Inpaint anything using Segment Anything and inpainting models.
This report presents the forensic synthetic code analysis of geekyutao/Inpaint-Anything, a Jupyter Notebook project with 7,676 GitHub stars. SynthScan v2.0 examined 45,267 lines of code across 427 source files, recording 626 pattern matches distributed across 13 syntactic categories. The overall adjusted score of 16.1 places this repository in the Moderate AI signal band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.
Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.
This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.
The scanner identified 626 distinct pattern matches across 13 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | remove_anything_3d.py | 2 | CODE | |
| LOW | remove_anything_3d.py | 14 | CODE | |
| LOW | remove_anything_3d.py | 14 | CODE | |
| LOW | remove_anything_3d.py | 19 | CODE | |
| LOW | ostrack.py | 1 | CODE | |
| LOW | ostrack.py | 12 | CODE | |
| LOW | fill_anything.py | 1 | CODE | |
| LOW | fill_anything.py | 8 | CODE | |
| LOW | fill_anything.py | 8 | CODE | |
| LOW | fill_anything.py | 8 | CODE | |
| LOW | replace_anything.py | 1 | CODE | |
| LOW | replace_anything.py | 8 | CODE | |
| LOW | replace_anything.py | 8 | CODE | |
| LOW | replace_anything.py | 8 | CODE | |
| LOW | lama_inpaint.py | 8 | CODE | |
| LOW | remove_anything_video.py | 6 | CODE | |
| LOW | remove_anything_video.py | 6 | CODE | |
| LOW | sam_segment.py | 6 | CODE | |
| LOW | sam_segment.py | 6 | CODE | |
| LOW | nerf/load_blender.py | 6 | CODE | |
| LOW | nerf/load_LINEMOD.py | 6 | CODE | |
| LOW | nerf/run_nerf.py | 1 | CODE | |
| LOW | nerf/run_nerf.py | 4 | CODE | |
| LOW | nerf/run_nerf.py | 8 | CODE | |
| LOW | nerf/run_nerf.py | 12 | CODE | |
| LOW | nerf/run_nerf.py | 14 | CODE | |
| LOW | nerf/load_llff.py | 21 | CODE | |
| LOW | app/__init__.py | 2 | CODE | |
| LOW | app/__init__.py | 3 | CODE | |
| LOW | app/app.py | 9 | CODE | |
| LOW | app/app.py | 15 | CODE | |
| LOW | app/app.py | 16 | CODE | |
| LOW | app/app.py | 16 | CODE | |
| LOW | app/app.py | 16 | CODE | |
| LOW | app/app.py | 16 | CODE | |
| LOW | app/.ipynb_checkpoints/app-checkpoint.py | 11 | CODE | |
| LOW | app/.ipynb_checkpoints/app-checkpoint.py | 12 | CODE | |
| LOW | app/.ipynb_checkpoints/app-checkpoint.py | 13 | CODE | |
| LOW | app/.ipynb_checkpoints/app-checkpoint.py | 14 | CODE | |
| LOW | app/.ipynb_checkpoints/app-checkpoint.py | 14 | CODE | |
| LOW | utils/frames2video copy.py | 7 | CODE | |
| LOW | utils/video2frames.py | 2 | CODE | |
| LOW | utils/video2frames.py | 4 | CODE | |
| LOW | utils/video2frames.py | 6 | CODE | |
| LOW | utils/video2frames.py | 7 | CODE | |
| LOW | utils/visualize_bbox.py | 3 | CODE | |
| LOW | utils/visualize_bbox.py | 4 | CODE | |
| LOW | utils/mask_processing.py | 2 | CODE | |
| LOW | utils/mask_processing.py | 3 | CODE | |
| LOW | utils/__init__.py | 1 | CODE | |
| LOW | utils/utils.py | 4 | CODE | |
| LOW | utils/utils.py | 4 | CODE | |
| LOW | utils/visualize_mask_on_img.py | 1 | CODE | |
| LOW | utils/visualize_mask_on_img.py | 5 | CODE | |
| LOW | utils/visualize_mask_on_img.py | 8 | CODE | |
| LOW | utils/visualize_mask_on_img.py | 8 | CODE | |
| LOW | utils/visualize_mask_on_img.py | 8 | CODE | |
| LOW | lama/saicinpainting/training/trainers/base.py | 10 | CODE | |
| LOW | …/saicinpainting/training/modules/depthwise_sep_conv.py | 1 | CODE | |
| LOW | lama/saicinpainting/training/modules/ffc.py | 13 | CODE | |
| 224 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | sttn_video_inpaint.py | 73 | def inpaint_video_with_builded_sttn( | CODE |
| LOW | lama_inpaint.py | 114 | def inpaint_img_with_builded_lama( | CODE |
| LOW | lama/saicinpainting/utils.py | 20 | def check_and_warn_input_range(tensor, min_value, max_value, name): | CODE |
| LOW | lama/saicinpainting/utils.py | 107 | def register_debug_signal_handlers(sig=signal.SIGUSR1, handler=print_traceback_handler): | CODE |
| LOW | lama/saicinpainting/utils.py | 112 | def handle_deterministic_config(config): | CODE |
| LOW | lama/saicinpainting/utils.py | 168 | def handle_ddp_parent_process(): | CODE |
| LOW | …a/saicinpainting/training/losses/distance_weighting.py | 117 | def make_mask_distance_weighter(kind='none', **kwargs): | CODE |
| LOW | lama/saicinpainting/training/visualizers/base.py | 23 | def visualize_mask_and_images(images_dict: Dict[str, np.ndarray], keys: List[str], | CODE |
| LOW | lama/saicinpainting/training/visualizers/base.py | 61 | def visualize_mask_and_images_batch(batch: Dict[str, torch.Tensor], keys: List[str], max_items=10, | CODE |
| LOW | lama/saicinpainting/training/trainers/default.py | 17 | def make_constant_area_crop_batch(batch, **kwargs): | CODE |
| LOW | lama/saicinpainting/training/modules/fake_fakes.py | 34 | def _fill_masks_with_gradient(self, masks): | CODE |
| LOW | lama/saicinpainting/training/data/datasets.py | 206 | def make_default_train_dataloader(indir, kind='default', out_size=512, mask_gen_kwargs=None, transform_variant='default' | CODE |
| LOW | lama/saicinpainting/training/data/datasets.py | 283 | def make_default_val_dataloader(*args, dataloader_kwargs=None, **kwargs): | CODE |
| LOW | lama/saicinpainting/training/data/datasets.py | 292 | def make_constant_area_crop_params(img_height, img_width, min_size=128, max_size=512, area=256*256, round_to_mod=16): | CODE |
| LOW | lama/saicinpainting/training/data/masks.py | 22 | def make_random_irregular_mask(shape, max_angle=4, max_len=60, max_width=20, min_times=0, max_times=10, | CODE |
| LOW | lama/saicinpainting/training/data/masks.py | 72 | def make_random_rectangle_mask(shape, margin=10, bbox_min_size=30, bbox_max_size=100, min_times=0, max_times=3): | CODE |
| LOW | lama/saicinpainting/training/data/masks.py | 118 | def make_random_superres_mask(shape, min_step=2, max_step=4, min_width=1, max_width=3): | CODE |
| LOW | lama/saicinpainting/training/data/aug.py | 53 | def get_transform_init_args_names(self): | CODE |
| LOW | lama/saicinpainting/training/data/aug.py | 83 | def get_transform_init_args_names(self): | CODE |
| LOW | lama/saicinpainting/evaluation/losses/base_loss.py | 121 | def fid_calculate_activation_statistics(act): | CODE |
| LOW | lama/saicinpainting/evaluation/losses/base_loss.py | 127 | def calculate_frechet_distance(activations_pred, activations_target, eps=1e-6): | CODE |
| LOW | lama/saicinpainting/evaluation/losses/base_loss.py | 263 | def distribute_values_to_classes(target_class_freq_by_image_mask, values, idx2name): | CODE |
| LOW | lama/saicinpainting/evaluation/losses/base_loss.py | 513 | def distribute_fid_to_classes(self, class_freq, activations_pred, activations_target): | CODE |
| LOW | lama/saicinpainting/evaluation/losses/fid/fid_score.py | 160 | def calculate_frechet_distance(mu1, sigma1, mu2, sigma2, eps=1e-6): | CODE |
| LOW | lama/saicinpainting/evaluation/losses/fid/fid_score.py | 218 | def calculate_activation_statistics(files, model, batch_size=50, | CODE |
| LOW | lama/saicinpainting/evaluation/losses/fid/fid_score.py | 243 | def _compute_statistics_of_path(path, model, batch_size, dims, cuda): | CODE |
| LOW | lama/saicinpainting/evaluation/losses/fid/fid_score.py | 257 | def _compute_statistics_of_images(images, model, batch_size, dims, cuda, keep_size=False): | CODE |
| LOW | lama/saicinpainting/evaluation/losses/fid/fid_score.py | 268 | def calculate_fid_given_paths(paths, batch_size, cuda, dims): | CODE |
| LOW | lama/saicinpainting/evaluation/losses/fid/fid_score.py | 289 | def calculate_fid_given_images(images, batch_size, cuda, dims, use_globals=False, keep_size=False): | CODE |
| LOW | lama/saicinpainting/evaluation/masks/mask.py | 250 | def _check_masks_intersection(self, aug_mask, total_mask_area, prev_masks): | CODE |
| LOW | lama/saicinpainting/evaluation/masks/mask.py | 260 | def _check_foreground_intersection(self, aug_mask, foreground): | CODE |
| LOW | lama/saicinpainting/evaluation/masks/mask.py | 410 | def propose_random_square_crop(mask, min_overlap=0.5): | CODE |
| LOW | …icinpainting/evaluation/masks/countless/countless3d.py | 209 | def dynamic_countless_generalized(data, factor): | CODE |
| LOW | …icinpainting/evaluation/masks/countless/countless3d.py | 261 | def downsample_with_averaging(array): | CODE |
| LOW | …icinpainting/evaluation/masks/countless/countless3d.py | 282 | def downsample_with_max_pooling(array): | CODE |
| LOW | …icinpainting/evaluation/masks/countless/countless2d.py | 376 | def downsample_with_averaging(array): | CODE |
| LOW | …icinpainting/evaluation/masks/countless/countless2d.py | 401 | def downsample_with_max_pooling(array): | CODE |
| LOW | lama/bin/analyze_errors.py | 85 | def extract_overlapping_masks(mask_fnames, cur_i, fake_scores_table, max_overlaps_n=2): | CODE |
| LOW | lama/bin/sample_from_dataset.py | 25 | def save_masked_img_for_sidebyside(item, out_file): | CODE |
| LOW | lama/bin/saicinpainting/utils.py | 20 | def check_and_warn_input_range(tensor, min_value, max_value, name): | CODE |
| LOW | lama/bin/saicinpainting/utils.py | 107 | def register_debug_signal_handlers(sig=signal.SIGUSR1, handler=print_traceback_handler): | CODE |
| LOW | lama/bin/saicinpainting/utils.py | 112 | def handle_deterministic_config(config): | CODE |
| LOW | lama/bin/saicinpainting/utils.py | 168 | def handle_ddp_parent_process(): | CODE |
| LOW | …n/saicinpainting/training/losses/distance_weighting.py | 117 | def make_mask_distance_weighter(kind='none', **kwargs): | CODE |
| LOW | lama/bin/saicinpainting/training/visualizers/base.py | 23 | def visualize_mask_and_images(images_dict: Dict[str, np.ndarray], keys: List[str], | CODE |
| LOW | lama/bin/saicinpainting/training/visualizers/base.py | 61 | def visualize_mask_and_images_batch(batch: Dict[str, torch.Tensor], keys: List[str], max_items=10, | CODE |
| LOW | lama/bin/saicinpainting/training/trainers/default.py | 17 | def make_constant_area_crop_batch(batch, **kwargs): | CODE |
| LOW | lama/bin/saicinpainting/training/modules/fake_fakes.py | 34 | def _fill_masks_with_gradient(self, masks): | CODE |
| LOW | lama/bin/saicinpainting/training/data/datasets.py | 206 | def make_default_train_dataloader(indir, kind='default', out_size=512, mask_gen_kwargs=None, transform_variant='default' | CODE |
| LOW | lama/bin/saicinpainting/training/data/datasets.py | 283 | def make_default_val_dataloader(*args, dataloader_kwargs=None, **kwargs): | CODE |
| LOW | lama/bin/saicinpainting/training/data/datasets.py | 292 | def make_constant_area_crop_params(img_height, img_width, min_size=128, max_size=512, area=256*256, round_to_mod=16): | CODE |
| LOW | lama/bin/saicinpainting/training/data/masks.py | 22 | def make_random_irregular_mask(shape, max_angle=4, max_len=60, max_width=20, min_times=0, max_times=10, | CODE |
| LOW | lama/bin/saicinpainting/training/data/masks.py | 72 | def make_random_rectangle_mask(shape, margin=10, bbox_min_size=30, bbox_max_size=100, min_times=0, max_times=3): | CODE |
| LOW | lama/bin/saicinpainting/training/data/masks.py | 118 | def make_random_superres_mask(shape, min_step=2, max_step=4, min_width=1, max_width=3): | CODE |
| LOW | lama/bin/saicinpainting/training/data/aug.py | 53 | def get_transform_init_args_names(self): | CODE |
| LOW | lama/bin/saicinpainting/training/data/aug.py | 83 | def get_transform_init_args_names(self): | CODE |
| LOW | lama/bin/saicinpainting/evaluation/losses/base_loss.py | 121 | def fid_calculate_activation_statistics(act): | CODE |
| LOW | lama/bin/saicinpainting/evaluation/losses/base_loss.py | 127 | def calculate_frechet_distance(activations_pred, activations_target, eps=1e-6): | CODE |
| LOW | lama/bin/saicinpainting/evaluation/losses/base_loss.py | 263 | def distribute_values_to_classes(target_class_freq_by_image_mask, values, idx2name): | CODE |
| LOW | lama/bin/saicinpainting/evaluation/losses/base_loss.py | 513 | def distribute_fid_to_classes(self, class_freq, activations_pred, activations_target): | CODE |
| 38 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | nerf/run_nerf.py | 69 | CODE | |
| LOW | nerf/run_nerf.py | 308 | CODE | |
| LOW | lama/saicinpainting/training/losses/style_loss.py | 155 | CODE | |
| LOW | lama/saicinpainting/training/losses/adversarial.py | 82 | CODE | |
| LOW | lama/saicinpainting/training/losses/perceptual.py | 113 | CODE | |
| LOW | lama/saicinpainting/training/trainers/default.py | 27 | CODE | |
| LOW | lama/saicinpainting/training/modules/multiscale.py | 45 | CODE | |
| LOW | lama/saicinpainting/training/modules/multiscale.py | 96 | CODE | |
| LOW | …/saicinpainting/training/modules/squeeze_excitation.py | 20 | CODE | |
| LOW | …a/saicinpainting/training/modules/multidilated_conv.py | 7 | CODE | |
| LOW | …/saicinpainting/training/modules/depthwise_sep_conv.py | 17 | CODE | |
| LOW | lama/saicinpainting/training/modules/ffc.py | 51 | CODE | |
| LOW | lama/saicinpainting/training/modules/ffc.py | 163 | CODE | |
| LOW | lama/saicinpainting/training/modules/ffc.py | 168 | CODE | |
| LOW | lama/saicinpainting/training/modules/ffc.py | 230 | CODE | |
| LOW | lama/saicinpainting/training/modules/ffc.py | 306 | CODE | |
| LOW | lama/saicinpainting/training/modules/fake_fakes.py | 32 | CODE | |
| LOW | lama/saicinpainting/training/modules/pix2pixhd.py | 90 | CODE | |
| LOW | lama/saicinpainting/training/modules/pix2pixhd.py | 152 | CODE | |
| LOW | lama/saicinpainting/training/modules/pix2pixhd.py | 175 | CODE | |
| LOW | lama/saicinpainting/training/modules/pix2pixhd.py | 179 | CODE | |
| LOW | lama/saicinpainting/training/modules/pix2pixhd.py | 240 | CODE | |
| LOW | lama/saicinpainting/training/modules/pix2pixhd.py | 342 | CODE | |
| LOW | lama/saicinpainting/training/data/datasets.py | 90 | CODE | |
| LOW | lama/saicinpainting/training/data/masks.py | 210 | CODE | |
| LOW | lama/saicinpainting/training/data/masks.py | 253 | CODE | |
| LOW | lama/saicinpainting/training/data/aug.py | 17 | CODE | |
| LOW | lama/saicinpainting/evaluation/losses/lpips.py | 252 | CODE | |
| LOW | lama/saicinpainting/evaluation/losses/lpips.py | 764 | CODE | |
| LOW | lama/saicinpainting/evaluation/losses/lpips.py | 805 | CODE | |
| LOW | lama/saicinpainting/evaluation/losses/lpips.py | 846 | CODE | |
| LOW | lama/saicinpainting/evaluation/losses/lpips.py | 891 | CODE | |
| LOW | lama/saicinpainting/evaluation/masks/mask.py | 141 | CODE | |
| LOW | lama/bin/saicinpainting/training/losses/style_loss.py | 155 | CODE | |
| LOW | lama/bin/saicinpainting/training/losses/adversarial.py | 82 | CODE | |
| LOW | lama/bin/saicinpainting/training/losses/perceptual.py | 113 | CODE | |
| LOW | lama/bin/saicinpainting/training/trainers/default.py | 27 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/multiscale.py | 45 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/multiscale.py | 96 | CODE | |
| LOW | …/saicinpainting/training/modules/squeeze_excitation.py | 20 | CODE | |
| LOW | …n/saicinpainting/training/modules/multidilated_conv.py | 7 | CODE | |
| LOW | …/saicinpainting/training/modules/depthwise_sep_conv.py | 17 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/ffc.py | 51 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/ffc.py | 163 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/ffc.py | 168 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/ffc.py | 230 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/ffc.py | 306 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/fake_fakes.py | 32 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/pix2pixhd.py | 90 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/pix2pixhd.py | 152 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/pix2pixhd.py | 175 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/pix2pixhd.py | 179 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/pix2pixhd.py | 240 | CODE | |
| LOW | lama/bin/saicinpainting/training/modules/pix2pixhd.py | 342 | CODE | |
| LOW | lama/bin/saicinpainting/training/data/datasets.py | 90 | CODE | |
| LOW | lama/bin/saicinpainting/training/data/masks.py | 210 | CODE | |
| LOW | lama/bin/saicinpainting/training/data/masks.py | 253 | CODE | |
| LOW | lama/bin/saicinpainting/training/data/aug.py | 17 | CODE | |
| LOW | lama/bin/saicinpainting/evaluation/losses/lpips.py | 252 | CODE | |
| LOW | lama/bin/saicinpainting/evaluation/losses/lpips.py | 764 | CODE | |
| 27 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | …icinpainting/evaluation/masks/countless/countless3d.py | 0 | downsample x by factor using striding. @return: the downsampled array, of the same type as x. | STRING |
| HIGH | …icinpainting/evaluation/masks/countless/countless2d.py | 0 | downsample x by factor using striding. @return: the downsampled array, of the same type as x. | STRING |
| HIGH | …icinpainting/evaluation/masks/countless/countless3d.py | 0 | downsample x by factor using striding. @return: the downsampled array, of the same type as x. | STRING |
| HIGH | …icinpainting/evaluation/masks/countless/countless2d.py | 0 | downsample x by factor using striding. @return: the downsampled array, of the same type as x. | STRING |
| HIGH | lama/bin/models/ade20k/mobilenet.py | 0 | constructs a resnet-18 model. args: pretrained (bool): if true, returns a model pre-trained on imagenet | STRING |
| HIGH | lama/models/ade20k/mobilenet.py | 0 | constructs a resnet-18 model. args: pretrained (bool): if true, returns a model pre-trained on imagenet | STRING |
| HIGH | lama/bin/models/ade20k/resnet.py | 0 | constructs a resnet-18 model. args: pretrained (bool): if true, returns a model pre-trained on imagenet | STRING |
| HIGH | lama/models/ade20k/resnet.py | 0 | constructs a resnet-18 model. args: pretrained (bool): if true, returns a model pre-trained on imagenet | STRING |
| HIGH | lama/bin/models/ade20k/resnet.py | 0 | modified from https://github.com/csailvision/semantic-segmentation-pytorch | STRING |
| HIGH | lama/bin/models/ade20k/utils.py | 0 | modified from https://github.com/csailvision/semantic-segmentation-pytorch | STRING |
| HIGH | lama/bin/models/ade20k/base.py | 0 | modified from https://github.com/csailvision/semantic-segmentation-pytorch | STRING |
| HIGH | lama/models/ade20k/resnet.py | 0 | modified from https://github.com/csailvision/semantic-segmentation-pytorch | STRING |
| HIGH | lama/models/ade20k/utils.py | 0 | modified from https://github.com/csailvision/semantic-segmentation-pytorch | STRING |
| HIGH | lama/models/ade20k/base.py | 0 | modified from https://github.com/csailvision/semantic-segmentation-pytorch | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | nerf/run_nerf.py | 422 | CODE | |
| LOW | lama/saicinpainting/utils.py | 121 | CODE | |
| LOW | …a/saicinpainting/training/losses/distance_weighting.py | 52 | CODE | |
| LOW | lama/saicinpainting/training/trainers/base.py | 224 | CODE | |
| LOW | …a/saicinpainting/training/modules/multidilated_conv.py | 7 | CODE | |
| LOW | lama/saicinpainting/training/data/datasets.py | 101 | CODE | |
| LOW | lama/saicinpainting/training/data/datasets.py | 249 | CODE | |
| LOW | lama/saicinpainting/training/data/masks.py | 22 | CODE | |
| LOW | lama/saicinpainting/evaluation/evaluator.py | 67 | CODE | |
| LOW | lama/saicinpainting/evaluation/losses/lpips.py | 252 | CODE | |
| LOW | lama/saicinpainting/evaluation/losses/lpips.py | 850 | CODE | |
| LOW | …icinpainting/evaluation/masks/countless/countless2d.py | 310 | CODE | |
| LOW | …icinpainting/evaluation/masks/countless/countless2d.py | 347 | CODE | |
| LOW | lama/bin/analyze_errors.py | 103 | CODE | |
| LOW | lama/bin/predict_inner_features.py | 39 | CODE | |
| LOW | lama/bin/predict.py | 39 | CODE | |
| LOW | lama/bin/make_checkpoint.py | 16 | CODE | |
| LOW | lama/bin/report_from_tb.py | 37 | CODE | |
| LOW | lama/bin/gen_mask_dataset.py | 27 | CODE | |
| LOW | lama/bin/gen_mask_dataset_hydra.py | 29 | CODE | |
| LOW | lama/bin/saicinpainting/utils.py | 121 | CODE | |
| LOW | …n/saicinpainting/training/losses/distance_weighting.py | 52 | CODE | |
| LOW | lama/bin/saicinpainting/training/trainers/base.py | 224 | CODE | |
| LOW | …n/saicinpainting/training/modules/multidilated_conv.py | 7 | CODE | |
| LOW | lama/bin/saicinpainting/training/data/datasets.py | 101 | CODE | |
| LOW | lama/bin/saicinpainting/training/data/datasets.py | 249 | CODE | |
| LOW | lama/bin/saicinpainting/training/data/masks.py | 22 | CODE | |
| LOW | lama/bin/saicinpainting/evaluation/evaluator.py | 67 | CODE | |
| LOW | lama/bin/saicinpainting/evaluation/losses/lpips.py | 252 | CODE | |
| LOW | lama/bin/saicinpainting/evaluation/losses/lpips.py | 850 | CODE | |
| LOW | …icinpainting/evaluation/masks/countless/countless2d.py | 310 | CODE | |
| LOW | …icinpainting/evaluation/masks/countless/countless2d.py | 347 | CODE | |
| LOW | lama/bin/models/ade20k/mobilenet.py | 129 | CODE | |
| LOW | lama/bin/models/ade20k/base.py | 68 | CODE | |
| LOW | …in/models/ade20k/segm_lib/nn/parallel/data_parallel.py | 27 | CODE | |
| LOW | …in/models/ade20k/segm_lib/nn/parallel/data_parallel.py | 32 | CODE | |
| LOW | lama/bin/models/ade20k/segm_lib/utils/th.py | 18 | CODE | |
| LOW | …ma/bin/models/ade20k/segm_lib/utils/data/dataloader.py | 104 | CODE | |
| LOW | …ma/bin/models/ade20k/segm_lib/utils/data/dataloader.py | 145 | CODE | |
| LOW | lama/bin/paper_runfiles/find_best_checkpoint.py | 16 | CODE | |
| LOW | lama/models/ade20k/mobilenet.py | 129 | CODE | |
| LOW | lama/models/ade20k/base.py | 68 | CODE | |
| LOW | …ma/models/ade20k/segm_lib/nn/parallel/data_parallel.py | 27 | CODE | |
| LOW | …ma/models/ade20k/segm_lib/nn/parallel/data_parallel.py | 32 | CODE | |
| LOW | lama/models/ade20k/segm_lib/utils/th.py | 18 | CODE | |
| LOW | lama/models/ade20k/segm_lib/utils/data/dataloader.py | 104 | CODE | |
| LOW | lama/models/ade20k/segm_lib/utils/data/dataloader.py | 145 | CODE | |
| LOW | segment_anything/segment_anything/utils/amg.py | 44 | CODE | |
| LOW | segment_anything/segment_anything/utils/amg.py | 59 | CODE | |
| LOW | sttn/test.py | 89 | CODE | |
| LOW | sttn/model/sttn.py | 25 | CODE | |
| LOW | sttn/model/sttn.py | 31 | CODE | |
| LOW | sttn/model/vis.py | 25 | CODE | |
| LOW | sttn/model/vis.py | 31 | CODE | |
| LOW | pytracking/lib/test/tracker/basetracker.py | 80 | CODE | |
| LOW | pytracking/lib/test/tracker/ostrack.py | 73 | CODE | |
| LOW | pytracking/lib/test/evaluation/data.py | 36 | CODE | |
| LOW | pytracking/lib/test/evaluation/data.py | 55 | CODE | |
| LOW | pytracking/lib/config/ostrack/config.py | 123 | CODE | |
| LOW | pytracking/lib/utils/ce_utils.py | 15 | CODE | |
| 4 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | lama/bin/models/ade20k/segm_lib/nn/modules/unittest.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| MEDIUM | lama/bin/models/ade20k/segm_lib/nn/modules/batchnorm.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| MEDIUM | lama/bin/models/ade20k/segm_lib/nn/modules/comm.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| MEDIUM | lama/bin/models/ade20k/segm_lib/nn/modules/replicate.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| MEDIUM | lama/bin/models/ade20k/segm_lib/nn/modules/__init__.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| MEDIUM | …de20k/segm_lib/nn/modules/tests/test_sync_batchnorm.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| MEDIUM | …0k/segm_lib/nn/modules/tests/test_numeric_batchnorm.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| MEDIUM | lama/models/ade20k/segm_lib/nn/modules/unittest.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| MEDIUM | lama/models/ade20k/segm_lib/nn/modules/batchnorm.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| MEDIUM | lama/models/ade20k/segm_lib/nn/modules/comm.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| MEDIUM | lama/models/ade20k/segm_lib/nn/modules/replicate.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| MEDIUM | lama/models/ade20k/segm_lib/nn/modules/__init__.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| MEDIUM | …de20k/segm_lib/nn/modules/tests/test_sync_batchnorm.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| MEDIUM | …0k/segm_lib/nn/modules/tests/test_numeric_batchnorm.py | 7 | # This file is part of Synchronized-BatchNorm-PyTorch. | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | ostrack.py | 81 | COMMENT | |
| LOW | ostrack.py | 101 | COMMENT | |
| LOW | …icinpainting/evaluation/masks/countless/countless2d.py | 501 | # Function MPx/sec MB/sec Sec | COMMENT |
| LOW | …icinpainting/evaluation/masks/countless/countless2d.py | 501 | # Function MPx/sec MB/sec Sec | COMMENT |
| LOW | lama/bin/models/ade20k/segm_lib/nn/modules/__init__.py | 1 | # -*- coding: utf-8 -*- | COMMENT |
| LOW | lama/bin/paper_runfiles/blur_tests.sh | 1 | ##!/usr/bin/env bash | COMMENT |
| LOW | lama/bin/paper_runfiles/blur_tests.sh | 21 | # for conf in segm_256 segm_512 | COMMENT |
| LOW | lama/bin/debug/analyze_overlapping_masks.sh | 1 | #!/bin/bash | COMMENT |
| LOW | lama/models/ade20k/segm_lib/nn/modules/__init__.py | 1 | # -*- coding: utf-8 -*- | COMMENT |
| LOW | lama/configs/training/data/abl-04-256-mh-dist.yaml | 41 | num_workers: ${data.num_workers} | COMMENT |
| LOW | lama/configs/training/data/abl-04-256-mh-dist.yaml | 61 | # dataloader_kwargs: | COMMENT |
| LOW | lama/configs/training/data/abl-04-256-mh-dist.yaml | 81 | # img_suffix: .png | COMMENT |
| LOW | lama/configs/training/data/abl-04-256-mh-dist-web.yaml | 41 | batch_size: ${data.val_batch_size} | COMMENT |
| LOW | lama/configs/training/data/abl-04-256-mh-dist-web.yaml | 61 | # indir: ${location.data_root_dir}/final_extra_val/random_thick_256 | COMMENT |
| LOW | lama/configs/training/data/abl-04-256-mh-dist-web.yaml | 81 | # random_thick_512: | COMMENT |
| LOW | lama/configs/training/data/abl-02-thin-bb.yaml | 41 | COMMENT | |
| LOW | lama/configs/training/data/abl-02-thin-bb.yaml | 61 | # dataloader_kwargs: | COMMENT |
| LOW | lama/configs/training/data/abl-02-thin-bb.yaml | 81 | # img_suffix: .png | COMMENT |
| LOW | segment_anything/segment_anything/utils/__init__.py | 1 | # Copyright (c) Meta Platforms, Inc. and affiliates. | COMMENT |
| LOW | sttn/core/spectral_norm.py | 41 | # broadcast from the parallelized module to each module replica, | COMMENT |
| LOW | sttn/core/spectral_norm.py | 141 | return fn | COMMENT |
| LOW | pytracking/lib/models/ostrack/vit.py | 141 | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | lama/bin/gen_outpainting_dataset.py | 73 | except Exception as ex: | CODE |
| MEDIUM | lama/bin/gen_outpainting_dataset.py | 34 | def main(args): | CODE |
| LOW | lama/bin/predict_inner_features.py | 113 | except Exception as ex: | CODE |
| LOW | lama/bin/predict.py | 97 | except Exception as ex: | CODE |
| LOW | lama/bin/train.py | 66 | except Exception as ex: | CODE |
| LOW | lama/bin/gen_mask_dataset.py | 96 | except Exception as ex: | CODE |
| LOW | lama/bin/gen_mask_dataset_hydra.py | 99 | except Exception as ex: | CODE |
| LOW | lama/bin/side_by_side.py | 57 | except Exception as ex: | CODE |
| LOW | …ma/bin/models/ade20k/segm_lib/utils/data/dataloader.py | 61 | except Exception: | CODE |
| LOW | …ma/bin/models/ade20k/segm_lib/utils/data/dataloader.py | 74 | except Exception: | CODE |
| LOW | …ma/bin/models/ade20k/segm_lib/utils/data/dataloader.py | 87 | except Exception: | CODE |
| LOW | lama/models/ade20k/segm_lib/utils/data/dataloader.py | 61 | except Exception: | CODE |
| LOW | lama/models/ade20k/segm_lib/utils/data/dataloader.py | 74 | except Exception: | CODE |
| LOW | lama/models/ade20k/segm_lib/utils/data/dataloader.py | 87 | except Exception: | CODE |
| LOW | pytracking/lib/test/utils/load_text.py | 27 | except Exception as e: | CODE |
| LOW | pytracking/lib/utils/misc.py | 263 | except Exception: | CODE |
| LOW | pytracking/lib/train/data/image_loader.py | 38 | except Exception as e: | CODE |
| LOW | pytracking/lib/train/data/image_loader.py | 51 | except Exception as e: | CODE |
| LOW | pytracking/lib/train/data/image_loader.py | 67 | except Exception as e: | CODE |
| LOW | pytracking/lib/train/data/image_loader.py | 77 | except Exception as e: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | lama/bin/models/ade20k/mobilenet.py | 14 | __all__ = ['mobilenetv2'] | CODE |
| LOW | lama/bin/models/ade20k/resnet.py | 10 | __all__ = ['ResNet', 'resnet50'] | CODE |
| LOW | …in/models/ade20k/segm_lib/nn/parallel/data_parallel.py | 10 | __all__ = ['UserScatteredDataParallel', 'user_scattered_collate', 'async_copy_to'] | CODE |
| LOW | lama/bin/models/ade20k/segm_lib/nn/modules/batchnorm.py | 21 | __all__ = ['SynchronizedBatchNorm1d', 'SynchronizedBatchNorm2d', 'SynchronizedBatchNorm3d'] | CODE |
| LOW | lama/bin/models/ade20k/segm_lib/nn/modules/comm.py | 15 | __all__ = ['FutureResult', 'SlavePipe', 'SyncMaster'] | CODE |
| LOW | lama/bin/models/ade20k/segm_lib/nn/modules/replicate.py | 15 | __all__ = [ | CODE |
| LOW | lama/bin/models/ade20k/segm_lib/utils/th.py | 6 | __all__ = ['as_variable', 'as_numpy', 'mark_volatile'] | CODE |
| LOW | lama/models/ade20k/mobilenet.py | 14 | __all__ = ['mobilenetv2'] | CODE |
| LOW | lama/models/ade20k/resnet.py | 10 | __all__ = ['ResNet', 'resnet50'] | CODE |
| LOW | …ma/models/ade20k/segm_lib/nn/parallel/data_parallel.py | 10 | __all__ = ['UserScatteredDataParallel', 'user_scattered_collate', 'async_copy_to'] | CODE |
| LOW | lama/models/ade20k/segm_lib/nn/modules/batchnorm.py | 21 | __all__ = ['SynchronizedBatchNorm1d', 'SynchronizedBatchNorm2d', 'SynchronizedBatchNorm3d'] | CODE |
| LOW | lama/models/ade20k/segm_lib/nn/modules/comm.py | 15 | __all__ = ['FutureResult', 'SlavePipe', 'SyncMaster'] | CODE |
| LOW | lama/models/ade20k/segm_lib/nn/modules/replicate.py | 15 | __all__ = [ | CODE |
| LOW | lama/models/ade20k/segm_lib/utils/th.py | 6 | __all__ = ['as_variable', 'as_numpy', 'mark_volatile'] | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| CRITICAL | segment_anything/segment_anything/utils/onnx.py | 73 | ) * self.model.prompt_encoder.no_mask_embed.weight.reshape(1, -1, 1, 1) | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | lama/fetch_data/sampler.py | 23 | # -------------------------------- | COMMENT |
| MEDIUM | …ent_anything/segment_anything/modeling/tiny_vit_sam.py | 1 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | …ent_anything/segment_anything/modeling/tiny_vit_sam.py | 8 | # -------------------------------------------------------- | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | segment_anything/segment_anything/utils/amg.py | 240 | # Check if boxes has a channel dimension | COMMENT |
| LOW | segment_anything/segment_anything/utils/amg.py | 249 | # Check if points has a channel dimension | COMMENT |
| LOW | pytracking/lib/test/evaluation/tracker.py | 237 | # Display the resulting frame | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …icinpainting/evaluation/masks/countless/countless2d.py | 291 | # image. if so it's fine, just return. | COMMENT |
| LOW | …icinpainting/evaluation/masks/countless/countless2d.py | 291 | # image. if so it's fine, just return. | COMMENT |