repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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mmyolo | mmyolo-main/tests/test_models/test_dense_heads/test_ppyoloe_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import torch
from mmengine import ConfigDict, MessageHub
from mmengine.config import Config
from mmengine.model import bias_init_with_prob
from mmengine.testing import assert_allclose
from mmyolo.models import PPYOLOEHead
from mmyolo.utils ... | 7,851 | 37.116505 | 78 | py |
mmyolo | mmyolo-main/tests/test_models/test_dense_heads/test_yolov7_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import torch
from mmengine.config import Config
from mmengine.structures import InstanceData
from mmyolo.models.dense_heads import YOLOv7Head
from mmyolo.utils import register_all_modules
register_all_modules()
# TODO: Test YOLOv7p6HeadM... | 5,521 | 36.821918 | 79 | py |
mmyolo | mmyolo-main/tests/test_models/test_dense_heads/test_yolov5_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import torch
from mmengine.config import Config
from mmengine.structures import InstanceData
from mmyolo.models.dense_heads import YOLOv5Head
from mmyolo.utils import register_all_modules
register_all_modules()
class TestYOLOv5Head(TestC... | 9,871 | 40.654008 | 79 | py |
mmyolo | mmyolo-main/tests/test_models/test_dense_heads/test_yolox_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import torch
from mmengine.config import Config
from mmengine.model import bias_init_with_prob
from mmengine.testing import assert_allclose
from mmyolo.models.dense_heads import YOLOXHead
from mmyolo.utils import register_all_modules
regis... | 6,200 | 37.75625 | 79 | py |
mmyolo | mmyolo-main/tests/test_models/test_dense_heads/test_yolov6_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import torch
from mmengine.config import Config
from mmyolo.models.dense_heads import YOLOv6Head
from mmyolo.utils import register_all_modules
register_all_modules()
class TestYOLOv6Head(TestCase):
def setUp(self):
self.head... | 1,713 | 26.645161 | 74 | py |
mmyolo | mmyolo-main/tests/test_models/test_dense_heads/test_rotated_rtmdet_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import pytest
import torch
from mmengine.config import Config
from mmengine.structures import InstanceData
from mmyolo.models.dense_heads import RTMDetRotatedHead
from mmyolo.utils import register_all_modules
register_all_modules()
class... | 10,370 | 38.135849 | 79 | py |
mmyolo | mmyolo-main/tests/test_models/test_dense_heads/test_yolov8_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import torch
from mmengine import ConfigDict
from mmengine.config import Config
from mmyolo.models import YOLOv8Head
from mmyolo.utils import register_all_modules
register_all_modules()
class TestYOLOv8Head(TestCase):
def setUp(self... | 5,914 | 35.512346 | 78 | py |
mmyolo | mmyolo-main/tests/test_models/test_dense_heads/test_rtmdet_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import numpy as np
import torch
from mmengine.config import Config
from mmengine.structures import InstanceData
from mmyolo.models import RTMDetInsSepBNHead
from mmyolo.models.dense_heads import RTMDetHead
from mmyolo.utils import register_... | 7,546 | 32.691964 | 78 | py |
mmyolo | mmyolo-main/tests/test_models/test_detectors/test_yolo_detector.py | # Copyright (c) OpenMMLab. All rights reserved.
import time
import unittest
from unittest import TestCase
import torch
from mmdet.structures import DetDataSample
from mmdet.testing import demo_mm_inputs
from mmengine.logging import MessageHub
from parameterized import parameterized
from mmyolo.testing import get_dete... | 5,695 | 40.275362 | 79 | py |
mmyolo | mmyolo-main/tests/test_models/test_task_modules/test_coders/test_distance_point_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import torch
from mmyolo.models.task_modules.coders import DistancePointBBoxCoder
class TestDistancePointBBoxCoder(TestCase):
def test_decoder(self):
coder = DistancePointBBoxCoder()
points = torch.Tensor([[74., 61.]... | 1,218 | 39.633333 | 77 | py |
mmyolo | mmyolo-main/tests/test_models/test_task_modules/test_coders/test_yolov5_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import torch
from mmyolo.models.task_modules.coders import YOLOv5BBoxCoder
class TestYOLOv5Coder(TestCase):
def test_decoder(self):
coder = YOLOv5BBoxCoder()
priors = torch.Tensor([[10., 10., 20., 20.], [10., 8., 10.... | 1,336 | 39.515152 | 77 | py |
mmyolo | mmyolo-main/tests/test_models/test_task_modules/test_coders/test_yolox_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import torch
from mmyolo.models.task_modules.coders import YOLOXBBoxCoder
class TestYOLOv5Coder(TestCase):
def test_decoder(self):
coder = YOLOXBBoxCoder()
priors = torch.Tensor([[10., 10.], [8., 8.], [15., 8.], [2.,... | 1,266 | 38.59375 | 77 | py |
mmyolo | mmyolo-main/tests/test_models/test_task_modules/test_assigners/test_batch_dsl_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import pytest
import torch
from mmyolo.models.task_modules.assigners import BatchDynamicSoftLabelAssigner
class TestBatchDynamicSoftLabelAssigner(TestCase):
def test_assign(self):
num_classes = 2
batch_size = 2
... | 7,466 | 37.689119 | 79 | py |
mmyolo | mmyolo-main/tests/test_models/test_task_modules/test_assigners/test_batch_atss_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import torch
from mmyolo.models.task_modules.assigners import BatchATSSAssigner
class TestBatchATSSAssigner(TestCase):
def test_batch_atss_assigner(self):
num_classes = 2
batch_size = 2
batch_atss_assigner = B... | 7,366 | 40.857955 | 79 | py |
mmyolo | mmyolo-main/tests/test_models/test_task_modules/test_assigners/test_batch_task_aligned_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import torch
from mmyolo.models.task_modules.assigners import BatchTaskAlignedAssigner
class TestBatchTaskAlignedAssigner(TestCase):
def test_batch_task_aligned_assigner(self):
batch_size = 2
num_classes = 4
a... | 2,212 | 37.824561 | 79 | py |
mmyolo | mmyolo-main/tests/test_models/test_plugins/test_cbam.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import torch
from mmyolo.models.plugins import CBAM
from mmyolo.utils import register_all_modules
register_all_modules()
class TestCBAM(TestCase):
def test_forward(self):
tensor_shape = (2, 16, 20, 20)
images = tor... | 783 | 23.5 | 65 | py |
mmyolo | mmyolo-main/tests/test_datasets/test_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import unittest
import numpy as np
import torch
from mmdet.structures import DetDataSample
from mmdet.structures.bbox import HorizontalBoxes
from mmengine.structures import InstanceData
from mmyolo.datasets import BatchShapePolicy, yolov5_collate
def _rand_bboxes(rng,... | 4,918 | 34.388489 | 79 | py |
mmyolo | mmyolo-main/tests/test_datasets/test_transforms/test_mix_img_transforms.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import os.path as osp
import unittest
import numpy as np
import torch
from mmdet.structures.bbox import HorizontalBoxes
from mmdet.structures.mask import BitmapMasks, PolygonMasks
from mmyolo.datasets import YOLOv5CocoDataset
from mmyolo.datasets.transforms ... | 17,683 | 40.221445 | 79 | py |
mmyolo | mmyolo-main/tests/test_datasets/test_transforms/test_transforms.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import os.path as osp
import unittest
import mmcv
import numpy as np
import torch
from mmdet.structures.bbox import HorizontalBoxes
from mmdet.structures.mask import BitmapMasks, PolygonMasks
from mmyolo.datasets.transforms import (LetterResize, LoadAnnotati... | 21,175 | 42.12831 | 79 | py |
mmyolo | mmyolo-main/demo/deploy_demo.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Deploy demo for mmdeploy.
This script help user to run mmdeploy demo after convert the
checkpoint to backends.
Usage:
python deploy_demo.py img \
config \
checkpoint \
[--deploy-cfg DEP... | 3,823 | 30.603306 | 95 | py |
mmyolo | mmyolo-main/demo/boxam_vis_demo.py | # Copyright (c) OpenMMLab. All rights reserved.
"""This script is in the experimental verification stage and cannot be
guaranteed to be completely correct. Currently Grad-based CAM and Grad-free CAM
are supported.
The target detection task is different from the classification task. It not
only includes the AM map of t... | 9,251 | 32.400722 | 79 | py |
mmyolo | mmyolo-main/docs/en/conf.py | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | 3,414 | 28.439655 | 79 | py |
mmyolo | mmyolo-main/docs/zh_cn/conf.py | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | 3,434 | 28.110169 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/data_preprocessors/data_preprocessor.py | # Copyright (c) OpenMMLab. All rights reserved.
import random
from typing import List, Optional, Tuple, Union
import torch
import torch.nn.functional as F
from mmdet.models import BatchSyncRandomResize
from mmdet.models.data_preprocessors import DetDataPreprocessor
from mmengine import MessageHub, is_list_of
from mmen... | 11,943 | 38.419142 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/detectors/yolo_detector.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet.models.detectors.single_stage import SingleStageDetector
from mmdet.utils import ConfigType, OptConfigType, OptMultiConfig
from mmengine.dist import get_world_size
from mmengine.logging import print_log
from mmyolo.registry import MODELS
@MODELS... | 2,138 | 38.611111 | 76 | py |
mmyolo | mmyolo-main/mmyolo/models/plugins/cbam.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmdet.utils import OptMultiConfig
from mmengine.model import BaseModule
from mmyolo.registry import MODELS
class ChannelAttention(BaseModule):
"""ChannelAttention.
Args:
channels ... | 3,949 | 31.916667 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/necks/yolox_pafpn.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List
import torch.nn as nn
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmdet.models.backbones.csp_darknet import CSPLayer
from mmdet.utils import ConfigType, OptMultiConfig
from mmyolo.registry import MODELS
from .base_yolo_neck... | 5,747 | 32.225434 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/necks/yolov8_pafpn.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Union
import torch.nn as nn
from mmdet.utils import ConfigType, OptMultiConfig
from mmyolo.registry import MODELS
from .. import CSPLayerWithTwoConv
from ..utils import make_divisible, make_round
from .yolov5_pafpn import YOLOv5PAFPN
@MODELS.r... | 3,716 | 35.087379 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/necks/yolov6_pafpn.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmdet.utils import ConfigType, OptMultiConfig
from mmyolo.registry import MODELS
from ..layers import BepC3StageBlock, RepStageBlock
from ..utils import make_round
from .base... | 10,763 | 36.636364 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/necks/yolov5_pafpn.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Union
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmdet.models.backbones.csp_darknet import CSPLayer
from mmdet.utils import ConfigType, OptMultiConfig
from mmyolo.registry import MODELS
from ..utils import make_divis... | 6,273 | 35.476744 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/necks/cspnext_pafpn.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
from typing import Sequence
import torch.nn as nn
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmdet.models.backbones.csp_darknet import CSPLayer
from mmdet.utils import ConfigType, OptMultiConfig
from mmyolo.registry import MODELS
from... | 6,750 | 32.420792 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/necks/yolov7_pafpn.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmdet.utils import ConfigType, OptMultiConfig
from mmyolo.registry import MODELS
from ..layers import MaxPoolAndStrideConvBlock, RepVGGBlock, SPPFCSPBlock
from .base_yolo_neck import Base... | 7,846 | 35.16129 | 77 | py |
mmyolo | mmyolo-main/mmyolo/models/necks/base_yolo_neck.py | # Copyright (c) OpenMMLab. All rights reserved.
from abc import ABCMeta, abstractmethod
from typing import List, Union
import torch
import torch.nn as nn
from mmdet.utils import ConfigType, OptMultiConfig
from mmengine.model import BaseModule
from torch.nn.modules.batchnorm import _BatchNorm
from mmyolo.registry impo... | 11,105 | 41.389313 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/necks/ppyoloe_csppan.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmdet.utils import ConfigType, OptMultiConfig
from mmyolo.models.backbones.csp_resnet import CSPResLayer
from mmyolo.models.necks import BaseYOLONeck
from mmyolo.registry import MODELS
... | 7,704 | 34.506912 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/layers/yolo_bricks.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Optional, Sequence, Tuple, Union
import numpy as np
import torch
import torch.nn as nn
from mmcv.cnn import (ConvModule, DepthwiseSeparableConvModule, MaxPool2d,
build_norm_layer)
from mmdet.models.layers.csp_layer import \
Da... | 54,506 | 35.073461 | 156 | py |
mmyolo | mmyolo-main/mmyolo/models/layers/ema.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
from typing import Optional
import torch
import torch.nn as nn
from mmdet.models.layers import ExpMomentumEMA as MMDET_ExpMomentumEMA
from torch import Tensor
from mmyolo.registry import MODELS
@MODELS.register_module()
class ExpMomentumEMA(MMDET_ExpMoment... | 3,886 | 39.072165 | 78 | py |
mmyolo | mmyolo-main/mmyolo/models/dense_heads/rtmdet_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Sequence, Tuple
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, is_norm
from mmdet.models.task_modules.samplers import PseudoSampler
from mmdet.structures.bbox import distance2bbox
from mmdet.utils import (ConfigType, Instance... | 15,054 | 39.799458 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/dense_heads/yolov8_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
from typing import List, Sequence, Tuple, Union
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmdet.models.utils import multi_apply
from mmdet.utils import (ConfigType, OptConfigType, OptInstanceList,
OptMult... | 16,795 | 41.307305 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/dense_heads/yolov6_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Sequence, Tuple, Union
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmdet.models.utils import multi_apply
from mmdet.utils import (ConfigType, OptConfigType, OptInstanceList,
OptMultiConfig)
fro... | 15,037 | 39.643243 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/dense_heads/yolox_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Optional, Sequence, Tuple, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmdet.models.task_modules.samplers import PseudoSampler
from mmdet.models.utils... | 22,508 | 42.706796 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/dense_heads/rtmdet_ins_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
from typing import List, Optional, Tuple
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, is_norm
from mmcv.ops import batched_nms
from mmdet.models.utils import filter_scores_and_topk
from... | 30,484 | 40.990358 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/dense_heads/yolov5_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import math
from typing import List, Optional, Sequence, Tuple, Union
import torch
import torch.nn as nn
from mmdet.models.dense_heads.base_dense_head import BaseDenseHead
from mmdet.models.utils import filter_scores_and_topk, multi_apply
from mmdet.structure... | 38,981 | 42.750842 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/dense_heads/yolov7_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
from typing import List, Optional, Sequence, Tuple, Union
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmdet.models.utils import multi_apply
from mmdet.utils import ConfigType, OptInstanceList
from mmengine.dist import get_dist_info... | 17,391 | 41.94321 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/dense_heads/rtmdet_rotated_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import warnings
from typing import List, Optional, Sequence, Tuple
import torch
import torch.nn as nn
from mmdet.models.utils import filter_scores_and_topk
from mmdet.structures.bbox import HorizontalBoxes, distance2bbox
from mmdet.structures.bbox.transforms ... | 26,337 | 40.024922 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/dense_heads/ppyoloe_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Sequence, Tuple, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmdet.models.utils import multi_apply
from mmdet.utils import (ConfigType, OptConfigType, OptInstanceList,
OptMultiConfig, reduce_me... | 15,834 | 41.226667 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/utils/misc.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
from typing import Sequence, Union
import torch
from mmdet.structures.bbox.transforms import get_box_tensor
from torch import Tensor
def make_divisible(x: float,
widen_factor: float = 1.0,
divisor: int = 8) -> int:
... | 3,851 | 38.306122 | 76 | py |
mmyolo | mmyolo-main/mmyolo/models/task_modules/assigners/utils.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Tuple
import torch
import torch.nn.functional as F
from torch import Tensor
def select_candidates_in_gts(priors_points: Tensor,
gt_bboxes: Tensor,
eps: float = 1e-9) -> Tensor:
"""Select ... | 4,202 | 36.864865 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/task_modules/assigners/batch_dsl_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmdet.structures.bbox import BaseBoxes
from mmdet.utils import ConfigType
from torch import Tensor
from mmyolo.registry import TASK_UTILS
INF = 100000000
EPS = 1.0e-7
def... | 10,901 | 38.934066 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/task_modules/assigners/batch_yolov7_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Sequence
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmdet.structures.bbox import bbox_cxcywh_to_xyxy, bbox_overlaps
def _cat_multi_level_tensor_in_place(*multi_level_tensor, place_hold_var):
"""concat multi-level tens... | 14,354 | 40.608696 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/task_modules/assigners/batch_atss_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmdet.utils import ConfigType
from torch import Tensor
from mmyolo.registry import TASK_UTILS
from .utils import (select_candidates_in_gts, select_highest_overlaps,
... | 14,471 | 41.564706 | 81 | py |
mmyolo | mmyolo-main/mmyolo/models/task_modules/assigners/batch_task_aligned_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Optional, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import Tensor
from mmyolo.models.losses import bbox_overlaps
from mmyolo.registry import TASK_UTILS
from .utils import (select_candidates_in_gts, select_high... | 13,143 | 41.128205 | 78 | py |
mmyolo | mmyolo-main/mmyolo/models/task_modules/coders/distance_point_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Optional, Sequence, Union
import torch
from mmdet.models.task_modules.coders import \
DistancePointBBoxCoder as MMDET_DistancePointBBoxCoder
from mmdet.structures.bbox import bbox2distance, distance2bbox
from mmyolo.registry import TASK_UTILS
@T... | 2,948 | 35.8625 | 78 | py |
mmyolo | mmyolo-main/mmyolo/models/task_modules/coders/yolox_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Union
import torch
from mmdet.models.task_modules.coders.base_bbox_coder import BaseBBoxCoder
from mmyolo.registry import TASK_UTILS
@TASK_UTILS.register_module()
class YOLOXBBoxCoder(BaseBBoxCoder):
"""YOLOX BBox coder.
This decoder decode... | 1,477 | 31.130435 | 78 | py |
mmyolo | mmyolo-main/mmyolo/models/task_modules/coders/distance_angle_point_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Optional, Sequence, Union
import torch
from mmyolo.registry import TASK_UTILS
try:
from mmrotate.models.task_modules.coders import \
DistanceAnglePointCoder as MMROTATE_DistanceAnglePointCoder
MMROTATE_AVAILABLE = True
except ImportEr... | 3,512 | 35.978947 | 78 | py |
mmyolo | mmyolo-main/mmyolo/models/task_modules/coders/yolov5_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Union
import torch
from mmdet.models.task_modules.coders.base_bbox_coder import BaseBBoxCoder
from mmyolo.registry import TASK_UTILS
@TASK_UTILS.register_module()
class YOLOv5BBoxCoder(BaseBBoxCoder):
"""YOLOv5 BBox coder.
This decoder deco... | 1,895 | 32.857143 | 78 | py |
mmyolo | mmyolo-main/mmyolo/models/losses/iou_loss.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from mmdet.models.losses.utils import weight_reduce_loss
from mmdet.structures.bbox import HorizontalBoxes
from mmyolo.registry import MODELS
def bbox_overlaps(pred: torch.Tensor,... | 8,786 | 36.712446 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/backbones/yolov7_backbone.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Optional, Tuple, Union
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmdet.models.backbones.csp_darknet import Focus
from mmdet.utils import ConfigType, OptMultiConfig
from mmyolo.registry import MODELS
from ..layers import MaxPoolA... | 11,081 | 37.748252 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/backbones/efficient_rep.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Tuple, Union
import torch
import torch.nn as nn
from mmdet.utils import ConfigType, OptMultiConfig
from mmyolo.models.layers.yolo_bricks import SPPFBottleneck
from mmyolo.registry import MODELS
from ..layers import BepC3StageBlock, RepStageBloc... | 11,355 | 38.430556 | 78 | py |
mmyolo | mmyolo-main/mmyolo/models/backbones/csp_resnet.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Tuple, Union
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmdet.utils import ConfigType, OptMultiConfig
from mmyolo.models.backbones import BaseBackbone
from mmyolo.models.layers.yolo_bricks import CSPResLayer
from mmyolo.registry ... | 6,791 | 38.952941 | 78 | py |
mmyolo | mmyolo-main/mmyolo/models/backbones/base_backbone.py | # Copyright (c) OpenMMLab. All rights reserved.
from abc import ABCMeta, abstractmethod
from typing import List, Sequence, Union
import torch
import torch.nn as nn
from mmcv.cnn import build_plugin_layer
from mmdet.utils import ConfigType, OptMultiConfig
from mmengine.model import BaseModule
from torch.nn.modules.batc... | 7,920 | 34.048673 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/backbones/cspnext.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
from typing import List, Sequence, Union
import torch.nn as nn
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmdet.models.backbones.csp_darknet import CSPLayer
from mmdet.utils import ConfigType, OptConfigType, OptMultiConfig
from mmyolo... | 7,258 | 37.611702 | 79 | py |
mmyolo | mmyolo-main/mmyolo/models/backbones/csp_darknet.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Tuple, Union
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmdet.models.backbones.csp_darknet import CSPLayer, Focus
from mmdet.utils import ConfigType, OptMultiConfig
from mmyolo.registry ... | 17,158 | 39.091121 | 79 | py |
mmyolo | mmyolo-main/mmyolo/datasets/utils.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Sequence
import numpy as np
import torch
from mmengine.dataset import COLLATE_FUNCTIONS
from ..registry import TASK_UTILS
@COLLATE_FUNCTIONS.register_module()
def yolov5_collate(data_batch: Sequence,
use_ms_training: bool = ... | 4,075 | 34.443478 | 79 | py |
mmyolo | mmyolo-main/mmyolo/datasets/transforms/mix_img_transforms.py | # Copyright (c) OpenMMLab. All rights reserved.
import collections
import copy
from abc import ABCMeta, abstractmethod
from typing import Optional, Sequence, Tuple, Union
import mmcv
import numpy as np
from mmcv.transforms import BaseTransform
from mmdet.structures.bbox import autocast_box_type
from mmengine.dataset i... | 46,505 | 39.404865 | 79 | py |
mmyolo | mmyolo-main/mmyolo/datasets/transforms/transforms.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
from copy import deepcopy
from typing import List, Sequence, Tuple, Union
import cv2
import mmcv
import numpy as np
import torch
from mmcv.transforms import BaseTransform, Compose
from mmcv.transforms.utils import cache_randomness
from mmdet.datasets.transfor... | 59,261 | 37.037227 | 79 | py |
mmyolo | mmyolo-main/mmyolo/deploy/object_detection.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Callable, Dict, Optional
import torch
from mmdeploy.codebase.base import CODEBASE, MMCodebase
from mmdeploy.codebase.mmdet.deploy import ObjectDetection
from mmdeploy.utils import Codebase, Task
from mmengine import Config
from mmengine.registry import... | 4,523 | 33.015038 | 78 | py |
mmyolo | mmyolo-main/mmyolo/deploy/models/layers/bbox_nms.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdeploy.core import mark
from torch import Tensor
def _efficient_nms(
boxes: Tensor,
scores: Tensor,
max_output_boxes_per_class: int = 1000,
iou_threshold: float = 0.5,
score_threshold: float = 0.05,
pre_top_k: int = -1,
ke... | 3,931 | 33.491228 | 78 | py |
mmyolo | mmyolo-main/mmyolo/deploy/models/dense_heads/yolov5_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
from functools import partial
from typing import List, Optional, Tuple
import torch
from mmdeploy.codebase.mmdet import get_post_processing_params
from mmdeploy.codebase.mmdet.models.layers import multiclass_nms
from mmdeploy.core import FUNCTION_REWRITER
fro... | 7,242 | 37.121053 | 79 | py |
mmyolo | mmyolo-main/mmyolo/engine/optimizers/yolov5_optim_constructor.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Optional
import torch.nn as nn
from mmengine.dist import get_world_size
from mmengine.logging import print_log
from mmengine.model import is_model_wrapper
from mmengine.optim import OptimWrapper
from mmyolo.registry import (OPTIM_WRAPPER_CONSTRUCTORS,... | 5,201 | 38.112782 | 78 | py |
mmyolo | mmyolo-main/mmyolo/engine/optimizers/yolov7_optim_wrapper_constructor.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Optional
import torch.nn as nn
from mmengine.dist import get_world_size
from mmengine.logging import print_log
from mmengine.model import is_model_wrapper
from mmengine.optim import OptimWrapper
from mmyolo.models.dense_heads.yolov7_head import Implic... | 5,576 | 38.835714 | 78 | py |
mmyolo | mmyolo-main/mmyolo/utils/large_image.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Sequence, Tuple
import torch
from mmcv.ops import batched_nms
from mmdet.structures import DetDataSample, SampleList
from mmengine.structures import InstanceData
def shift_rbboxes(bboxes: torch.Tensor, offset: Sequence[int]):
"""Shift rotated bbo... | 3,871 | 36.230769 | 79 | py |
mmyolo | mmyolo-main/mmyolo/utils/misc.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import urllib
import numpy as np
import torch
from mmengine.utils import scandir
from prettytable import PrettyTable
from mmyolo.models import RepVGGBlock
IMG_EXTENSIONS = ('.jpg', '.jpeg', '.png', '.ppm', '.bmp', '.pgm', '.tif',
'.tiff', '.... | 4,932 | 35.813433 | 175 | py |
mmyolo | mmyolo-main/mmyolo/utils/boxam_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import bisect
import copy
import warnings
from pathlib import Path
from typing import Callable, List, Optional, Tuple, Union
import cv2
import numpy as np
import torch
import torch.nn as nn
import torchvision
from mmcv.transforms import Compose
from mmdet.evaluation impo... | 19,429 | 36.875244 | 79 | py |
DALLE-pytorch | DALLE-pytorch-main/train_dalle.py | import argparse
from pathlib import Path
import time
from glob import glob
import os
import shutil
import torch
import wandb # Quit early if user doesn't have wandb installed.
from torch.nn.utils import clip_grad_norm_
from torch.optim import Adam
from torch.optim.lr_scheduler import ReduceLROnPlateau
from torch.util... | 23,672 | 33.967504 | 199 | py |
DALLE-pytorch | DALLE-pytorch-main/setup.py | from setuptools import setup, find_packages
exec(open('dalle_pytorch/version.py').read())
setup(
name = 'dalle-pytorch',
packages = find_packages(),
include_package_data = True,
version = __version__,
license='MIT',
description = 'DALL-E - Pytorch',
author = 'Phil Wang',
author_email = 'lucidrains@gmai... | 1,149 | 23.468085 | 65 | py |
DALLE-pytorch | DALLE-pytorch-main/generate.py | import argparse
from pathlib import Path
from tqdm import tqdm
# torch
import torch
from einops import repeat
# vision imports
from PIL import Image
from torchvision.utils import make_grid, save_image
# dalle related classes and utils
from dalle_pytorch import __version__
from dalle_pytorch import DiscreteVAE, O... | 4,695 | 31.611111 | 286 | py |
DALLE-pytorch | DALLE-pytorch-main/train_vae.py | import math
from math import sqrt
import argparse
from pathlib import Path
# torch
import torch
from torch.optim import Adam
from torch.optim.lr_scheduler import ExponentialLR
# vision imports
from torchvision import transforms as T
from torch.utils.data import DataLoader
from torchvision.datasets import ImageFolde... | 9,727 | 29.117647 | 168 | py |
DALLE-pytorch | DALLE-pytorch-main/dalle_pytorch/reversible.py | import torch
import torch.nn as nn
from operator import itemgetter
from torch.autograd.function import Function
from torch.utils.checkpoint import get_device_states, set_device_states
# for routing arguments into the functions of the reversible layer
def route_args(router, args, depth):
routed_args = [(dict(), dic... | 5,390 | 33.120253 | 165 | py |
DALLE-pytorch | DALLE-pytorch-main/dalle_pytorch/dalle_pytorch.py | from math import log2, sqrt
import torch
from torch import nn, einsum
import torch.nn.functional as F
import numpy as np
from axial_positional_embedding import AxialPositionalEmbedding
from einops import rearrange
from dalle_pytorch import distributed_utils
from dalle_pytorch.vae import OpenAIDiscreteVAE, VQGanVAE
fr... | 23,608 | 34.13244 | 170 | py |
DALLE-pytorch | DALLE-pytorch-main/dalle_pytorch/vae.py | import io
import sys
import os
import requests
import PIL
import warnings
import hashlib
import urllib
import yaml
from pathlib import Path
from tqdm import tqdm
from math import sqrt, log
from packaging import version
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel, GumbelVQ
import importlib
... | 7,674 | 31.939914 | 149 | py |
DALLE-pytorch | DALLE-pytorch-main/dalle_pytorch/distributed_utils.py | """
Utility functions for optional distributed execution.
To use,
1. set the `BACKENDS` to the ones you want to make available,
2. in the script, wrap the argument parser with `wrap_arg_parser`,
3. in the script, set and use the backend by calling
`set_backend_from_args`.
You can check whether a backend is in use ... | 2,839 | 28.278351 | 79 | py |
DALLE-pytorch | DALLE-pytorch-main/dalle_pytorch/transformer.py | from collections import deque
from collections.abc import Iterable
from functools import partial
from itertools import islice, cycle
import torch
from torch import nn, einsum
import torch.nn.functional as F
from einops import rearrange
from dalle_pytorch.reversible import ReversibleSequence, SequentialSequence
from d... | 13,131 | 36.413105 | 180 | py |
DALLE-pytorch | DALLE-pytorch-main/dalle_pytorch/tokenizer.py | # take from https://github.com/openai/CLIP/blob/main/clip/simple_tokenizer.py
# to give users a quick easy start to training DALL-E without doing BPE
import torch
import youtokentome as yttm
from tokenizers import Tokenizer
from tokenizers.processors import ByteLevel
from transformers import BertTokenizer
import htm... | 9,432 | 34.329588 | 120 | py |
DALLE-pytorch | DALLE-pytorch-main/dalle_pytorch/__init__.py | from dalle_pytorch.dalle_pytorch import DALLE, CLIP, DiscreteVAE
from dalle_pytorch.vae import OpenAIDiscreteVAE, VQGanVAE
from pkg_resources import get_distribution
from dalle_pytorch.version import __version__
| 213 | 34.666667 | 64 | py |
DALLE-pytorch | DALLE-pytorch-main/dalle_pytorch/attention.py | from inspect import isfunction
from math import ceil
import torch
from torch import nn, einsum
import torch.nn.functional as F
from einops import rearrange, repeat
from rotary_embedding_torch import apply_rotary_emb
# helpers
def exists(val):
return val is not None
def uniq(arr):
return{el: True for el in ... | 14,131 | 34.418546 | 165 | py |
DALLE-pytorch | DALLE-pytorch-main/dalle_pytorch/loader.py | from pathlib import Path
from random import randint, choice
import PIL
from torch.utils.data import Dataset
from torchvision import transforms as T
class TextImageDataset(Dataset):
def __init__(self,
folder,
text_len=256,
image_size=128,
trunca... | 3,558 | 33.221154 | 112 | py |
DALLE-pytorch | DALLE-pytorch-main/dalle_pytorch/distributed_backends/deepspeed_backend.py | import json
import os
import torch
from .distributed_backend import DistributedBackend
class DeepSpeedBackend(DistributedBackend):
"""Distributed backend using the DeepSpeed engine."""
BACKEND_MODULE_NAME = 'deepspeed'
BACKEND_NAME = 'DeepSpeed'
def wrap_arg_parser(self, parser):
if not se... | 5,987 | 33.813953 | 78 | py |
DALLE-pytorch | DALLE-pytorch-main/dalle_pytorch/distributed_backends/horovod_backend.py | import torch
from .distributed_backend import DistributedBackend
class HorovodBackend(DistributedBackend):
"""Distributed backend using Horovod."""
BACKEND_MODULE_NAME = 'horovod.torch'
BACKEND_NAME = 'Horovod'
def wrap_arg_parser(self, parser):
return parser
def check_batch_size(self,... | 1,703 | 27.881356 | 71 | py |
covid-vax-stance | covid-vax-stance-main/classifier/classifier_predict.py | # Libraries
import torch
from torchtext.data import Field, TabularDataset, Iterator
import torch.nn as nn
import torch.nn.functional as F
from transformers import AutoTokenizer, BertForSequenceClassification
import os
import csv
import time
import argparse
import warnings
torch.manual_seed(42)
warnings.filterwarning... | 5,168 | 33.46 | 176 | py |
libgpuarray | libgpuarray-master/pygpu/tests/test_gpu_ndarray.py | from __future__ import print_function
import unittest
import copy
from six.moves import range
from six import PY3
import pickle
import numpy
from nose.tools import assert_raises
import pygpu
from pygpu.gpuarray import GpuArray, GpuKernel
from .support import (guard_devsup, check_meta, check_flags, check_all,
... | 26,790 | 31.162065 | 79 | py |
GENESIM | GENESIM-master/constructors/ensemble.py | """
Contains wrappers around well-known ensemble techniques: Random Forest and XGBoost.
Written by Gilles Vandewiele in commission of IDLab - INTEC from University Ghent.
"""
import time
from bayes_opt import BayesianOptimization
from sklearn.cross_validation import cross_val_score
from sklearn.ensemble import AdaBoo... | 12,560 | 38.5 | 121 | py |
WiFi-CSI-Sensing-Benchmark | WiFi-CSI-Sensing-Benchmark-main/NTU_Fi_model.py | import torch
import torchvision
import torch.nn as nn
import torch.nn.functional as F
from einops import rearrange, reduce, repeat
from einops.layers.torch import Rearrange, Reduce
class NTU_Fi_MLP(nn.Module):
def __init__(self, num_classes):
super(NTU_Fi_MLP,self).__init__()
self.fc = nn.Sequentia... | 13,031 | 32.674419 | 128 | py |
WiFi-CSI-Sensing-Benchmark | WiFi-CSI-Sensing-Benchmark-main/dataset.py | import numpy as np
import glob
import scipy.io as sio
import torch
from torch.utils.data import Dataset, DataLoader
def UT_HAR_dataset(root_dir):
data_list = glob.glob(root_dir+'/UT_HAR/data/*.csv')
label_list = glob.glob(root_dir+'/UT_HAR/label/*.csv')
WiFi_data = {}
for data_dir in data_list:
... | 3,086 | 29.564356 | 105 | py |
WiFi-CSI-Sensing-Benchmark | WiFi-CSI-Sensing-Benchmark-main/UT_HAR_model.py | import torch
import torchvision
import torch.nn as nn
import torch.nn.functional as F
from einops import rearrange, reduce, repeat
from einops.layers.torch import Rearrange, Reduce
class UT_HAR_MLP(nn.Module):
def __init__(self):
super(UT_HAR_MLP,self).__init__()
self.fc = nn.Sequential(
... | 12,505 | 32.52815 | 128 | py |
WiFi-CSI-Sensing-Benchmark | WiFi-CSI-Sensing-Benchmark-main/run.py | import numpy as np
import torch
import torch.nn as nn
import argparse
from util import load_data_n_model
def train(model, tensor_loader, num_epochs, learning_rate, criterion, device):
model = model.to(device)
optimizer = torch.optim.Adam(model.parameters(), lr = learning_rate)
for epoch in range(num_epochs... | 3,185 | 33.258065 | 140 | py |
WiFi-CSI-Sensing-Benchmark | WiFi-CSI-Sensing-Benchmark-main/self_supervised_model.py | import torch
import torch.nn as nn
from einops import rearrange, reduce, repeat
from einops.layers.torch import Rearrange, Reduce
import torch.nn.functional as F
class MLP_Parrallel(nn.Module):
def __init__(self):
super(MLP_Parrallel, self).__init__()
self.encoder_1 = MLP_encoder()
self.en... | 20,995 | 30.763994 | 128 | py |
WiFi-CSI-Sensing-Benchmark | WiFi-CSI-Sensing-Benchmark-main/util.py | from dataset import *
from UT_HAR_model import *
from NTU_Fi_model import *
from widar_model import *
from self_supervised_model import *
import torch
def load_data_n_model(dataset_name, model_name, root):
classes = {'UT_HAR_data':7,'NTU-Fi-HumanID':14,'NTU-Fi_HAR':6,'Widar':22}
if dataset_name == 'UT_HAR_data... | 10,985 | 41.416988 | 140 | py |
WiFi-CSI-Sensing-Benchmark | WiFi-CSI-Sensing-Benchmark-main/widar_model.py | import torch
import torchvision
import torch.nn as nn
import torch.nn.functional as F
from einops import rearrange, reduce, repeat
from einops.layers.torch import Rearrange, Reduce
class Widar_MLP(nn.Module):
def __init__(self, num_classes):
super(Widar_MLP,self).__init__()
self.fc = nn.Sequential(... | 12,936 | 32.866492 | 128 | py |
WiFi-CSI-Sensing-Benchmark | WiFi-CSI-Sensing-Benchmark-main/self_supervised.py | import torch
import torch.optim as optim
import random
import torch.nn as nn
from util import load_unsupervised_data_n_model
import argparse
from torch.autograd import Variable
class EntLoss(nn.Module):
def __init__(self, args, lam1, lam2, pqueue=None):
super(EntLoss, self).__init__()
self.lam1 = ... | 8,839 | 39.365297 | 139 | py |
deficient-efficient | deficient-efficient-master/main.py | ''''Writing everything into one script..'''
from __future__ import print_function
import os
import imp
import sys
import time
import json
import argparse
import torch
import torch.nn as nn
import torch.optim as optim
import torch.optim.lr_scheduler as lr_scheduler
import torch.nn.functional as F
import torchvision
impo... | 25,508 | 39.426307 | 141 | py |
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