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values | repo_created_at timestamp[s]date 2012-07-24 23:12:50 2025-06-16 08:07:28 ⌀ | repo_updated_at timestamp[s]date 2026-02-23 15:23:15 2026-05-03 18:52:12 ⌀ | repo_topics listlengths 0 13 ⌀ | repo_languages unknown | is_fork bool 1
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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/models/materialize.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:16.765151 | """
materialize.py
Factory class for initializing Vision Backbones, LLM Backbones, and VLMs from a set registry; provides and exports
individual functions for clear control flow.
"""
from typing import Optional, Tuple
from transformers import PreTrainedTokenizerBase
from prismatic.models.backbones.llm import LLaMa2... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/models/load.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:16.767268 | """
load.py
Entry point for loading pretrained VLMs for inference; exposes functions for listing available models (with canonical
IDs, mappings to paper experiments, and short descriptions), as well as for loading models (from disk or HF Hub).
"""
import json
import os
from pathlib import Path
from typing import List... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/models/backbones/vision/siglip_vit.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:16.768151 | """
siglip_vit.py
"""
from prismatic.models.backbones.vision.base_vision import TimmViTBackbone
# Registry =>> Supported SigLIP Vision Backbones (from TIMM) =>> Note:: Using SigLIP w/ Patch = 14 (but SO400M Arch)
SIGLIP_VISION_BACKBONES = {
"siglip-vit-b16-224px": "vit_base_patch16_siglip_224",
"siglip-vit-b1... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/models/registry.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:16.795999 | """
registry.py
Exhaustive list of pretrained VLMs (with full descriptions / links to corresponding names and sections of paper).
"""
# === Pretrained Model Registry ===
# fmt: off
MODEL_REGISTRY = {
# === LLaVa v1.5 Reproductions ===
"reproduction-llava-v15+7b": {
"model_id": "reproduction-llava-v15+... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/models/vlms/base_vlm.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:16.846804 | """
base_vlm.py
Abstract class definition of a Vision-Language Model (VLM), with full annotations of class methods, utility functions,
and initialization logic. This is mostly to future-proof the codebase; while all our experiments instantiate
from PrismaticVLM, theoretically, this base class should be general enough ... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/preprocessing/materialize.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:17.740988 | """
materialize.py
Factory class for initializing pretraining datasets on a per-VLM basis; provides and exports individual functions for
clear control flow.
"""
from typing import Tuple, Type
from torch.utils.data import Dataset
from transformers import PreTrainedTokenizerBase
from prismatic.conf import DatasetConf... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/overwatch/overwatch.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:17.765977 | """
overwatch.py
Utility class for creating a centralized/standardized logger (built on Rich) and accelerate handler.
"""
import logging
import logging.config
import os
from contextlib import nullcontext
from logging import LoggerAdapter
from typing import Any, Callable, ClassVar, Dict, MutableMapping, Tuple, Union
... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/models/vlms/prismatic.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:17.796354 | """
prismatic.py
PyTorch Module defining a PrismaticVLM, our general interface for defining the various different VLMs in our work.
Notes:
- For now, we don't subclass `transformers.PretrainedModel` (or CausalLM). Instead, we assume a very limited subset
of the {Model}ForCausalLM API that enables dispatch t... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/preprocessing/datasets/datasets.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:17.874916 | """
datasets.py
PyTorch Dataset Definitions for Prismatic models; supports processing for both the `align` and `finetune` stages, with
utilities for formatting conversations during the `finetune` stage subject to the given LLM backbone's expected
formatting (e.g., SYS_PROMPT + USER: ... ASSISTANT: ... for Vicuña v1.5 ... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/preprocessing/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:17.876004 | from .download import convert_to_jpg, download_extract
from .materialize import get_dataset_and_collator
|
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/preprocessing/download.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:17.877485 | """
download.py
Utility functions for downloading and extracting various datasets to (local) disk.
"""
import os
import shutil
from pathlib import Path
from typing import Dict, List, TypedDict
from zipfile import ZipFile
import requests
from PIL import Image
from rich.progress import BarColumn, DownloadColumn, MofNC... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/training/metrics.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:18.636852 | """
metrics.py
Utility classes defining a Metrics container and multiple Trackers to enable model/stage-specific logging to various
endpoints (e.g., JSONL local logs, Weights & Biases).
"""
import time
from collections import deque
from pathlib import Path
from typing import Any, Dict, Optional, Protocol, Tuple, Unio... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/training/strategies/fsdp.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:18.708256 | """
fsdp.py
Core class definition for a strategy implementing Torch native Fully Sharded Data Parallel Training (with support for
fine-grained control over wrapping policies and mixed precision per component).
"""
import math
import shutil
from collections import OrderedDict
from functools import partial
from pathlib... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/training/materialize.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:18.721514 | """
materialize.py
Factory class defining functions for instantiating various Training Strategies, supporting different VLMs, backbones,
and strategy configurations.
"""
from typing import Callable, Optional
import torch
from prismatic.models.vlms import PrismaticVLM
from prismatic.training.strategies import FSDPSt... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/util/nn_utils.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:18.784109 | """
nn_utils.py
Utility functions and PyTorch submodule definitions.
"""
import torch
import torch.nn as nn
# === Definitions for Various Projection Modules, with Signature :: [..., in_dim] --> [..., out_dim] ===
class LinearProjector(nn.Module):
def __init__(self, vision_dim: int, llm_dim: int) -> None:
... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/util/batching_utils.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:18.821805 | """
batching_utils.py
Core definitions of (Distributed) Samplers for VLM finetuning; provides functionality for construction and allocating
"split-modality" batches as described in the LLaVa paper; this makes sure that a given device/batch is either entirely
(vision, language) or (language-only) data, which leads to s... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/util/data_utils.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:18.866806 | """
data_utils.py
General utilities and classes for facilitating data loading and collation.
"""
from dataclasses import dataclass
from typing import Dict, Sequence, Tuple
import torch
from torch.nn.utils.rnn import pad_sequence
# HuggingFace Default / LLaMa-2 IGNORE_INDEX (for labels)
IGNORE_INDEX = -100
@datacl... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/util/torch_utils.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:19.493206 | """
torch_utils.py
General utilities for randomness, mixed precision training, and miscellaneous checks in PyTorch.
Random `set_global_seed` functionality is taken directly from PyTorch-Lighting:
> Ref: https://github.com/PyTorchLightning/pytorch-lightning/blob/master/pytorch_lightning/utilities/seed.py
This is ... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/training/strategies/ddp.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:19.690909 | """
ddp.py
Core class definition for a strategy implementing Torch native Distributed Data Parallel Training; note that on most
GPU hardware and LLM backbones >= 5-7B parameters, DDP training will OOM, which is why we opt for FSDP.
"""
import shutil
from pathlib import Path
from typing import Optional
import torch
f... |
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/training/strategies/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:28.253035 | from .base_strategy import TrainingStrategy
from .ddp import DDPStrategy
from .fsdp import FSDPStrategy
|
TRI-ML/prismatic-vlms | https://github.com/TRI-ML/prismatic-vlms | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | prismatic/training/strategies/base_strategy.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:28.282508 | """
base_strategy.py
Abstract class definition of a (distributed) training strategy, with full annotations of class methods, utility
functions, and initialization logic.
Training Strategies (DDP, FSDP-Grad, FSDP-Full) tend to have a lot of repeated components; this class does a lot of
heavy lifting.
"""
from abc imp... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/config/tools.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:30.403873 | from dataclasses import dataclass
from pathlib import Path
from typing import Type, TypeVar
from dacite import Config, from_dict
from omegaconf import DictConfig, OmegaConf
TYPE_HOOKS = {
Path: Path,
}
T = TypeVar("T")
def get_typed_config(
data_class: Type[T],
cfg: DictConfig,
extra_type_hooks: d... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/config/pretrain.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:30.408941 | from dataclasses import dataclass
from ..dataset.data_module_pretrain import DataModulePretrainCfg
from ..model.model_wrapper_pretrain import ModelWrapperPretrainCfg
from .common import CommonCfg
@dataclass
class StageCfg:
batch_size: int
num_workers: int
@dataclass
class PretrainCfg(CommonCfg):
model_... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/dataset/data_module_pretrain.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:30.410136 | import random
from dataclasses import dataclass
from typing import Callable
import numpy as np
import torch
from lightning.pytorch import LightningDataModule
from torch import Generator
from torch.utils.data import DataLoader, Dataset, IterableDataset
from ..frame_sampler import FrameSamplerCfg
from . import DatasetC... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/config/common.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:30.414169 | from dataclasses import dataclass
from typing import Literal, Type, TypeVar
from omegaconf import DictConfig
from ..dataset import DatasetCfg
from ..flow import FlowPredictorCfg
from ..frame_sampler import FrameSamplerCfg
from ..loss import LossCfg
from ..misc.cropping import CroppingCfg
from ..model.model import Mod... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/dataset/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:30.425463 | from ..frame_sampler import FrameSamplerCfg, get_frame_sampler
try:
from .dataset_co3d import DatasetCO3D, DatasetCO3DCfg
from .dataset_colmap import DatasetCOLMAP, DatasetCOLMAPCfg
from .dataset_images import DatasetImages, DatasetImagesCfg
from .dataset_llff import DatasetLLFF, DatasetLLFFCfg
fro... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/dataset/data_module_overfit.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:30.425990 | from typing import Iterator
from lightning.pytorch import LightningDataModule
from torch.utils.data import DataLoader, IterableDataset
class DummyDataset(IterableDataset):
def __init__(self, limit: int | None = None) -> None:
self.limit = limit
def __iter__(self) -> Iterator:
if self.limit:
... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/dataset/dataset.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:30.428140 | from dataclasses import dataclass
@dataclass
class DatasetCfgCommon:
image_shape: tuple[int, int] | None
scene: str | None
|
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/dataset/dataset_co3d.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:30.429291 | import gzip
import json
from collections import defaultdict
from dataclasses import dataclass
from functools import cache
from pathlib import Path
from typing import Literal
import torch
import torchvision.transforms as tf
from jaxtyping import Float
from PIL import Image
from torch import Tensor
from torch.utils.data... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/config/overfit.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:30.433615 | from dataclasses import dataclass
from pathlib import Path
from ..model.model_wrapper_overfit import ModelWrapperOverfitCfg
from ..tracking import TrackPrecomputationCfg, TrackPredictorCfg
from .common import CommonCfg
@dataclass
class OverfitCfg(CommonCfg):
tracking: TrackPredictorCfg
track_precomputation: ... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/dataset/dataset_colmap.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:30.452353 | from dataclasses import dataclass
from pathlib import Path
from typing import Literal
import torch
import torchvision.transforms as tf
from PIL import Image
from torch.utils.data import Dataset
from ..export.colmap import read_colmap_model
from ..frame_sampler.frame_sampler import FrameSampler
from .dataset import Da... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/dataset/dataset_merged.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:31.013830 | import torch
from torch.utils.data import Dataset, IterableDataset
class DatasetMerged(IterableDataset):
def __init__(self, datasets: list[IterableDataset | Dataset]) -> None:
self.datasets = datasets
def __iter__(self):
remaining = [len(dataset) for dataset in self.datasets]
iterator... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/dataset/dataset_images.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:31.014400 | from dataclasses import dataclass
from pathlib import Path
from typing import Literal
import torch
import torchvision.transforms as tf
from PIL import Image
from torch.utils.data import Dataset
from ..frame_sampler.frame_sampler import FrameSampler
from .dataset import DatasetCfgCommon
from .types import Stage
@dat... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/dataset/types.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:31.054408 | from dataclasses import dataclass
from typing import Literal
from jaxtyping import Float, Int64
from torch import Tensor
from ..misc.manipulable import Manipulable
Stage = Literal["train", "test", "val"]
@dataclass
class Batch(Manipulable):
videos: Float[Tensor, "batch frame 3 height=_ width=_"]
indices: I... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/dataset/dataset_llff.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:31.063736 | from dataclasses import dataclass
from pathlib import Path
from typing import Literal
import numpy as np
import torch
import torchvision.transforms as tf
from einops import rearrange, repeat
from jaxtyping import Float
from PIL import Image
from torch import Tensor
from torch.utils.data import Dataset
from ..frame_sa... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/dataset/validation_wrapper.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:31.065018 | from typing import Iterator, Optional
import torch
from torch.utils.data import Dataset, IterableDataset
class ValidationWrapper(Dataset):
"""Wraps a dataset so that PyTorch Lightning's validation step can be turned into a
visualization step.
"""
dataset: Dataset
dataset_iterator: Optional[Itera... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/flow/common.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:31.071749 | from einops import rearrange
from jaxtyping import Float
from torch import Tensor
def split_videos(
videos: Float[Tensor, "batch frame 3 height width"],
) -> tuple[
Float[Tensor, "batch*(frame-1) 3 height width"], # source (flattened batch dims)
Float[Tensor, "batch*(frame-1) 3 height width"], # target ... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/dataset/dataset_re10k.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:31.075157 | import json
from dataclasses import dataclass
from functools import cached_property
from io import BytesIO
from pathlib import Path
from typing import Literal
import torch
import torchvision.transforms as tf
from einops import rearrange, repeat
from jaxtyping import Float, UInt8
from PIL import Image
from torch import... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/export/colmap.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:31.076321 | import shutil
from pathlib import Path
import numpy as np
import torch
from einops import einsum, rearrange
from jaxtyping import Float
from plyfile import PlyData, PlyElement
from scipy.spatial.transform import Rotation as R
from torch import Tensor
from ..misc.cropping import center_crop_intrinsics
from ..model.mod... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/flow/flow_predictor.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:31.112112 | from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Generic, TypeVar
import torch.nn.functional as F
from einops import rearrange
from jaxtyping import Float
from torch import Tensor, nn
from ..dataset.types import Batch
from ..misc.manipulable import Manipulable
from ..model.proj... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/flow/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:31.126157 | import torch
from ..dataset.types import Batch
from ..misc.nn_module_tools import convert_to_buffer
from .flow_predictor import FlowPredictor, Flows
from .flow_predictor_gmflow import FlowPredictorGMFlow, FlowPredictorGMFlowCfg
from .flow_predictor_raft import FlowPredictorRaft, FlowPredictorRaftCfg
FLOW_PREDICTORS =... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/frame_sampler/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:32.379783 | from typing import Any
from .frame_sampler import FrameSampler
from .frame_sampler_overfit import FrameSamplerOverfit, FrameSamplerOverfitCfg
from .frame_sampler_pretrain import FrameSamplerPretrain, FrameSamplerPretrainCfg
FRAME_SAMPLER = {
"overfit": FrameSamplerOverfit,
"pretrain": FrameSamplerPretrain,
}
... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/frame_sampler/frame_sampler_overfit.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:32.383409 | from dataclasses import dataclass
from typing import Literal
import torch
from jaxtyping import Int64
from torch import Tensor
from .frame_sampler import FrameSampler
@dataclass
class FrameSamplerOverfitCfg:
name: Literal["overfit"]
start: int | None
num_frames: int | None
step: int | None
class F... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/frame_sampler/frame_sampler_pretrain.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:32.385265 | from dataclasses import dataclass
from typing import Literal
import torch
from jaxtyping import Int64
from torch import Tensor
from .frame_sampler import FrameSampler
@dataclass
class FrameSamplerPretrainCfg:
name: Literal["pretrain"]
num_frames: int
class FrameSamplerPretrain(FrameSampler[FrameSamplerPre... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/frame_sampler/frame_sampler.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:32.386148 | from abc import ABC, abstractmethod
from typing import Generic, TypeVar
import torch
from jaxtyping import Int64
from torch import Tensor
T = TypeVar("T")
class FrameSampler(ABC, Generic[T]):
"""A frame sampler picks the frames that should be sampled from a dataset's video.
It makes sense to break the logic... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/flow/flow_predictor_gmflow.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:32.387027 | import sys
import urllib.request
from dataclasses import dataclass
from pathlib import Path
from typing import Literal
import torch
from einops import rearrange
from jaxtyping import Float
from torch import Tensor
try:
from ..third_party.gmflow.gmflow.gmflow import GMFlow
except ImportError:
GMFlow = None
fr... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/flow/flow_predictor_raft.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:32.388528 | from dataclasses import dataclass
from functools import partial
from typing import Literal
import torch
from einops import rearrange
from jaxtyping import Float
from torch import Tensor
from torchvision.models.optical_flow import Raft_Large_Weights, raft_large
from tqdm import tqdm
from .common import split_videos
fr... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/loss/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:32.389065 | from .loss import Loss
from .loss_flow import LossFlow, LossFlowCfg
from .loss_tracking import LossTracking, LossTrackingCfg
LOSSES = {
"flow": LossFlow,
"tracking": LossTracking,
}
LossCfg = LossFlowCfg | LossTrackingCfg
def get_losses(cfgs: list[LossCfg]) -> list[Loss]:
return [LOSSES[cfg.name](cfg) f... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/loss/loss.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:33.324993 | from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Generic, TypeVar
import torch
from jaxtyping import Float
from torch import Tensor, nn
from ..dataset.types import Batch
from ..flow import Flows
from ..model.model import ModelOutput
from ..tracking import Tracks
@dataclass
cl... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/loss/mapping/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:33.326146 | from .mapping import Mapping
from .mapping_huber import MappingHuber, MappingHuberCfg
from .mapping_l1 import MappingL1, MappingL1Cfg
from .mapping_l2 import MappingL2, MappingL2Cfg
MAPPINGS = {
"huber": MappingHuber,
"l1": MappingL1,
"l2": MappingL2,
}
MappingCfg = MappingHuberCfg | MappingL1Cfg | Mappin... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/misc/common_training_setup.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:33.354263 | from pathlib import Path
import hydra
import torch
import wandb
from lightning.pytorch.callbacks import Callback, LearningRateMonitor, ModelCheckpoint
from lightning.pytorch.loggers import Logger
from lightning.pytorch.loggers.wandb import WandbLogger
from omegaconf import DictConfig, OmegaConf
from ..config.common i... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/loss/loss_flow.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:33.440645 | from dataclasses import dataclass
from typing import Literal
from jaxtyping import Float
from torch import Tensor
from ..dataset.types import Batch
from ..flow import Flows
from ..model.model import ModelOutput
from ..model.projection import (
compute_backward_flow,
compute_forward_flow,
sample_image_grid... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/loss/loss_tracking.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:33.456447 | from dataclasses import dataclass
from typing import Literal
from einops import rearrange
from jaxtyping import Float
from torch import Tensor
from ..dataset.types import Batch
from ..flow import Flows
from ..model.model import ModelOutput
from ..model.projection import compute_track_flow
from ..tracking import Track... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/misc/config_tools.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:34.221903 | from dataclasses import dataclass
from pathlib import Path
from typing import Type, TypeVar
from dacite import Config, from_dict
from omegaconf import DictConfig, OmegaConf
TYPE_HOOKS = {
Path: Path,
}
T = TypeVar("T")
def get_typed_config(
data_class: Type[T],
cfg: DictConfig,
extra_type_hooks: d... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/misc/image_io.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:34.224509 | import io
from pathlib import Path
from typing import Union
import numpy as np
import torch
import torchvision.transforms as tf
from einops import rearrange, repeat
from jaxtyping import Float, UInt8
from matplotlib.figure import Figure
from PIL import Image
from torch import Tensor
FloatImage = Union[
Float[Tens... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/misc/disk_cache.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:34.225925 | import hashlib
import json
from pathlib import Path
from typing import Any, Callable, TypeVar
import torch
T = TypeVar("T")
def make_cache(location: Path | None):
def cache(key: Any, fallback: Callable[[], T]) -> T:
# If there's no cache location, the cache is disabled.
if location is None:
... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/loss/mapping/mapping_l1.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:34.227464 | from dataclasses import dataclass
from typing import Literal
from jaxtyping import Float
from torch import Tensor
from .mapping import Mapping
@dataclass
class MappingL1Cfg:
name: Literal["l1"]
class MappingL1(Mapping[MappingL1Cfg]):
def forward_undistorted(
self,
delta: Float[Tensor, "*ba... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/misc/local_logger.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:34.228403 | import os
from pathlib import Path
from typing import Any, Optional
from lightning.pytorch.loggers import Logger
from lightning.pytorch.utilities import rank_zero_only
from PIL import Image
LOG_PATH = Path("outputs/local")
class LocalLogger(Logger):
def __init__(self) -> None:
super().__init__()
... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/loss/mapping/mapping_huber.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:34.229637 | from dataclasses import dataclass
from typing import Literal
import torch
import torch.nn.functional as F
from jaxtyping import Float
from torch import Tensor
from .mapping import Mapping
@dataclass
class MappingHuberCfg:
name: Literal["huber"]
delta: float
class MappingHuber(Mapping[MappingHuberCfg]):
... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/loss/mapping/mapping_l2.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:34.230601 | from dataclasses import dataclass
from typing import Literal
from jaxtyping import Float
from torch import Tensor
from .mapping import Mapping
@dataclass
class MappingL2Cfg:
name: Literal["l2"]
class MappingL2(Mapping[MappingL2Cfg]):
def forward_undistorted(
self,
delta: Float[Tensor, "*ba... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/misc/ate.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:34.231708 | import torch
from jaxtyping import Float
from scipy import spatial
from torch import Tensor
def compute_ate(
gt: Float[Tensor, "point 3"],
predicted: Float[Tensor, "point 3"],
) -> tuple[
Float[Tensor, ""], # ate
Float[Tensor, "point 3"], # aligned gt
Float[Tensor, "point 3"], # aligned predict... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/misc/cropping.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:34.335140 | from dataclasses import dataclass, replace
import torch.nn.functional as F
from einops import rearrange
from jaxtyping import Float
from PIL import Image
from torch import Tensor
from ..dataset.types import Batch
@dataclass
class CroppingCfg:
image_shape: tuple[int, int] | int
flow_scale_multiplier: int
... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/misc/manipulable.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:35.226947 | from dataclasses import fields, replace
from typing import Any, TypeVar
import numpy as np
import torch
from jaxtyping import Bool, Int64
from torch import Tensor
T = TypeVar("T")
SliceLike = slice | int | Int64[Tensor, "..."] | Bool[Tensor, "..."]
Sliceable = Tensor | np.ndarray | list | tuple
def to_tuple(lst):
... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/misc/wandb_tools.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:35.227561 | from pathlib import Path
import wandb
from ..config.common import WandbCfg
def version_to_int(artifact) -> int:
"""Convert versions of the form vX to X. For example, v12 to 12."""
return int(artifact.version[1:])
def download_checkpoint(
run_id: str,
download_dir: Path,
version: str | None,
) ... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/model/backbone/backbone_explicit_depth.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:35.228896 | from dataclasses import dataclass
from typing import Literal
import torch
from torch import nn
from ...dataset.types import Batch
from ...flow.flow_predictor import Flows
from .backbone import Backbone, BackboneOutput
@dataclass
class BackboneExplicitDepthCfg:
name: Literal["explicit_depth"]
initial_depth: ... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/misc/nn_module_tools.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:35.229671 | from torch import nn
def convert_to_buffer(module: nn.Module, persistent: bool = True):
# Recurse over child modules.
for name, child in list(module.named_children()):
convert_to_buffer(child, persistent)
# Also re-save buffers to change persistence.
for name, parameter_or_buffer in (
... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/model/backbone/backbone.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:35.230133 | from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Generic, TypeVar
from jaxtyping import Float
from torch import Tensor, nn
from ...dataset.types import Batch
from ...flow.flow_predictor import Flows
T = TypeVar("T")
@dataclass
class BackboneOutput:
depths: Float[Tensor, ... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/model/backbone/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:35.230579 | from .backbone import Backbone
from .backbone_explicit_depth import BackboneExplicitDepth, BackboneExplicitDepthCfg
from .backbone_midas import BackboneMidas, BackboneMidasCfg
BACKBONES = {
"explicit_depth": BackboneExplicitDepth,
"midas": BackboneMidas,
}
BackboneCfg = BackboneExplicitDepthCfg | BackboneMida... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/model/backbone/backbone_midas.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:35.231089 | from dataclasses import dataclass
from typing import Literal
import torch
import torch.nn.functional as F
from einops import rearrange
from jaxtyping import Float
from torch import Tensor, nn
from ...dataset.types import Batch
from ...flow.flow_predictor import Flows
from ..projection import earlier, later, sample_im... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/model/extrinsics/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:35.666205 | from .extrinsics import Extrinsics
from .extrinsics_procrustes import ExtrinsicsProcrustes, ExtrinsicsProcrustesCfg
from .extrinsics_regressed import ExtrinsicsRegressed, ExtrinsicsRegressedCfg
EXTRINSICS = {
"procrustes": ExtrinsicsProcrustes,
"regressed": ExtrinsicsRegressed,
}
ExtrinsicsCfg = ExtrinsicsPro... |
dcharatan/flowmap | https://github.com/dcharatan/flowmap | null | null | null | null | 976 | null | null | mit | null | null | null | null | null | null | null | flowmap/loss/mapping/mapping.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:38.244950 | from abc import ABC, abstractmethod
from typing import Generic, TypeVar
import torch
from jaxtyping import Float
from torch import Tensor, nn
def fix_aspect_ratio(
points: Float[Tensor, "*batch 2"],
image_shape: tuple[int, int],
) -> Float[Tensor, "*batch 2"]:
"""When computing losses on normalized image... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/core/logger.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:40.445294 | #
# Copyright (C) 2010-2012 Vinay Sajip. All rights reserved. Licensed under the new BSD license.
#
import logging
import re
import platform
import sys
if platform.system() == 'Windows':
import ctypes
import ctypes.wintypes
# Reference: https://gist.github.com/vsajip/758430
# https://githu... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/cmdline.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:40.446420 | # coding: utf-8
import os
import sys
import json
from urllib.parse import urlparse
from argparse import ArgumentParser
from doujinshi_dl import __version__
from doujinshi_dl.utils import generate_html, generate_main_html, DB, EXTENSIONS
from doujinshi_dl.logger import logger
from doujinshi_dl.constant import PATH_SE... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/command.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:40.449262 | # coding: utf-8
import os
import shutil
import sys
import signal
import platform
import urllib3.exceptions
from doujinshi_dl.cmdline import cmd_parser, banner, write_config
from doujinshi_dl.core.registry import get_first_plugin
from doujinshi_dl.core import config as core_config
from doujinshi_dl.downloader import Do... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/core/registry.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:40.450614 | # coding: utf-8
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from doujinshi_dl.core.plugin import BasePlugin
def get_plugin(name: str) -> 'BasePlugin':
from importlib.metadata import entry_points
eps = entry_points(group='doujinshi_dl.plugins')
for ep in eps:
if ep.name == name:
... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/core/config.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:40.453866 | # coding: utf-8
"""Runtime configuration store for the main package.
Plugins write their paths and settings here so that generic utilities
(e.g. db.py) can read them without hard-coding any plugin name.
"""
_runtime: dict = {}
def set(key: str, value) -> None:
_runtime[key] = value
def get(key: str, default=N... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/core/downloader.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:40.459029 | # coding: utf-
import os
import asyncio
import httpx
import urllib3.exceptions
import zipfile
import io
from urllib.parse import urlparse
from doujinshi_dl.core.logger import logger
from doujinshi_dl.core.utils.db import Singleton
from doujinshi_dl.core import config as core_config
async def _async_request(method, ... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/constant.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:40.460119 | # coding: utf-8
"""Main-package constants.
Only the constants that the main package itself needs are defined here.
Plugin-specific constants live in the respective plugin package.
"""
import os
PATH_SEPARATOR = os.path.sep
|
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/core/plugin.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:40.476688 | # coding: utf-8
from abc import ABC, abstractmethod
from dataclasses import dataclass, field
from typing import List, Dict, Any, Iterator, Tuple
@dataclass
class GalleryMeta:
id: str
name: str
pretty_name: str
img_id: str
ext: list
pages: int
info: Dict[str, Any] = field(default_factory=di... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/core/utils/fs.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:41.357982 | # coding: utf-8
"""Filesystem utilities: filename formatting, CBZ generation, folder management."""
import os
import zipfile
import shutil
from typing import Tuple
from doujinshi_dl.core.logger import logger
from doujinshi_dl.constant import PATH_SEPARATOR
MAX_FIELD_LENGTH = 100
EXTENSIONS = ('.png', '.jpg', '.jpeg',... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/downloader.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:46.201703 | # coding: utf-8
# Compatibility shim — re-exports from new location.
# Preserves backward compatibility for: from doujinshi_dl.downloader import Downloader, CompressedDownloader
from doujinshi_dl.core.downloader import * # noqa: F401, F403
from doujinshi_dl.core.downloader import Downloader, CompressedDownloader, down... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/core/utils/http.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:46.232187 | # coding: utf-8
"""Generic async HTTP request helper (no site-specific headers injected here)."""
import httpx
import urllib3.exceptions
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
async def async_request(method, url, proxy=None, **kwargs):
"""
Thin async HTTP client wrapper.
Hea... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/logger.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:46.233716 | # coding: utf-8
# Compatibility shim — re-exports from new location.
# Preserves backward compatibility for: from doujinshi_dl.logger import logger
from doujinshi_dl.core.logger import * # noqa: F401, F403
from doujinshi_dl.core.logger import logger # noqa: F401
|
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/utils.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:46.758285 | # coding: utf-8
# Utility helpers for the main package.
# No plugin-specific imports.
# Generic filesystem / HTML utilities
from doujinshi_dl.core.utils.fs import ( # noqa: F401
format_filename, parse_doujinshi_obj, generate_cbz, move_to_folder,
EXTENSIONS, MAX_FIELD_LENGTH,
)
from doujinshi_dl.core.utils.htm... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/core/utils/db.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:46.760092 | # coding: utf-8
"""DB and Singleton utilities."""
import os
import sqlite3
class _Singleton(type):
""" A metaclass that creates a Singleton base class when called. """
_instances = {}
def __call__(cls, *args, **kwargs):
if cls not in cls._instances:
cls._instances[cls] = super(_Single... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/core/utils/html.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:46.760652 | # coding: utf-8
"""HTML viewer generation utilities (generic, no site-specific references)."""
import json
import os
import urllib.parse
from doujinshi_dl.core.logger import logger
from doujinshi_dl.core.utils.fs import EXTENSIONS, parse_doujinshi_obj
from doujinshi_dl.constant import PATH_SEPARATOR
def _readfile(pa... |
RicterZ/doujinshi-dl | https://github.com/RicterZ/doujinshi-dl | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | doujinshi_dl/core/utils/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:47.213169 | # coding: utf-8
from doujinshi_dl.core.utils.db import Singleton, DB
from doujinshi_dl.core.utils.fs import format_filename, generate_cbz, move_to_folder, parse_doujinshi_obj, EXTENSIONS
from doujinshi_dl.core.utils.html import generate_html, generate_main_html
from doujinshi_dl.core.utils.http import async_request
|
dannymcc/bluehood | https://github.com/dannymcc/bluehood | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | bluehood/config.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:49.358431 | """Configuration for bluehood."""
import os
from pathlib import Path
# Data directory
DATA_DIR = Path(os.environ.get("BLUEHOOD_DATA_DIR", Path.home() / ".local" / "share" / "bluehood"))
DATA_DIR.mkdir(parents=True, exist_ok=True)
# Database path (can be overridden directly)
DB_PATH = Path(os.environ.get("BLUEHOOD_DB... |
dannymcc/bluehood | https://github.com/dannymcc/bluehood | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | bluehood/notifications.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:49.359815 | """Notification system using ntfy.sh for push notifications."""
import asyncio
import logging
from datetime import datetime, timedelta
from typing import Optional
import aiohttp
from . import db
from .db import Device, Settings
logger = logging.getLogger(__name__)
# ntfy.sh base URL
NTFY_BASE_URL = "https://ntfy.s... |
dannymcc/bluehood | https://github.com/dannymcc/bluehood | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | bluehood/patterns.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:49.361365 | """Traffic pattern analysis for bluehood."""
from dataclasses import dataclass
from typing import Optional
from . import db
@dataclass
class Pattern:
"""Analyzed traffic pattern for a device."""
time_description: str # e.g., "Evenings (5PM-11PM)"
day_description: str # e.g., "Weekdays"
frequency:... |
dannymcc/bluehood | https://github.com/dannymcc/bluehood | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | bluehood/daemon.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:49.368137 | """Bluehood daemon - continuous Bluetooth scanning service."""
import argparse
import asyncio
import json
import logging
import os
import platform
import signal
import sys
import time
from pathlib import Path
from typing import Optional
import aiohttp
from . import db, __version__
from .config import SCAN_INTERVAL, ... |
dannymcc/bluehood | https://github.com/dannymcc/bluehood | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | bluehood/web.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:49.369197 | """Compatibility module for the Bluehood web server."""
from .webapp.server import WebServer
__all__ = ["WebServer"]
|
dannymcc/bluehood | https://github.com/dannymcc/bluehood | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | bluehood/classifier.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:49.369806 | """Device type classification based on vendor and patterns."""
import re
from typing import Optional
# macOS CoreBluetooth provides UUIDs instead of real MAC addresses for privacy.
# These are 36-character strings like "460649E9-2306-1FF2-1272-A8D9B9D9143D".
_MACOS_UUID_RE = re.compile(
r'^[0-9A-Fa-f]{8}-[0-9A-Fa... |
dannymcc/bluehood | https://github.com/dannymcc/bluehood | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | bluehood/db.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:49.371929 | """Database operations for bluehood."""
import json
import aiosqlite
from datetime import datetime, timedelta
from typing import Optional
from dataclasses import dataclass
from .config import DB_PATH, HEARTBEAT_URL, HEARTBEAT_INTERVAL, PRUNE_DAYS
@dataclass
class Device:
"""Represents a Bluetooth device."""
... |
dannymcc/bluehood | https://github.com/dannymcc/bluehood | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | bluehood/scanner.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:49.395026 | """Bluetooth scanning module using bleak (BLE) and hcitool (classic)."""
import asyncio
import logging
import os
import re
import subprocess
import time
from dataclasses import dataclass, field
from typing import Callable, Optional
import aiohttp
from bleak import BleakScanner
from bleak.backends.device import BLEDev... |
dannymcc/bluehood | https://github.com/dannymcc/bluehood | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | bluehood/prometheus.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:49.480850 | """Prometheus metrics exporter for Bluehood."""
import logging
from threading import Thread
from typing import Optional
import aiosqlite
from prometheus_client import (
Counter,
Gauge,
Histogram,
Info,
start_http_server,
)
from .config import DB_PATH
logger = logging.getLogger(__name__)
# Bucke... |
dannymcc/bluehood | https://github.com/dannymcc/bluehood | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | bluehood/webapp/server.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:50.073514 | """Web server for the Bluehood dashboard."""
import hashlib
import logging
import math
import secrets
from datetime import datetime, timedelta
from typing import Optional
from aiohttp import web
from .. import db
from ..classifier import classify_device, get_type_icon, get_type_label, get_all_types, is_randomized_ma... |
ProHiryu/bert-chinese-ner | https://github.com/ProHiryu/bert-chinese-ner | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | tf_metrics.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:52.531364 | """
Multiclass
from:
https://github.com/guillaumegenthial/tf_metrics/blob/master/tf_metrics/__init__.py
"""
__author__ = "Guillaume Genthial"
import numpy as np
import tensorflow as tf
from tensorflow.python.ops.metrics_impl import _streaming_confusion_matrix
def precision(labels, predictions, num_c... |
ProHiryu/bert-chinese-ner | https://github.com/ProHiryu/bert-chinese-ner | null | null | null | null | 975 | null | null | mit | null | null | null | null | null | null | null | BERT_NER.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:52.531818 | #! usr/bin/env python3
# -*- coding:utf-8 -*-
"""
Copyright 2018 The Google AI Language Team Authors.
BASED ON Google_BERT.
@Author:zhoukaiyin
Adjust code for chinese ner
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections
imp... |
Olivia5k/doge | https://github.com/Olivia5k/doge | null | null | null | null | 974 | null | null | mit | null | null | null | null | null | null | null | src/doge/core.py | null | null | null | null | null | null | Python | 2026-05-04T01:37:54.406950 | #!/usr/bin/env python
# Copyright (C) 2013-2024 Olivia Thiderman
"""Wow print Shibe to terminal, such random words."""
import argparse
import contextlib
import datetime
import getpass
import os
import platform
import random
import re
import shutil
import subprocess
import sys
import traceback
import unicodedata
from... |
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