repo_full_name stringlengths 6 93 | repo_url stringlengths 25 112 | repo_api_url stringclasses 28
values | owner stringclasses 28
values | repo_name stringclasses 28
values | description stringclasses 28
values | stars int64 617 98.8k | forks int64 31 355 ⌀ | watchers int64 990 999 ⌀ | license stringclasses 2
values | default_branch stringclasses 2
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
class | open_issues int64 3 104 ⌀ | file_path stringlengths 3 208 | file_name stringclasses 509
values | file_extension stringclasses 1
value | file_size_bytes int64 101 84k ⌀ | file_url stringclasses 627
values | file_raw_url stringclasses 627
values | file_sha stringclasses 624
values | language stringclasses 8
values | parsed_at stringdate 2026-05-04 01:12:36 2026-05-04 19:41:55 | text stringlengths 100 102k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/dataset/math_function.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:30.568869 | """
Math Functions
"""
import polars as pl
from .utility import DataProxy
def less(feature1: DataProxy, feature2: DataProxy | float) -> DataProxy:
"""Return the minimum value between two features"""
if isinstance(feature2, DataProxy):
df_merged: pl.DataFrame = feature1.df.join(feature2.df, on=["date... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:30.569382 | # The MIT License (MIT)
# Copyright (c) 2015-present, Xiaoyou Chen
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, cop... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/dataset/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:30.575868 | from .template import AlphaDataset
from .utility import Segment, to_datetime
from .processor import (
process_drop_na,
process_fill_na,
process_cs_norm,
process_robust_zscore_norm,
process_cs_rank_norm
)
__all__ = [
"AlphaDataset",
"Segment",
"to_datetime",
"process_drop_na",
"... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/dataset/datasets/alpha_158.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:30.605827 | import polars as pl
from vnpy.alpha import AlphaDataset
class Alpha158(AlphaDataset):
"""158 basic factors from Qlib"""
def __init__(
self,
df: pl.DataFrame,
train_period: tuple[str, str],
valid_period: tuple[str, str],
test_period: tuple[str, str]
) -> None:
... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/dataset/cs_function.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:30.608083 | """
Cross Section Operators
"""
import polars as pl
from .utility import DataProxy
def cs_rank(feature: DataProxy) -> DataProxy:
"""Perform cross-sectional ranking"""
df: pl.DataFrame = feature.df.select(
pl.col("datetime"),
pl.col("vt_symbol"),
pl.col("data").rank().over("datetime")... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/dataset/datasets/alpha_101.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:30.609301 | import polars as pl
from vnpy.alpha import AlphaDataset
class Alpha101(AlphaDataset):
"""101 basic factors from WorldQuant"""
def __init__(
self,
df: pl.DataFrame,
train_period: tuple[str, str],
valid_period: tuple[str, str],
test_period: tuple[str, str]
) -> None... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/dataset/processor.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:30.652684 | from datetime import datetime
import numpy as np
import polars as pl
from .utility import to_datetime
def process_drop_na(df: pl.DataFrame, names: list[str] | None = None) -> pl.DataFrame:
"""Remove rows with missing values"""
if names is None:
names = df.columns[2:-1]
for name in names:
... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/dataset/ta_function.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.098529 | """
Technical Analysis Operators
"""
import talib
import polars as pl
import pandas as pd
from .utility import DataProxy
def to_pd_series(feature: DataProxy) -> pd.Series:
"""Convert to pandas.Series data structure"""
series: pd.Series = feature.df.to_pandas().set_index(["datetime", "vt_symbol"])["data"]
... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/dataset/template.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.125724 | import time
from datetime import datetime
from typing import cast
from collections.abc import Callable
from multiprocessing import get_context
from multiprocessing.context import BaseContext
import polars as pl
import pandas as pd
from tqdm import tqdm
from alphalens.utils import get_clean_factor_and_forward_returns ... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/lab.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.165589 | import json
import shelve
import pickle
from pathlib import Path
from datetime import datetime, timedelta
from collections import defaultdict
from functools import lru_cache
import polars as pl
from vnpy.trader.object import BarData
from vnpy.trader.constant import Interval
from vnpy.trader.utility import extract_vt_... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/logger.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.175158 | import sys
from loguru import logger
# Remove default output
logger.remove()
# Add terminal output
fmt: str = "<green>{time:YYYY-MM-DD HH:mm:ss}</green> <level>{message}</level>"
logger.add(sys.stdout, colorize=True, format=fmt)
|
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/dataset/ts_function.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.185245 | """Time Series Operators"""
from typing import cast
from scipy import stats
import polars as pl
import numpy as np
from .utility import DataProxy
def ts_delay(feature: DataProxy, window: int) -> DataProxy:
"""Get the value from a fixed time in the past"""
df: pl.DataFrame = feature.df.select(
pl.co... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/model/models/lasso_model.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.237776 | import numpy as np
import polars as pl
from sklearn.linear_model import Lasso # type: ignore
from vnpy.alpha import (
AlphaDataset,
AlphaModel,
Segment,
logger
)
class LassoModel(AlphaModel):
"""LASSO regression learning algorithm"""
def __init__(
self,
alpha: float = 0.... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/model/models/lgb_model.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.284465 | from typing import cast
import numpy as np
import polars as pl
import lightgbm as lgb
import matplotlib.pyplot as plt
from vnpy.alpha.dataset import AlphaDataset, Segment
from vnpy.alpha.model import AlphaModel
class LgbModel(AlphaModel):
"""LightGBM ensemble learning algorithm"""
def __init__(
sel... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/dataset/utility.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.287431 | from datetime import datetime
from enum import Enum
from typing import Union
import polars as pl
class DataProxy:
"""Feature data proxy"""
def __init__(self, df: pl.DataFrame) -> None:
"""Constructor"""
self.name: str = df.columns[-1]
self.df: pl.DataFrame = df.rename({self.name: "da... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/model/models/mlp_model.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.698800 | import copy
from collections import defaultdict
from typing import Literal, cast
import numpy as np
import pandas as pd
import polars as pl
from sklearn.metrics import mean_squared_error # type: ignore
import torch
import torch.nn as nn
import torch.optim as optim
from vnpy.alpha import (
AlphaDataset,
A... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/model/template.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.729913 | from abc import ABCMeta, abstractmethod
from typing import Any
import numpy as np
from vnpy.alpha.dataset import AlphaDataset, Segment
class AlphaModel(metaclass=ABCMeta):
"""Template class for machine learning algorithms"""
@abstractmethod
def fit(self, dataset: AlphaDataset) -> None:
"""
... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/strategy/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.746828 | from .template import AlphaStrategy
from .backtesting import BacktestingEngine
__all__ = [
"AlphaStrategy",
"BacktestingEngine"
]
|
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/strategy/strategies/equity_demo_strategy.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.842324 | from collections import defaultdict
import polars as pl
from vnpy.trader.object import BarData, TradeData
from vnpy.trader.constant import Direction
from vnpy.trader.utility import round_to
from vnpy.alpha import AlphaStrategy
class EquityDemoStrategy(AlphaStrategy):
"""Equity Long-Only Demo Strategy"""
t... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/strategy/template.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.858350 | from abc import ABCMeta, abstractmethod
from collections import defaultdict
from typing import TYPE_CHECKING
import polars as pl
from vnpy.trader.object import BarData, TradeData, OrderData
from vnpy.trader.constant import Offset, Direction
if TYPE_CHECKING:
from vnpy.alpha.strategy.backtesting import Backtesti... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/chart/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.866751 | from .widget import ChartWidget
from .item import CandleItem, VolumeItem
__all__ = [
"ChartWidget",
"CandleItem",
"VolumeItem",
]
|
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/chart/base.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.881863 | from vnpy.trader.ui import QtGui
WHITE_COLOR = (255, 255, 255)
BLACK_COLOR = (0, 0, 0)
GREY_COLOR = (100, 100, 100)
UP_COLOR = (255, 75, 75)
DOWN_COLOR = (0, 255, 255)
CURSOR_COLOR = (255, 245, 162)
PEN_WIDTH = 1
BAR_WIDTH = 0.3
AXIS_WIDTH = 0.8
NORMAL_FONT = QtGui.QFont("Arial", 9)
def to_int(value: float) -> i... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/alpha/strategy/backtesting.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.941320 | from collections import defaultdict
from datetime import date, datetime
from copy import copy
from typing import cast
import traceback
import numpy as np
import polars as pl
import plotly.graph_objects as go # type: ignore
from plotly.subplots import make_subplots # type: ignore
from tqdm import tq... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/chart/axis.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:31.992962 | from datetime import datetime
from typing import Any
import pyqtgraph as pg # type: ignore
from .manager import BarManager
from .base import AXIS_WIDTH, NORMAL_FONT, QtGui
class DatetimeAxis(pg.AxisItem):
""""""
def __init__(self, manager: BarManager, *args: Any, **kwargs: Any) -> None:
""""""... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/chart/item.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:32.246972 | from abc import abstractmethod
import pyqtgraph as pg # type: ignore
from vnpy.trader.ui import QtCore, QtGui, QtWidgets
from vnpy.trader.object import BarData
from .base import BLACK_COLOR, UP_COLOR, DOWN_COLOR, PEN_WIDTH, BAR_WIDTH
from .manager import BarManager
class ChartItem(pg.GraphicsObject):
""""... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/chart/widget.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:32.327552 | from datetime import datetime
import pyqtgraph as pg # type: ignore
from vnpy.trader.ui import QtGui, QtWidgets, QtCore
from vnpy.trader.object import BarData
from .manager import BarManager
from .base import (
GREY_COLOR, WHITE_COLOR, CURSOR_COLOR, BLACK_COLOR,
to_int, NORMAL_FONT
)
from .axis import D... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/chart/manager.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:32.427340 | from datetime import datetime
from _collections_abc import dict_keys
from vnpy.trader.object import BarData
from .base import to_int
class BarManager:
""""""
def __init__(self) -> None:
""""""
self._bars: dict[datetime, BarData] = {}
self._datetime_index_map: dict[datetime, int] = {... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/event/engine.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:32.427811 | """
Event-driven framework of VeighNa framework.
"""
from collections import defaultdict
from collections.abc import Callable
from queue import Empty, Queue
from threading import Thread
from time import sleep
from typing import Any
EVENT_TIMER = "eTimer"
class Event:
"""
Event object consists of a type str... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/rpc/client.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:32.468210 | import threading
from time import time
from functools import lru_cache
from typing import Any
import zmq
from .common import HEARTBEAT_TOPIC, HEARTBEAT_TOLERANCE
class RemoteException(Exception):
"""
RPC remote exception
"""
def __init__(self, value: Any) -> None:
"""
Constructor
... |
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/event/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:32.497533 | from .engine import Event, EventEngine, EVENT_TIMER
__all__ = [
"Event",
"EventEngine",
"EVENT_TIMER",
]
|
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/rpc/common.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:32.575943 | import signal
# Achieve Ctrl-c interrupt recv
signal.signal(signal.SIGINT, signal.SIG_DFL)
HEARTBEAT_TOPIC = "heartbeat"
HEARTBEAT_INTERVAL = 10
HEARTBEAT_TOLERANCE = 30
|
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/rpc/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:32.576766 | from .client import RpcClient
from .server import RpcServer
__all__ = [
"RpcClient",
"RpcServer",
]
|
vnpy/vnpy | https://github.com/vnpy/vnpy | null | null | null | null | 40,081 | null | null | mit | null | null | null | null | null | null | null | vnpy/rpc/server.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:32.659196 | import threading
import traceback
from time import time
from collections.abc import Callable
import zmq
from .common import HEARTBEAT_TOPIC, HEARTBEAT_INTERVAL
class RpcServer:
""""""
def __init__(self) -> None:
"""
Constructor
"""
# Save functions dict: key is function name... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | gpu/generate.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:35.414148 | # Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import json
import os
import readline # type: ignore # noqa
import sys
import time
from dataclasses import dat... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | gpu/convert_checkpoint.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:35.460208 | import json
import os
import re
import sys
from pathlib import Path
from typing import Optional
from dataclasses import dataclass
import torch
from einops import rearrange
from safetensors.torch import save_file
import model
from pack_weight import convert_weight_int8_to_int2
@torch.inference_mode()
def ... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | gpu/convert_safetensors.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:35.460715 | import re
import torch
from pathlib import Path
from safetensors.torch import load_file
from einops import rearrange
from dataclasses import dataclass
from typing import Optional
transformer_configs = {
"2B": dict(n_layer=30, n_head=20, dim=2560, vocab_size=128256, n_local_heads=5, intermediate_size=6912),
}
@dat... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | gpu/bitnet_kernels/setup.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:35.469571 | from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
setup(
name='bitlinear_cpp',
ext_modules=[
CUDAExtension('bitlinear_cuda', [
'bitnet_kernels.cu',
])
],
cmdclass={
'build_ext': BuildExtension
}) |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | gpu/test.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:35.470701 | import torch
from torch.utils import benchmark
from torch import nn
from pack_weight import convert_weight_int8_to_int2
from torch.profiler import profile, record_function, ProfilerActivity
import ctypes
import numpy as np
# set all seed
torch.manual_seed(42)
np.random.seed(42)
bitnet_lib = ctypes.CDLL('bitnet_kernel... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | gpu/stats.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:35.472515 | # Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import time
from dataclasses import dataclass
from typing import Optional
@dataclass
class PhaseStats:
... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | gpu/sample_utils.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:35.481219 | # Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import torch
@torch.compile
def top_p(probs: torch.Tensor, p: float) -> torch.Tensor:
"""
Perform top-... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | gpu/model.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:35.482352 | # Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from torch import nn
... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | gpu/tokenizer.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:35.492719 | import os
from logging import getLogger
from pathlib import Path
from typing import (
AbstractSet,
cast,
Collection,
Dict,
Iterator,
List,
Literal,
Sequence,
TypedDict,
Union,
)
import tiktoken
from tiktoken.load import load_tiktoken_bpe
logger = getLogger(... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | gpu/pack_weight.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:35.522370 | import torch
import numpy as np
def B_global_16x32_to_shared_load_16x32_layout(i, j):
"""
stride * 8 * (tx // HALF_WARP_expr)
+ (tx % 8) * stride
+ 16 * ((tx % HALF_WARP_expr) // 8)
"""
thread_id = i * 2 + j // 16
row = (thread_id // 16) * 8 + (threa... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | run_inference.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.073025 | import os
import sys
import signal
import platform
import argparse
import subprocess
def run_command(command, shell=False):
"""Run a system command and ensure it succeeds."""
try:
subprocess.run(command, shell=shell, check=True)
except subprocess.CalledProcessError as e:
print(f"Error occur... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | run_inference_server.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.084260 | import os
import sys
import signal
import platform
import argparse
import subprocess
def run_command(command, shell=False):
"""Run a system command and ensure it succeeds."""
try:
subprocess.run(command, shell=shell, check=True)
except subprocess.CalledProcessError as e:
print(f"Error occur... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | setup_env.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.111568 | import subprocess
import signal
import sys
import os
import platform
import argparse
import logging
import shutil
from pathlib import Path
logger = logging.getLogger("setup_env")
SUPPORTED_HF_MODELS = {
"1bitLLM/bitnet_b1_58-large": {
"model_name": "bitnet_b1_58-large",
},
"1bitLLM/bitnet_b1_58-3B... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | utils/convert-helper-bitnet.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.124261 | #!/usr/bin/env python3
import sys
import os
import shutil
import subprocess
from pathlib import Path
def run_command(command_list, cwd=None, check=True):
print(f"Executing: {' '.join(map(str, command_list))}")
try:
process = subprocess.run(command_list, cwd=cwd, check=check, capture_output=False, text... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | utils/convert-hf-to-gguf-bitnet.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.125613 | #!/usr/bin/env python3
from __future__ import annotations
import logging
import argparse
import contextlib
import json
import os
import re
import sys
from abc import ABC, abstractmethod
from enum import IntEnum
from pathlib import Path
from hashlib import sha256
from typing import TYPE_CHECKING, Any, Callable, Contex... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | utils/codegen_tl1.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.129763 | import argparse
import os
from configparser import ConfigParser
def gen_ctor_code():
kernel_code = "\n\
#include \"ggml-bitnet.h\"\n\
#define GGML_BITNET_MAX_NODES 8192\n\
static bool initialized = false;\n\
static bitnet_tensor_extra * bitnet_tensor_extras = nullptr;\n\
static size_t bitnet_tensor_extras_index = ... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | utils/codegen_tl2.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.132145 | import argparse
import os
from configparser import ConfigParser
def gen_ctor_code():
kernel_code = "\n\
#include \"ggml-bitnet.h\"\n\
#include <cstring>\n\
#include <immintrin.h>\n\
#define GGML_BITNET_MAX_NODES 8192\n\
static bool initialized = false;\n\
static bitnet_tensor_extra * bitnet_tensor_extras = nullptr... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | utils/convert.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.154723 | #!/usr/bin/env python3
from __future__ import annotations
import logging
import argparse
import concurrent.futures
import enum
import faulthandler
import functools
import itertools
import json
import math
import mmap
import os
import re
import signal
import struct
import sys
import textwrap
import time
from abc import... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | utils/e2e_benchmark.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.184878 | import os
import sys
import logging
import argparse
import platform
import subprocess
def run_command(command, shell=False, log_step=None):
"""Run a system command and ensure it succeeds."""
if log_step:
log_file = os.path.join(args.log_dir, log_step + ".log")
with open(log_file, "w") as f:
... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | utils/convert-ms-to-gguf-bitnet.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.185598 | #!/usr/bin/env python3
from __future__ import annotations
import logging
import argparse
import concurrent.futures
import enum
import faulthandler
import functools
import itertools
import json
import math
import mmap
import os
import re
import signal
import struct
import sys
import textwrap
import time
from abc import... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | utils/generate-dummy-bitnet-model.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.685423 | #!/usr/bin/env python3
# dummy model generation script based on convert-hf-to-gguf-bitnet.py
from __future__ import annotations
import sys
from pathlib import Path
import numpy as np
import configparser
import logging
import argparse
import contextlib
import json
import os
import re
import sys
from abc import ABC, ab... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | utils/quantize_embeddings.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.693217 | #!/usr/bin/env python3
"""
Embedding Quantization Script
This script converts ggml-model-f32.gguf to multiple quantized versions
with different token embedding types.
"""
import subprocess
import os
import argparse
import re
import csv
from pathlib import Path
from datetime import datetime
class EmbeddingQuantizer:
... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | utils/preprocess-huggingface-bitnet.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.723384 | from safetensors import safe_open
from safetensors.torch import save_file
import torch
def quant_weight_fp16(weight):
weight = weight.to(torch.float)
s = 1.0 / weight.abs().mean().clamp_(min=1e-5)
new_weight = (weight * s).round().clamp(-1, 1) / s
return new_weight
def quant_model(input, output):
... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | utils/test_perplexity.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.793031 | #!/usr/bin/env python3
"""
Perplexity Test Script
Tests GGUF model perplexity on multiple datasets using llama-perplexity.
"""
import os
import subprocess
import time
import csv
import re
from datetime import datetime
from pathlib import Path
import argparse
import tempfile
import shutil
import statistics
class Perp... |
microsoft/BitNet | https://github.com/microsoft/BitNet | null | null | null | null | 38,793 | null | null | mit | null | null | null | null | null | null | null | utils/tune_gemm_config.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:36.823488 | #!/usr/bin/env python3
"""
GEMM Configuration Tuning Script
This script automatically tunes ROW_BLOCK_SIZE, COL_BLOCK_SIZE, and PARALLEL_SIZE
to find the optimal configuration for maximum throughput (t/s).
"""
import subprocess
import os
import re
import csv
import shutil
from datetime import datetime
from pathlib imp... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/speed_estimation/inference_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:40.273959 | import os
from collections import defaultdict, deque
import cv2
import numpy as np
from inference.models.utils import get_roboflow_model
import supervision as sv
SOURCE = np.array([[1252, 787], [2298, 803], [5039, 2159], [-550, 2159]])
TARGET_WIDTH = 25
TARGET_HEIGHT = 250
TARGET = np.array(
[
[0, 0],
... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/inference_file_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:40.275672 | import cv2
import numpy as np
from inference import get_model
from utils.general import find_in_list, load_zones_config
from utils.timers import FPSBasedTimer
import supervision as sv
COLORS = sv.ColorPalette.from_hex(["#E6194B", "#3CB44B", "#FFE119", "#3C76D1"])
COLOR_ANNOTATOR = sv.ColorAnnotator(color=COLORS)
LABE... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/heatmap_and_track/script.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:40.280848 | from typing import Optional
import cv2
from ultralytics import YOLO
import supervision as sv
from supervision.assets import VideoAssets, download_assets
def download_video() -> str:
download_assets(VideoAssets.PEOPLE_WALKING)
return VideoAssets.PEOPLE_WALKING.value
def main(
source_weig... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/speed_estimation/ultralytics_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:40.282343 | from collections import defaultdict, deque
import cv2
import numpy as np
from ultralytics import YOLO
import supervision as sv
SOURCE = np.array([[1252, 787], [2298, 803], [5039, 2159], [-550, 2159]])
TARGET_WIDTH = 25
TARGET_HEIGHT = 250
TARGET = np.array(
[
[0, 0],
[TARGET_WIDTH - 1, 0],
... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/count_people_in_zone/inference_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:40.283585 | import json
import os
import cv2
import numpy as np
from inference.core.models.roboflow import RoboflowInferenceModel
from inference.models.utils import get_roboflow_model
from tqdm import tqdm
import supervision as sv
COLORS = sv.ColorPalette.DEFAULT
def load_zones_config(file_path: str) -> list[np.ndarray]:
... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/speed_estimation/yolo_nas_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:40.284513 | from collections import defaultdict, deque
import cv2
import numpy as np
from super_gradients.common.object_names import Models
from super_gradients.training import models
import supervision as sv
SOURCE = np.array([[1252, 787], [2298, 803], [5039, 2159], [-550, 2159]])
TARGET_WIDTH = 25
TARGET_HEIGHT = 250
TARGET... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/compact_mask/benchmark.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:40.285920 | """CompactMask demo & benchmark.
Demonstrates that ``CompactMask`` is a drop-in replacement for dense
``(N, H, W)`` bool arrays in ``supervision.Detections``, while using
significantly less memory and enabling faster annotation.
Run with:
uv run python examples/compact_mask/benchmark.py
No GPU or real model is r... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/count_people_in_zone/ultralytics_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:40.354661 | import json
import cv2
import numpy as np
from tqdm import tqdm
from ultralytics import YOLO
import supervision as sv
COLORS = sv.ColorPalette.DEFAULT
def load_zones_config(file_path: str) -> list[np.ndarray]:
"""
Load polygon zone configurations from a JSON file.
This function reads a JSON file which... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | .github/scripts/augment_links.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:40.477496 | #!/usr/bin/env python3
"""
Script to augment relative links in markdown files to GitHub URLs.
"""
import argparse
import os
import re
from re import Match
def get_repo_root() -> str:
"""Get the repository root path."""
script_dir = os.path.dirname(os.path.abspath(__file__))
return os.path.dirname(os.path... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/speed_estimation/video_downloader.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:40.478051 | import os
from supervision.assets import VideoAssets, download_assets
if not os.path.exists("data"):
os.makedirs("data")
os.chdir("data")
download_assets(VideoAssets.VEHICLES)
|
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/rfdetr_stream_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:41.121899 | from __future__ import annotations
from enum import Enum
import cv2
import numpy as np
from inference import InferencePipeline
from inference.core.interfaces.camera.entities import VideoFrame
from rfdetr import RFDETRBase, RFDETRLarge, RFDETRMedium, RFDETRNano, RFDETRSmall
from utils.general import find_in_list, load... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/scripts/stream_from_file.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:41.296834 | import os
import subprocess
import tempfile
from glob import glob
from threading import Thread
import yaml
from jsonargparse import auto_cli
SERVER_CONFIG = {"protocols": ["tcp"], "paths": {"all": {"source": "publisher"}}}
BASE_STREAM_URL = "rtsp://localhost:8554/live"
def main(video_directory: str, number_of_strea... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/inference_stream_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:41.299232 | import cv2
import numpy as np
from inference import InferencePipeline
from inference.core.interfaces.camera.entities import VideoFrame
from utils.general import find_in_list, load_zones_config
from utils.timers import ClockBasedTimer
import supervision as sv
COLORS = sv.ColorPalette.from_hex(["#E6194B", "#3CB44B", "#... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/rfdetr_naive_stream_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:41.300184 | from __future__ import annotations
from enum import Enum
import cv2
import numpy as np
from rfdetr import RFDETRBase, RFDETRLarge, RFDETRMedium, RFDETRNano, RFDETRSmall
from utils.general import find_in_list, get_stream_frames_generator, load_zones_config
from utils.timers import ClockBasedTimer
import supervision a... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/ultralytics_file_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:41.301359 | import cv2
import numpy as np
from ultralytics import YOLO
from utils.general import find_in_list, load_zones_config
from utils.timers import FPSBasedTimer
import supervision as sv
COLORS = sv.ColorPalette.from_hex(["#E6194B", "#3CB44B", "#FFE119", "#3C76D1"])
COLOR_ANNOTATOR = sv.ColorAnnotator(color=COLORS)
LABEL_A... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/scripts/download_from_youtube.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:41.303257 | from __future__ import annotations
import os
import sys
from typing import Any
import yt_dlp
from jsonargparse import auto_cli
from yt_dlp.utils import DownloadError
def _build_ydl_opts(output_path: str | None, file_name: str | None) -> dict[str, Any]:
out_dir = output_path or "."
if not os.path.exists(out... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/scripts/draw_zones.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:41.304320 | from __future__ import annotations
import json
import os
from typing import Any
import cv2
import numpy as np
from jsonargparse import auto_cli
import supervision as sv
KEY_ENTER = 13
KEY_NEWLINE = 10
KEY_ESCAPE = 27
KEY_QUIT = ord("q")
KEY_SAVE = ord("s")
THICKNESS = 2
COLORS = sv.ColorPalette.DEFAULT
WINDOW_NAME... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/inference_naive_stream_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:41.380312 | import cv2
import numpy as np
from inference import get_model
from utils.general import find_in_list, get_stream_frames_generator, load_zones_config
from utils.timers import ClockBasedTimer
import supervision as sv
COLORS = sv.ColorPalette.from_hex(["#E6194B", "#3CB44B", "#FFE119", "#3C76D1"])
COLOR_ANNOTATOR = sv.Co... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/ultralytics_naive_stream_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:41.384045 | import cv2
import numpy as np
from ultralytics import YOLO
from utils.general import find_in_list, get_stream_frames_generator, load_zones_config
from utils.timers import ClockBasedTimer
import supervision as sv
COLORS = sv.ColorPalette.from_hex(["#E6194B", "#3CB44B", "#FFE119", "#3C76D1"])
COLOR_ANNOTATOR = sv.Color... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/rfdetr_file_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:41.501538 | from __future__ import annotations
from enum import Enum
import cv2
import numpy as np
from rfdetr import RFDETRBase, RFDETRLarge, RFDETRMedium, RFDETRNano, RFDETRSmall
from utils.general import find_in_list, load_zones_config
from utils.timers import FPSBasedTimer
import supervision as sv
COLORS = sv.ColorPalette.... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/ultralytics_stream_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.077927 | from __future__ import annotations
import cv2
import numpy as np
from inference import InferencePipeline
from inference.core.interfaces.camera.entities import VideoFrame
from ultralytics import YOLO
from utils.general import find_in_list, load_zones_config
from utils.timers import ClockBasedTimer
import supervision a... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/traffic_analysis/inference_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.087200 | from __future__ import annotations
import os
from collections.abc import Iterable
import cv2
import numpy as np
from inference.models.utils import get_roboflow_model
from tqdm import tqdm
import supervision as sv
COLORS = sv.ColorPalette.from_hex(["#E6194B", "#3CB44B", "#FFE119", "#3C76D1"])
ZONE_IN_POLYGONS = [
... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/tracking/ultralytics_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.190552 | from tqdm import tqdm
from ultralytics import YOLO
import supervision as sv
def main(
source_weights_path: str,
source_video_path: str,
target_video_path: str,
confidence_threshold: float = 0.3,
iou_threshold: float = 0.7,
) -> None:
"""
Video Processing with YOLO and ByteTrack.
Args... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/tracking/inference_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.198879 | import os
from inference.models.utils import get_roboflow_model
from tqdm import tqdm
import supervision as sv
def main(
source_video_path: str,
target_video_path: str,
roboflow_api_key: str,
model_id: str = "yolov8x-1280",
confidence_threshold: float = 0.3,
iou_threshold: float = 0.7,
) -> ... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/utils/timers.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.202757 | from datetime import datetime
import numpy as np
import supervision as sv
class FPSBasedTimer:
"""
A timer that calculates the duration each object has been detected based on frames
per second (FPS).
Attributes:
fps (float): The frame rate of the video stream, used to calculate
... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/time_in_zone/utils/general.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.210187 | import json
from collections.abc import Generator
import cv2
import numpy as np
def load_zones_config(file_path: str) -> list[np.ndarray]:
"""
Load polygon zone configurations from a JSON file.
This function reads a JSON file which contains polygon coordinates, and
converts them into a list of NumPy... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | examples/traffic_analysis/ultralytics_example.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.215048 | from __future__ import annotations
from collections.abc import Iterable
import cv2
import numpy as np
from tqdm import tqdm
from ultralytics import YOLO
import supervision as sv
COLORS = sv.ColorPalette.from_hex(["#E6194B", "#3CB44B", "#FFE119", "#3C76D1"])
ZONE_IN_POLYGONS = [
np.array([[592, 282], [900, 282]... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.300624 | import importlib.metadata as importlib_metadata
try:
# This will read version from pyproject.toml
__version__ = importlib_metadata.version(__package__ or __name__)
except importlib_metadata.PackageNotFoundError:
__version__ = "development"
from supervision.annotators.core import (
BackgroundOverlayAnn... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/annotators/utils.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.642819 | from __future__ import annotations
import re
import textwrap
from enum import Enum
from typing import Any
import numpy as np
import numpy.typing as npt
from supervision.config import CLASS_NAME_DATA_FIELD
from supervision.detection.core import Detections
from supervision.draw.color import Color, ColorPalette
from su... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/annotators/base.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.670786 | from abc import ABC, abstractmethod
from typing import Any
from supervision.detection.core import Detections
class BaseAnnotator(ABC):
@abstractmethod
def annotate(
self, scene: Any, detections: Detections, *args: Any, **kwargs: Any
) -> Any:
pass
|
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/assets/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.773059 | from supervision.assets.downloader import download_assets
from supervision.assets.list import ImageAssets, VideoAssets
__all__ = ["ImageAssets", "VideoAssets", "download_assets"]
|
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/assets/list.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.803613 | from enum import Enum
BASE_VIDEO_URL = "https://media.roboflow.com/supervision/video-examples/"
BASE_IMAGE_URL = "https://media.roboflow.com/supervision/image-examples/"
class Assets(Enum):
filename: str
md5_hash: str
def __new__(cls, filename: str, md5_hash: str) -> "Assets":
obj = object.__new... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/classification/core.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.880490 | from __future__ import annotations
from dataclasses import dataclass
from typing import TYPE_CHECKING, Any
import numpy as np
import numpy.typing as npt
if TYPE_CHECKING:
import torch
def _validate_class_ids(class_id: Any, n: int) -> None:
"""
Ensure that class_id is a 1d np.ndarray with (n, ) shape.
... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/dataset/core.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.884889 | from __future__ import annotations
import os
from abc import ABC, abstractmethod
from collections.abc import Iterator
from dataclasses import dataclass
from itertools import chain
from pathlib import Path
import cv2
import numpy as np
import numpy.typing as npt
from supervision.classification.core import Classificat... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/assets/downloader.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:42.915828 | from __future__ import annotations
import os
from hashlib import md5
from pathlib import Path
from shutil import copyfileobj
from requests import get
from tqdm.auto import tqdm
from supervision.assets.list import MEDIA_ASSETS, Assets
from supervision.utils.logger import _get_logger
logger = _get_logger(__name__)
... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/dataset/formats/coco.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:43.250062 | import warnings
from datetime import datetime
from pathlib import Path
from typing import TYPE_CHECKING, Any, Union, cast
import numpy as np
import numpy.typing as npt
from supervision.dataset.utils import (
approximate_mask_with_polygons,
map_detections_class_id,
)
from supervision.detection.core import Dete... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/dataset/formats/pascal_voc.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:43.354071 | from __future__ import annotations
import os
from pathlib import Path
from xml.etree.ElementTree import Element, SubElement
import cv2
import numpy as np
import numpy.typing as npt
from defusedxml.ElementTree import parse, tostring
from defusedxml.minidom import parseString
from supervision.dataset.utils import appr... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/dataset/utils.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:43.401010 | from __future__ import annotations
import copy
import os
import random
import shutil
from pathlib import Path
from typing import TYPE_CHECKING, Any, TypeVar
import cv2
import numpy as np
import numpy.typing as npt
from deprecate import deprecated, void
from supervision.detection.core import Detections
from supervisi... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/dataset/formats/yolo.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:43.426057 | from __future__ import annotations
import os
import warnings
from pathlib import Path
from typing import TYPE_CHECKING, Any
import numpy as np
import numpy.typing as npt
from PIL import Image
from supervision.config import ORIENTED_BOX_COORDINATES
from supervision.dataset.utils import approximate_mask_with_polygons
... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/detection/compact_mask.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:43.473434 | """Crop-RLE compact mask storage for memory-efficient instance segmentation.
Dense ``(N, H, W)`` boolean masks use O(N·H·W) memory, which becomes
prohibitive for aerial imagery (e.g. 1000 objects x 4K image ~ 8.3 GB).
:class:`CompactMask` stores each mask as a run-length encoding of its
bounding-box crop, reducing typ... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/detection/line_zone.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:43.513770 | from __future__ import annotations
import math
import warnings
from collections import Counter, defaultdict, deque
from collections.abc import Iterable
from functools import lru_cache
from typing import Any, Literal, cast
import cv2
import numpy as np
import numpy.typing as npt
from supervision.config import CLASS_N... |
roboflow/supervision | https://github.com/roboflow/supervision | null | null | null | null | 38,300 | null | null | mit | null | null | null | null | null | null | null | src/supervision/detection/core.py | null | null | null | null | null | null | Python | 2026-05-04T02:21:43.672271 | from __future__ import annotations
from collections.abc import Iterator
from dataclasses import dataclass, field
from functools import reduce
from typing import Any, cast
import numpy as np
import numpy.typing as npt
from supervision.config import (
CLASS_NAME_DATA_FIELD,
ORIENTED_BOX_COORDINATES,
)
from sup... |
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