel Args: ksize : e.g., 15, kernel size theta : [0, pi], rotation angle range l1
ldm/modules/image_degradation/bsrgan.py:65
↓ 1 callersFunctionappend_dims
Appends dimensions to the end of a tensor until it has target_dims dimensions. From https://github.com/crowsonkb/k-diffusion/blob/master/k_diffusi
ldm/models/diffusion/sampling_util.py:5
↓ 1 callersFunctionaugment_img
Kai Zhang (github: https://github.com/cszn)
ldm/modules/image_degradation/utils_image.py:380
↓ 1 callersFunctionavg_pool_nd
Create a 1D, 2D, or 3D average pooling module.
ldm/modules/diffusionmodules/util.py:238
↓ 1 callersMethodbackward
(ctx, *output_grads)
ldm/modules/diffusionmodules/util.py:131
↓ 1 callersFunctionbgr2ycbcr
bgr version of rgb2ycbcr only_y: only return Y channel Input: uint8, [0, 255] float, [0, 1]
ldm/modules/image_degradation/utils_image.py:573
↓ 1 callersMethodblend_rgba
(self, img)
ldm/data/nerf_like.py:79
↓ 1 callersMethodblend_rgba
(self, img)
ldm/data/nerf_like.py:123
↓ 1 callersMethodblend_rgba
(self, img)
ldm/data/nerf_like.py:163
↓ 1 callersMethodcalculate_adaptive_weight
(self, nll_loss, g_loss, last_layer=None)
ldm/modules/losses/vqperceptual.py:85
↓ 1 callersMethodcalculate_adaptive_weight
(self, nll_loss, g_loss, last_layer=None)
ldm/modules/losses/contperceptual.py:32
↓ 1 callersFunctioncompute_frechet_distance
(mu_sample,sigma_sample,mu_ref,sigma_ref)
ldm/modules/evaluate/torch_frechet_video_distance.py:25
↓ 1 callersMethodcompute_inception_score
(self, activations: np.ndarray, split_size: int = 5000)
ldm/modules/evaluate/adm_evaluator.py:201
↓ 1 callersMethodcompute_loss
(self, inp)
ldm/guidance.py:19
↓ 1 callersFunctioncompute_perceptual_similarity
(folder, pred_img, tgt_img, take_every_other)
ldm/modules/evaluate/evaluate_perceptualsim.py:353
↓ 1 callersMethodcompute_prec_recall
( self, activations_ref: np.ndarray, activations_sample: np.ndarray )
ldm/modules/evaluate/adm_evaluator.py:216
↓ 1 callersFunctioncompute_scale_and_shift
(prediction, target, mask)
ldm/data/common.py:140
↓ 1 callersFunctioncompute_statistics
(videos_fake, videos_real, device: str='cuda', bs=32, only_ref=False,only_sample=False)
ldm/modules/evaluate/torch_frechet_video_distance.py:199
↓ 1 callersMethodcompute_statistics
(self, activations: np.ndarray)
ldm/modules/evaluate/adm_evaluator.py:196
↓ 1 callersMethodconfigure_optimizers
(self)
ldm/models/autoencoder.py:198
↓ 1 callersFunctioncos_sim
(in0, in1)
ldm/modules/evaluate/evaluate_perceptualsim.py:25
↓ 1 callersFunctioncreate_pose_embedding
(rot_mat, trans_mat, K, pos_enc=False, target_res=512)
ldm/data/data_helpers.py:162
↓ 1 callersMethodddim_sampling
(self, cond, shape, x_T=None, ddim_use_original_steps=False, callb
ldm/models/diffusion/ddim.py:129
↓ 1 callersMethodencode
(self, x)
ldm/models/autoencoder.py:325
↓ 1 callersMethodencode_with_pretrained
(self,x)
ldm/modules/diffusionmodules/model.py:816
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