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Functions202 in github.com/Parskatt/DeDoDe

⨍ Functions 202◇ Types & classes 41
↓ 23 callersFunctionget_best_device
(verbose = False)
DeDoDe/utils.py:15
↓ 20 callersMethodload
( self, model, optimizer, lr_scheduler, n, )
DeDoDe/checkpoint.py:35
↓ 11 callersMethodsave
( self, model, optimizer, lr_scheduler, n, )
DeDoDe/checkpoint.py:15
↓ 10 callersMethoddetect_from_path
(self, im_path, num_keypoints = 30_000, H = 784, W = 784, dense = False)
DeDoDe/detectors/dedode_detector.py:65
↓ 9 callersMethodbuild_scenes
(self, split="train", min_overlap=0.0, scene_names = None, **kwargs)
DeDoDe/datasets/megadepth.py:226
↓ 8 callersFunctiondedode_detector_L
(device = get_best_device(), weights = None, remove_borders = False)
DeDoDe/model_zoo/dedode_models.py:67
↓ 6 callersMethoddescribe_keypoints_from_path
(self, im_path, keypoints, H = 784, W = 784)
DeDoDe/descriptors/dedode_descriptor.py:48
↓ 5 callersFunctionwarp_kpts
Warp kpts0 from I0 to I1 with depth, K and Rt Also check covisibility and depth consistency. Depth is consistent if relative error < 0.2 (hard
DeDoDe/utils.py:449
↓ 4 callersMethodcompute_cross_entropy
(self, log_p_hat, p)
DeDoDe/detectors/keypoint_loss.py:93
↓ 4 callersMethoddetect
(self, batch, num_keypoints = 10_000)
DeDoDe/detectors/dedode_detector.py:43
↓ 4 callersMethoddevice
(self)
DeDoDe/transformer/dinov2.py:158
↓ 4 callersMethodmatch
(self, keypoints_A, descriptions_A, keypoints_B, descriptions_B, P_A = None, P_B = None,
DeDoDe/matchers/dual_softmax_matcher.py:11
↓ 4 callersMethodprepare_tokens_with_masks
(self, x, masks=None)
DeDoDe/transformer/dinov2.py:192
↓ 4 callersMethodto_pixel_coords
(self, x, H, W)
DeDoDe/detectors/dedode_detector.py:72
↓ 3 callersMethod__init__
(self, size = "19", pretrained=False, amp = False, amp_dtype = torch.float16)
DeDoDe/encoder.py:26
↓ 3 callersMethodbenchmark
(self, detector)
DeDoDe/benchmarks/num_inliers.py:56
↓ 3 callersFunctionget_gt_warp
(depth1, depth2, T_1to2, K1, K2, depth_interpolation_mode = 'bilinear', relative_depth_error_threshold = 0.05,
DeDoDe/utils.py:207
↓ 3 callersFunctionhomog_transform
(Homog, x)
DeDoDe/utils.py:666
↓ 3 callersFunctionsample_keypoints
(scoremap, num_samples = 8192, device = get_best_device(), use_nms = True, sample_topk =
DeDoDe/utils.py:116
↓ 3 callersFunctiontensor_to_pil
(x, unnormalize=False, autoscale = False)
DeDoDe/utils.py:565
↓ 3 callersFunctionto_best_device
(batch, device=get_best_device())
DeDoDe/utils.py:586
↓ 3 callersFunctionto_normalized_coords
(flow, h1, w1)
DeDoDe/utils.py:622
↓ 3 callersFunctionto_pixel_coords
(flow, h1, w1)
DeDoDe/utils.py:610
↓ 3 callersFunctiontrain_k_steps
( n_0, k, dataloader, model, objective, optimizer, lr_scheduler, grad_scaler = None, progress_bar=True )
DeDoDe/train.py:22
↓ 3 callersMethodweight_scenes
(self, concat_dataset, alpha=0.5)
DeDoDe/datasets/megadepth.py:264
↓ 2 callersMethodbenchmark
(self, detector, descriptor)
DeDoDe/benchmarks/nll_benchmark.py:50
↓ 2 callersMethodcompute_kl_div
(self, log_p, log_q)
DeDoDe/detectors/keypoint_loss.py:64
↓ 2 callersFunctioncompute_pose_error
(T_0to1, R, t)
DeDoDe/utils.py:281
↓ 2 callersFunctioncompute_relative_pose
(R1, t1, R2, t2)
DeDoDe/utils.py:605
↓ 2 callersMethodcreate_block
( self, in_dim, out_dim, dw=True, kernel_size=5, bias = True,
DeDoDe/decoder.py:54
↓ 2 callersFunctiondedode_descriptor_B
(device = get_best_device(), weights = None)
DeDoDe/model_zoo/dedode_models.py:126
↓ 2 callersFunctiondedode_descriptor_G
(device = get_best_device(), weights = None, dinov2_weights = None)
DeDoDe/model_zoo/dedode_models.py:183
↓ 2 callersMethoddescribe_keypoints
(self, batch, keypoints)
DeDoDe/descriptors/dedode_descriptor.py:39
↓ 2 callersFunctiondrop_add_residual_stochastic_depth
( x: Tensor, residual_func: Callable[[Tensor], Tensor], sample_drop_ratio: float = 0.0, )
DeDoDe/transformer/layers/block.py:110
↓ 2 callersFunctiondrop_add_residual_stochastic_depth_list
( x_list: List[Tensor], residual_func: Callable[[Tensor, Any], Tensor], sample_drop_ratio: float =
DeDoDe/transformer/layers/block.py:181
↓ 2 callersFunctiondual_log_softmax_matcher
(desc_A: tuple['B','N','C'], desc_B: tuple['B','M','C'], inv_temperature = 1, normalize = False)
DeDoDe/utils.py:680
↓ 2 callersFunctionestimate_pose
(kpts0, kpts1, K0, K1, norm_thresh, conf=0.99999)
DeDoDe/utils.py:46
↓ 2 callersFunctionfast_inv_2x2
(matrix: tuple[...,2,2], eps = 1e-10)
DeDoDe/utils.py:101
↓ 2 callersMethodforward
( self, batch, )
DeDoDe/detectors/dedode_detector.py:21
↓ 2 callersMethodforward_features
(self, x, masks=None)
DeDoDe/transformer/dinov2.py:222
↓ 2 callersFunctionget_attn_bias_and_cat
this will perform the index select, cat the tensors, and provide the attn_bias from cache
DeDoDe/transformer/layers/block.py:157
↓ 2 callersMethodload_depth
(self, depth_ref, crop=None)
DeDoDe/datasets/megadepth.py:76
↓ 2 callersMethodload_im
(self, im_B, crop=None)
DeDoDe/datasets/megadepth.py:62
↓ 2 callersFunctionmake_2tuple
(x)
DeDoDe/transformer/layers/patch_embed.py:17
↓ 2 callersMethodmasked_log_softmax
(self, logits, mask)
DeDoDe/detectors/keypoint_loss.py:67
↓ 2 callersFunctionpose_auc
(errors, thresholds)
DeDoDe/utils.py:290
↓ 2 callersMethodrand_shake
(self, *things)
DeDoDe/datasets/megadepth.py:92
↓ 2 callersMethodscale_detections
(self, detections, wi, hi)
DeDoDe/datasets/megadepth.py:88
↓ 2 callersMethodscale_intrinsic
(self, K, wi, hi)
DeDoDe/datasets/megadepth.py:83
↓ 2 callersFunctiontrain_step
(train_batch, model, objective, optimizer, grad_scaler = None,**kwargs)
DeDoDe/train.py:6
↓ 1 callersMethod__init__
(self, layers, *args, super_resolution = False, num_prototypes = 1, **kwargs)
DeDoDe/decoder.py:7
↓ 1 callersMethod__init__
( self, in_features: int, hidden_features: Optional[int] = None, out_features:
DeDoDe/transformer/layers/swiglu_ffn.py:14
↓ 1 callersFunction_build_mlp
(nlayers, in_dim, bottleneck_dim, hidden_dim=None, use_bn=False, bias=True)
DeDoDe/transformer/layers/dino_head.py:45
↓ 1 callersMethod_get_intermediate_layers_chunked
(self, x, n=1)
DeDoDe/transformer/dinov2.py:251
↓ 1 callersMethod_get_intermediate_layers_not_chunked
(self, x, n=1)
DeDoDe/transformer/dinov2.py:239
↓ 1 callersFunctionadd_residual
(x, brange, residual, residual_scale_factor, scaling_vector=None)
DeDoDe/transformer/layers/block.py:142
↓ 1 callersFunctionangle_error_mat
(R1, R2)
DeDoDe/utils.py:270
↓ 1 callersFunctionangle_error_vec
(v1, v2)
DeDoDe/utils.py:276
↓ 1 callersMethodcompute_batch_metrics
(self, detector, descriptor, batch, device = "cuda")
DeDoDe/benchmarks/nll_benchmark.py:21
↓ 1 callersMethodcompute_batch_metrics
(self, outputs, batch, device = get_best_device())
DeDoDe/benchmarks/num_inliers.py:22
↓ 1 callersMethodcompute_detection_img
(self, detections, mask, B, H, W, device = "cuda")
DeDoDe/detectors/keypoint_loss.py:79
↓ 1 callersMethodcompute_jensen_shannon_div
(self, log_p, log_q)
DeDoDe/detectors/keypoint_loss.py:61
↓ 1 callersMethodcompute_joint_neg_log_likelihood
(self, logits_A, logits_B_to_A, detections_A = None, detections_B_to_A = None, mask = None, device = "cuda", d
DeDoDe/detectors/keypoint_loss.py:40
↓ 1 callersMethodcompute_matchability
(self, keypoint_p, has_depth, B, K, H, W, device = "cuda")
DeDoDe/detectors/keypoint_loss.py:96
↓ 1 callersMethoddetect_dense
(self, batch)
DeDoDe/detectors/dedode_detector.py:55
↓ 1 callersFunctiondraw_kpts
(im, kpts)
demo/demo_kpts.py:8
↓ 1 callersFunctiondraw_matches
(im_A, kpts_A, im_B, kpts_B)
demo/demo_match_dedode_G.py:10
↓ 1 callersFunctiondraw_matches
(im_A, kpts_A, im_B, kpts_B)
demo/demo_match.py:10
↓ 1 callersFunctiondrop_path
(x, drop_prob: float = 0.0, training: bool = False)
DeDoDe/transformer/layers/drop_path.py:15
↓ 1 callersFunctiondual_softmax_matcher
(desc_A: tuple['B','N','C'], desc_B: tuple['B','M','C'], inv_temperature = 1, normalize = False)
DeDoDe/utils.py:691
↓ 1 callersFunctionfinite_diff_grad
(f: tuple(["B", "H", "W"]), device = get_best_device())
DeDoDe/utils.py:93
↓ 1 callersFunctionfinite_diff_hessian
(f: tuple(["B", "H", "W"]), device = get_best_device())
DeDoDe/utils.py:83
↓ 1 callersMethodforward
( self, batch, )
DeDoDe/descriptors/dedode_descriptor.py:17
↓ 1 callersMethodforward
(self, x: Tensor)
DeDoDe/transformer/layers/block.py:82
↓ 1 callersMethodforward
(self, x: Tensor)
DeDoDe/transformer/layers/attention.py:49
↓ 1 callersMethodforward_features_list
(self, x_list, masks_list)
DeDoDe/transformer/dinov2.py:203
↓ 1 callersMethodforward_nested
x_list contains a list of tensors to nest together and run
DeDoDe/transformer/layers/block.py:205
↓ 1 callersFunctionfrom_homogeneous
(xh, eps = 1e-12)
DeDoDe/utils.py:663
↓ 1 callersFunctionget_branges_scales
(x, sample_drop_ratio=0.0)
DeDoDe/transformer/layers/block.py:134
↓ 1 callersFunctionget_depth_tuple_transform_ops
(resize=None, normalize=True, unscale=False)
DeDoDe/utils.py:306
↓ 1 callersFunctionget_grid
(B,H,W, device = get_best_device())
DeDoDe/utils.py:70
↓ 1 callersFunctionget_tuple_transform_ops
(resize=None, normalize=True, unscale=False, clahe = False)
DeDoDe/utils.py:313
↓ 1 callersMethodhorizontal_flip
(self, im_A, im_B, depth_A, depth_B, K_A, K_B)
DeDoDe/datasets/megadepth.py:66
↓ 1 callersMethodinit_weights
(self)
DeDoDe/transformer/dinov2.py:161
↓ 1 callersMethodinterpolate_pos_encoding
(self, x, w, h)
DeDoDe/transformer/dinov2.py:166
↓ 1 callersFunctionnamed_apply
(fn: Callable, module: nn.Module, name="", depth_first=True, include_root=False)
DeDoDe/transformer/dinov2.py:25
↓ 1 callersFunctionnumpy_to_pil
Args: x: Assumed to be of shape (h,w,c)
DeDoDe/utils.py:552
↓ 1 callersMethodread_image
(self, im_path, H = 784, W = 784, device=get_best_device())
DeDoDe/detectors/dedode_detector.py:60
↓ 1 callersMethodread_image
(self, im_path, H = 784, W = 784, device=get_best_device())
DeDoDe/descriptors/dedode_descriptor.py:45
↓ 1 callersMethodsupervised_loss
(self, outputs, batch)
DeDoDe/detectors/keypoint_loss.py:105
↓ 1 callersMethodsupervised_loss
(self, outputs, batch)
DeDoDe/descriptors/descriptor_loss.py:39
↓ 1 callersFunctionto_cuda
(batch)
DeDoDe/utils.py:579
↓ 1 callersFunctionto_homogeneous
(x)
DeDoDe/utils.py:659
↓ 1 callersFunctiontrain
(detector_weights_path = "dedode_detector_L.pth")
experiments/dedode_descriptor-G.py:21
↓ 1 callersFunctiontrain
()
experiments/dedode_detector.py:18
↓ 1 callersFunctiontrain
(detector_weights_path = "dedode_detector_L.pth")
experiments/dedode_descriptor-B.py:21
↓ 1 callersFunctiontrain_epoch
( dataloader=None, model=None, objective=None, optimizer=None, lr_scheduler=None, epoc
DeDoDe/train.py:41
↓ 1 callersFunctionvit_large
(patch_size=16, **kwargs)
DeDoDe/transformer/dinov2.py:333
↓ 1 callersMethodwarp_from_depth
(self, batch, kpts_A, kpts_B)
DeDoDe/descriptors/descriptor_loss.py:19
↓ 1 callersMethodwarp_from_homog
(self, batch, kpts_A, kpts_B)
DeDoDe/descriptors/descriptor_loss.py:34
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