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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RNPRF-RNDFF-RNPMF | RNPRF-RNDFF-RNPMF-master/Houston_code/SSRN_Houston_HSI.py | #Write by Chiru Ge, contact: gechiru@126.com
# use CPU only
#import os
#import sys
#os.environ["CUDA_DEVICE_ORDER"]="PCA_BUS_ID"
#os.environ["CUDA_VISIBLE_DEVICES"]="0"
#import tensorflow as tf
#sess = tf.Session(config=tf.ConfigProto(device_count={'gpu':-1}))
#use GPU
import os
import tensorflow as tf
#tf.device... | 11,030 | 39.704797 | 203 | py |
RNPRF-RNDFF-RNPMF | RNPRF-RNDFF-RNPMF-master/Houston_code/SSRN_Houston_LiDAR_EPLBP.py | #Write by Chiru Ge, contact: gechiru@126.com
## use CPU only
#import os
#import sys
#os.environ["CUDA_DEVICE_ORDER"]="PCA_BUS_ID"
#os.environ["CUDA_VISIBLE_DEVICES"]="-1"
## use GPU
import os
import tensorflow as tf
os.environ['CUDA_VISIBLE_DEVICES']='0'
config=tf.ConfigProto()
config.gpu_options.allow_growth= True... | 10,865 | 40.003774 | 203 | py |
RNPRF-RNDFF-RNPMF | RNPRF-RNDFF-RNPMF-master/Houston_code/SSRN_Houston_stack_all.py | #Write by Chiru Ge, contact: gechiru@126.com
# HSI ++ Resnet
# use CPU only
#import os
#import sys
#os.environ["CUDA_DEVICE_ORDER"]="PCA_BUS_ID"
#os.environ["CUDA_VISIBLE_DEVICES"]="0"
#import tensorflow as tf
#sess = tf.Session(config=tf.ConfigProto(device_count={'gpu':-1}))
#use GPU
import os
import tensorflow... | 11,127 | 39.318841 | 203 | py |
RNPRF-RNDFF-RNPMF | RNPRF-RNDFF-RNPMF-master/Houston_code/SSRN_Houston_HSI_EPLBP.py | #Write by Chiru Ge, contact: gechiru@126.com
# HSI_EPLBP ++ Resnet
### use CPU only
#import os
#import sys
#os.environ["CUDA_DEVICE_ORDER"]="PCA_BUS_ID"
#os.environ["CUDA_VISIBLE_DEVICES"]="-1"
# use GPU
import os
import tensorflow as tf
os.environ['CUDA_VISIBLE_DEVICES']='0'
config=tf.ConfigProto()
config.gpu_opt... | 10,906 | 39.396296 | 203 | py |
RNPRF-RNDFF-RNPMF | RNPRF-RNDFF-RNPMF-master/Mapping/Houston/Houston_classification_maps_LiDAR_EPLBP.py | #Write by Chiru Ge, contact: gechiru@126.com
# -*- coding: utf-8 -*-
## use GPU
import os
import tensorflow as tf
os.environ['CUDA_VISIBLE_DEVICES']='0'
config=tf.ConfigProto()
config.gpu_options.allow_growth= True
sess=tf.Session(config=config)
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as si... | 6,404 | 33.251337 | 131 | py |
RNPRF-RNDFF-RNPMF | RNPRF-RNDFF-RNPMF-master/Mapping/Houston/Houston_classification_maps_HSI_EPLBP.py | #Write by Chiru Ge, contact: gechiru@126.com
# -*- coding: utf-8 -*-
## use GPU
import os
import tensorflow as tf
os.environ['CUDA_VISIBLE_DEVICES']='0'
config=tf.ConfigProto()
config.gpu_options.allow_growth= True
sess=tf.Session(config=config)
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as si... | 6,435 | 32.520833 | 129 | py |
RNPRF-RNDFF-RNPMF | RNPRF-RNDFF-RNPMF-master/Mapping/Houston/Houston_classification_maps_3F.py | #Write by Chiru Ge, contact: gechiru@126.com
# -*- coding: utf-8 -*-
## use GPU
import os
import tensorflow as tf
os.environ['CUDA_VISIBLE_DEVICES']='0'
config=tf.ConfigProto()
config.gpu_options.allow_growth= True
sess=tf.Session(config=config)
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as si... | 8,729 | 39.604651 | 164 | py |
RNPRF-RNDFF-RNPMF | RNPRF-RNDFF-RNPMF-master/Mapping/Houston/Houston_classification_maps_HSI.py | #Write by Chiru Ge, contact: gechiru@126.com
# -*- coding: utf-8 -*-
## use GPU
import os
import tensorflow as tf
os.environ['CUDA_VISIBLE_DEVICES']='0'
config=tf.ConfigProto()
config.gpu_options.allow_growth= True
sess=tf.Session(config=config)
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as si... | 6,384 | 33.144385 | 125 | py |
RNPRF-RNDFF-RNPMF | RNPRF-RNDFF-RNPMF-master/Mapping/Houston/Houston_classification_maps_stack.py | #Write by Chiru Ge, contact: gechiru@126.com
# -*- coding: utf-8 -*-
## use GPU
import os
import tensorflow as tf
os.environ['CUDA_VISIBLE_DEVICES']='0'
config=tf.ConfigProto()
config.gpu_options.allow_growth= True
sess=tf.Session(config=config)
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as si... | 6,356 | 32.994652 | 132 | py |
RNPRF-RNDFF-RNPMF | RNPRF-RNDFF-RNPMF-master/Mapping/Houston/Houston_classification_maps_stackall.py | #Write by Chiru Ge, contact: gechiru@126.com
# -*- coding: utf-8 -*-
## use GPU
import os
import tensorflow as tf
os.environ['CUDA_VISIBLE_DEVICES']='0'
config=tf.ConfigProto()
config.gpu_options.allow_growth= True
sess=tf.Session(config=config)
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as si... | 6,400 | 32.513089 | 135 | py |
PAIR-Diffusion | PAIR-Diffusion-main/gradio_app.py |
import einops
import gradio as gr
import numpy as np
import torch
import random
import os
import subprocess
import shlex
from huggingface_hub import hf_hub_url, hf_hub_download
from share import *
from pytorch_lightning import seed_everything
from annotator.util import resize_image, HWC3
from annotator.OneFormer im... | 18,346 | 43.423729 | 200 | py |
PAIR-Diffusion | PAIR-Diffusion-main/cldm/hack.py | import torch
import einops
import ldm.modules.encoders.modules
import ldm.modules.attention
from transformers import logging
from ldm.modules.attention import default
def disable_verbosity():
logging.set_verbosity_error()
print('logging improved.')
return
def enable_sliced_attention():
ldm.modules... | 3,567 | 30.857143 | 100 | py |
PAIR-Diffusion | PAIR-Diffusion-main/cldm/ddim_hacked.py | """SAMPLING ONLY."""
import torch
import numpy as np
from tqdm import tqdm
from ldm.modules.diffusionmodules.util import make_ddim_sampling_parameters, make_ddim_timesteps, noise_like, extract_into_tensor
class DDIMSampler(object):
def __init__(self, model, schedule="linear", **kwargs):
super().__init__... | 19,556 | 51.013298 | 153 | py |
PAIR-Diffusion | PAIR-Diffusion-main/cldm/model.py | import os
import torch
from omegaconf import OmegaConf
from ldm.util import instantiate_from_config
def get_state_dict(d):
return d.get('state_dict', d)
def load_state_dict(ckpt_path, location='cpu'):
_, extension = os.path.splitext(ckpt_path)
if extension.lower() == ".safetensors":
import safe... | 961 | 27.294118 | 95 | py |
PAIR-Diffusion | PAIR-Diffusion-main/cldm/logger.py | import os
import numpy as np
import torch
import torchvision
from PIL import Image
from pytorch_lightning.callbacks import Callback
import pytorch_lightning as pl
from pytorch_lightning.utilities.distributed import rank_zero_only
from omegaconf import OmegaConf
# class ImageLogger(Callback):
# def __init__(self, ... | 10,091 | 42.313305 | 107 | py |
PAIR-Diffusion | PAIR-Diffusion-main/cldm/data.py | import os
import torch
import pytorch_lightning as pl
from omegaconf import OmegaConf
from functools import partial
from ldm.util import instantiate_from_config
from torch.utils.data import random_split, DataLoader, Dataset, Subset
class WrappedDataset(Dataset):
"""Wraps an arbitrary object with __len__ and __geti... | 4,077 | 40.191919 | 103 | py |
PAIR-Diffusion | PAIR-Diffusion-main/cldm/cldm.py | import einops
import torch
import torch as th
import torch.nn as nn
import math
from ldm.modules.diffusionmodules.util import (
conv_nd,
linear,
zero_module,
timestep_embedding,
)
import torchvision
from einops import rearrange, repeat
from torchvision.utils import make_grid
from ldm.modules.attention ... | 29,034 | 44.085404 | 145 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/datasets/custom_datasets/instance_oneformer_custom_dataset_mapper.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/data/dataset_mappers/mask_former_instance_dataset_mapper.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# ---------------------------------... | 9,218 | 36.47561 | 142 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/datasets/custom_datasets/instance_coco_custom_dataset_mapper.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/data/dataset_mappers/coco_instance_new_baseline_dataset_mapper.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# ---------------------------... | 8,680 | 35.783898 | 148 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/datasets/custom_datasets/semantic_oneformer_custom_dataset_mapper.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/data/dataset_mappers/mask_former_semantic_dataset_mapper.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# ---------------------------------... | 9,039 | 36.824268 | 142 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/demo/defaults.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/detectron2/blob/main/detectron2/engine/defaults.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# ----------------------------------------------------------------------------... | 3,372 | 40.134146 | 99 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/test_time_augmentation.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/test_time_augmentation.py
# ------------------------------------------------------------------------------
import copy
import logging
from itertools import... | 4,099 | 37.317757 | 108 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/oneformer_model.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/maskformer_model.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# -------------------------------------------------------------------------... | 21,761 | 43.777778 | 149 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/datasetmapper_tta.py | import copy
import numpy as np
from typing import List
import torch
from fvcore.transforms import NoOpTransform
from torch import nn
from detectron2.config import configurable
from detectron2.data.transforms import (
RandomFlip,
ResizeShortestEdge,
ResizeTransform,
apply_augmentations,
)
__all__ = ["D... | 3,165 | 34.977273 | 94 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/evaluation/cityscapes_evaluation.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/detectron2/blob/main/detectron2/evaluation/cityscapes_evaluation.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# -----------------------------------------------------------... | 8,659 | 41.871287 | 139 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/evaluation/evaluator.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/detectron2/blob/main/detectron2/evaluation/evaluator.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# -----------------------------------------------------------------------... | 8,434 | 35.834061 | 104 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/evaluation/detection_coco_evaluator.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/detectron2/blob/main/detectron2/evaluation/coco_evaluation.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# -----------------------------------------------------------------... | 30,561 | 41.271093 | 168 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/evaluation/instance_evaluation.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/evaluation/instance_evaluation.py
# ------------------------------------------------------------------------------
import contextlib
import copy
import io
... | 4,854 | 42.738739 | 116 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/evaluation/coco_evaluator.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/detectron2/blob/main/detectron2/evaluation/coco_evaluation.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# -----------------------------------------------------------------... | 24,186 | 41.960924 | 168 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/utils/events.py | import os
import wandb
from detectron2.utils import comm
from detectron2.utils.events import EventWriter, get_event_storage
def setup_wandb(cfg, args):
if comm.is_main_process():
init_args = {
k.lower(): v
for k, v in cfg.WANDB.items()
if isinstance(k, str) and k not in... | 3,989 | 32.25 | 95 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/utils/pos_embed.py | # --------------------------------------------------------
# Position embedding utils
# --------------------------------------------------------
from typing import Tuple
import numpy as np
import torch
# --------------------------------------------------------
# 2D sine-cosine position embedding
# References:
# Tra... | 4,836 | 38.325203 | 107 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/utils/misc.py | # Copyright (c) Facebook, Inc. and its affiliates.
# Modified by Bowen Cheng from https://github.com/facebookresearch/detr/blob/master/util/misc.py
"""
Misc functions, including distributed helpers.
Mostly copy-paste from torchvision references.
"""
from typing import List, Optional
import torch
import torch.distribu... | 7,486 | 36.813131 | 96 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/utils/box_ops.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Utilities for bounding box manipulation and GIoU.
"""
import torch, os
from torchvision.ops.boxes import box_area
def box_cxcywh_to_xyxy(x):
x_c, y_c, w, h = x.unbind(-1)
b = [(x_c - 0.5 * w), (y_c - 0.5 * h),
(x_c + 0.5 * w),... | 3,885 | 28.218045 | 110 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/data/tokenizer.py | # -------------------------------------------------------------------------
# MIT License
#
# Copyright (c) 2021 OpenAI
#
# 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, ... | 7,122 | 35.906736 | 120 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/data/build.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/detectron2/blob/main/detectron2/data/build.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# ------------------------------------------------------------------------------
f... | 4,563 | 36.719008 | 100 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/data/dataset_mappers/dataset_mapper.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/detectron2/blob/main/detectron2/data/dataset_mapper.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# ------------------------------------------------------------------------... | 8,867 | 42.684729 | 103 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/data/dataset_mappers/coco_unified_new_baseline_dataset_mapper.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/data/dataset_mappers/coco_panoptic_new_baseline_dataset_mapper.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# ---------------------------... | 13,714 | 39.102339 | 148 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/data/dataset_mappers/oneformer_unified_dataset_mapper.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/data/dataset_mappers/mask_former_panoptic_dataset_mapper.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# ---------------------------------... | 15,428 | 40.034574 | 142 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/matcher.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/modeling/matcher.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# -------------------------------------------------------------------------... | 8,248 | 37.7277 | 115 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/criterion.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/modeling/criterion.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# -----------------------------------------------------------------------... | 13,385 | 39.563636 | 128 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/backbone/swin.py | # --------------------------------------------------------
# Swin Transformer
# Copyright (c) 2021 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ze Liu, Yutong Lin, Yixuan Wei
# --------------------------------------------------------
# Copyright (c) Facebook, Inc. and its affiliate... | 27,476 | 34.638132 | 157 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/backbone/dinat.py | # --------------------------------------------------------
# Neighborhood Attention Transformer
# Licensed under The MIT License
# Written by Ali Hassani
# --------------------------------------------------------
# Modified by Jitesh Jain
import torch
import torch.nn as nn
from timm.models.layers import DropPath
from... | 10,506 | 34.377104 | 111 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/backbone/convnext.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from functools import partial
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.models.layer... | 8,191 | 37.280374 | 112 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/meta_arch/oneformer_head.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/modeling/meta_arch/mask_former_head.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# ------------------------------------------------------... | 6,000 | 43.125 | 127 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/transformer_decoder/text_transformer.py | # -------------------------------------------------------------------------
# MIT License
#
# Copyright (c) 2021 OpenAI
#
# 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, ... | 9,225 | 34.898833 | 125 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/transformer_decoder/position_encoding.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/modeling/transformer_decoder/position_encoding.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# -------------------------------------------... | 2,709 | 38.852941 | 132 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/transformer_decoder/oneformer_transformer_decoder.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/modeling/transformer_decoder/mask2former_transformer_decoder.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# -----------------------------... | 20,427 | 37.689394 | 180 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/transformer_decoder/transformer.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/modeling/transformer_decoder/transformer.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# -------------------------------------------------... | 12,282 | 31.580902 | 126 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/pixel_decoder/msdeformattn.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/modeling/pixel_decoder/msdeformattn.py
# Modified by Jitesh Jain (https://github.com/praeclarumjj3)
# ------------------------------------------------------... | 15,659 | 42.140496 | 132 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/pixel_decoder/fpn.py | # ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/Mask2Former/blob/main/mask2former/modeling/pixel_decoder/fpn.py
# ------------------------------------------------------------------------------
import logging
import numpy as np
from typing... | 12,627 | 39.088889 | 122 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/pixel_decoder/ops/test.py | # ------------------------------------------------------------------------------------------------
# Deformable DETR
# Copyright (c) 2020 SenseTime. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 [see LICENSE for details]
# -------------------------------------------------------------------------... | 4,223 | 44.419355 | 172 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/pixel_decoder/ops/setup.py | # ------------------------------------------------------------------------------------------------
# Deformable DETR
# Copyright (c) 2020 SenseTime. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 [see LICENSE for details]
# -------------------------------------------------------------------------... | 3,038 | 37.468354 | 139 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/pixel_decoder/ops/functions/ms_deform_attn_func.py | # ------------------------------------------------------------------------------------------------
# Deformable DETR
# Copyright (c) 2020 SenseTime. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 [see LICENSE for details]
# -------------------------------------------------------------------------... | 3,841 | 49.552632 | 138 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/pixel_decoder/ops/functions/__init__.py | # ------------------------------------------------------------------------------------------------
# Deformable DETR
# Copyright (c) 2020 SenseTime. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 [see LICENSE for details]
# -------------------------------------------------------------------------... | 598 | 53.454545 | 98 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/pixel_decoder/ops/modules/__init__.py | # ------------------------------------------------------------------------------------------------
# Deformable DETR
# Copyright (c) 2020 SenseTime. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 [see LICENSE for details]
# -------------------------------------------------------------------------... | 585 | 52.272727 | 98 | py |
PAIR-Diffusion | PAIR-Diffusion-main/annotator/OneFormer/oneformer/modeling/pixel_decoder/ops/modules/ms_deform_attn.py | # ------------------------------------------------------------------------------------------------
# Deformable DETR
# Copyright (c) 2020 SenseTime. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 [see LICENSE for details]
# -------------------------------------------------------------------------... | 6,747 | 52.133858 | 153 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/util.py | import importlib
import torch
from torch import optim
import numpy as np
from inspect import isfunction
from PIL import Image, ImageDraw, ImageFont
def log_txt_as_img(wh, xc, size=10):
# wh a tuple of (width, height)
# xc a list of captions to plot
b = len(xc)
txts = list()
for bi in range(b):
... | 7,227 | 35.690355 | 119 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/ema.py | import torch
from torch import nn
class LitEma(nn.Module):
def __init__(self, model, decay=0.9999, use_num_upates=True):
super().__init__()
if decay < 0.0 or decay > 1.0:
raise ValueError('Decay must be between 0 and 1')
self.m_name2s_name = {}
self.register_buffer('de... | 3,110 | 37.407407 | 102 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/attention.py | from inspect import isfunction
import math
import torch
import torch.nn.functional as F
from torch import nn, einsum
from einops import rearrange, repeat
from typing import Optional, Any
from ldm.modules.diffusionmodules.util import checkpoint
try:
import xformers
import xformers.ops
XFORMERS_IS_AVAILBLE... | 11,806 | 33.523392 | 143 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/midas/utils.py | """Utils for monoDepth."""
import sys
import re
import numpy as np
import cv2
import torch
def read_pfm(path):
"""Read pfm file.
Args:
path (str): path to file
Returns:
tuple: (data, scale)
"""
with open(path, "rb") as file:
color = None
width = None
heig... | 4,582 | 23.121053 | 88 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/midas/api.py | # based on https://github.com/isl-org/MiDaS
import cv2
import torch
import torch.nn as nn
from torchvision.transforms import Compose
from ldm.modules.midas.midas.dpt_depth import DPTDepthModel
from ldm.modules.midas.midas.midas_net import MidasNet
from ldm.modules.midas.midas.midas_net_custom import MidasNet_small
fr... | 5,338 | 30.222222 | 103 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/midas/midas/base_model.py | import torch
class BaseModel(torch.nn.Module):
def load(self, path):
"""Load model from file.
Args:
path (str): file path
"""
parameters = torch.load(path, map_location=torch.device('cpu'))
if "optimizer" in parameters:
parameters = parameters["mod... | 367 | 20.647059 | 71 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/midas/midas/midas_net.py | """MidashNet: Network for monocular depth estimation trained by mixing several datasets.
This file contains code that is adapted from
https://github.com/thomasjpfan/pytorch_refinenet/blob/master/pytorch_refinenet/refinenet/refinenet_4cascade.py
"""
import torch
import torch.nn as nn
from .base_model import BaseModel
f... | 2,709 | 34.194805 | 130 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/midas/midas/vit.py | import torch
import torch.nn as nn
import timm
import types
import math
import torch.nn.functional as F
class Slice(nn.Module):
def __init__(self, start_index=1):
super(Slice, self).__init__()
self.start_index = start_index
def forward(self, x):
return x[:, self.start_index :]
class... | 14,625 | 28.727642 | 96 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/midas/midas/dpt_depth.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from .base_model import BaseModel
from .blocks import (
FeatureFusionBlock,
FeatureFusionBlock_custom,
Interpolate,
_make_encoder,
forward_vit,
)
def _make_fusion_block(features, use_bn):
return FeatureFusionBlock_custom(
... | 3,154 | 27.681818 | 89 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/midas/midas/midas_net_custom.py | """MidashNet: Network for monocular depth estimation trained by mixing several datasets.
This file contains code that is adapted from
https://github.com/thomasjpfan/pytorch_refinenet/blob/master/pytorch_refinenet/refinenet/refinenet_4cascade.py
"""
import torch
import torch.nn as nn
from .base_model import BaseModel
f... | 5,207 | 39.6875 | 168 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/midas/midas/blocks.py | import torch
import torch.nn as nn
from .vit import (
_make_pretrained_vitb_rn50_384,
_make_pretrained_vitl16_384,
_make_pretrained_vitb16_384,
forward_vit,
)
def _make_encoder(backbone, features, use_pretrained, groups=1, expand=False, exportable=True, hooks=None, use_vit_only=False, use_readout="ign... | 9,242 | 25.947522 | 150 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/distributions/distributions.py | import torch
import numpy as np
class AbstractDistribution:
def sample(self):
raise NotImplementedError()
def mode(self):
raise NotImplementedError()
class DiracDistribution(AbstractDistribution):
def __init__(self, value):
self.value = value
def sample(self):
retur... | 2,970 | 30.946237 | 131 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/image_degradation/bsrgan.py | # -*- coding: utf-8 -*-
"""
# --------------------------------------------
# Super-Resolution
# --------------------------------------------
#
# Kai Zhang (cskaizhang@gmail.com)
# https://github.com/cszn
# From 2019/03--2021/08
# --------------------------------------------
"""
import numpy as np
import cv2
import tor... | 25,198 | 33.471956 | 147 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/image_degradation/bsrgan_light.py | # -*- coding: utf-8 -*-
import numpy as np
import cv2
import torch
from functools import partial
import random
from scipy import ndimage
import scipy
import scipy.stats as ss
from scipy.interpolate import interp2d
from scipy.linalg import orth
import albumentations
import ldm.modules.image_degradation.utils_image as ... | 22,341 | 33.266871 | 147 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/image_degradation/utils_image.py | import os
import math
import random
import numpy as np
import torch
import cv2
from torchvision.utils import make_grid
from datetime import datetime
#import matplotlib.pyplot as plt # TODO: check with Dominik, also bsrgan.py vs bsrgan_light.py
os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE"
'''
# ----------------------... | 29,022 | 30.684498 | 107 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/encoders/modules.py | import torch
import torch.nn as nn
from torch.utils.checkpoint import checkpoint
from transformers import T5Tokenizer, T5EncoderModel, CLIPTokenizer, CLIPTextModel
import open_clip
from ldm.util import default, count_params
class AbstractEncoder(nn.Module):
def __init__(self):
super().__init__()
de... | 7,611 | 34.570093 | 153 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/diffusionmodules/upscaling.py | import torch
import torch.nn as nn
import numpy as np
from functools import partial
from ldm.modules.diffusionmodules.util import extract_into_tensor, make_beta_schedule
from ldm.util import default
class AbstractLowScaleModel(nn.Module):
# for concatenating a downsampled image to the latent representation
d... | 3,424 | 40.768293 | 110 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/diffusionmodules/model.py | # pytorch_diffusion + derived encoder decoder
import math
import torch
import torch.nn as nn
import numpy as np
from einops import rearrange
from typing import Optional, Any
from ldm.modules.attention import MemoryEfficientCrossAttention
try:
import xformers
import xformers.ops
XFORMERS_IS_AVAILBLE = True... | 34,384 | 39.310668 | 138 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/diffusionmodules/openaimodel.py | from abc import abstractmethod
import math
import numpy as np
import torch as th
import torch.nn as nn
import torch.nn.functional as F
from ldm.modules.diffusionmodules.util import (
checkpoint,
conv_nd,
linear,
avg_pool_nd,
zero_module,
normalization,
timestep_embedding,
)
from ldm.module... | 30,371 | 37.592122 | 143 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/modules/diffusionmodules/util.py | # adopted from
# https://github.com/openai/improved-diffusion/blob/main/improved_diffusion/gaussian_diffusion.py
# and
# https://github.com/lucidrains/denoising-diffusion-pytorch/blob/7706bdfc6f527f58d33f84b7b522e61e6e3164b3/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py
# and
# https://github.com/openai/gu... | 9,868 | 35.551852 | 164 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/models/autoencoder.py | import torch
import pytorch_lightning as pl
import torch.nn.functional as F
from contextlib import contextmanager
from ldm.modules.diffusionmodules.model import Encoder, Decoder
from ldm.modules.distributions.distributions import DiagonalGaussianDistribution
from ldm.util import instantiate_from_config
from ldm.modul... | 8,560 | 37.913636 | 116 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/models/diffusion/ddim.py | """SAMPLING ONLY."""
import torch
import numpy as np
from tqdm import tqdm
from ldm.modules.diffusionmodules.util import make_ddim_sampling_parameters, make_ddim_timesteps, noise_like, extract_into_tensor
class DDIMSampler(object):
def __init__(self, model, schedule="linear", **kwargs):
super().__init__... | 17,304 | 50.502976 | 136 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/models/diffusion/ddpm.py | """
wild mixture of
https://github.com/lucidrains/denoising-diffusion-pytorch/blob/7706bdfc6f527f58d33f84b7b522e61e6e3164b3/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py
https://github.com/openai/improved-diffusion/blob/e94489283bb876ac1477d5dd7709bbbd2d9902ce/improved_diffusion/gaussian_diffusion.py
https... | 84,659 | 46.085651 | 162 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/models/diffusion/plms.py | """SAMPLING ONLY."""
import torch
import numpy as np
from tqdm import tqdm
from functools import partial
from ldm.modules.diffusionmodules.util import make_ddim_sampling_parameters, make_ddim_timesteps, noise_like
from ldm.models.diffusion.sampling_util import norm_thresholding
class PLMSSampler(object):
def __... | 12,927 | 51.767347 | 131 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/models/diffusion/sampling_util.py | import torch
import numpy as np
def append_dims(x, target_dims):
"""Appends dimensions to the end of a tensor until it has target_dims dimensions.
From https://github.com/crowsonkb/k-diffusion/blob/master/k_diffusion/utils.py"""
dims_to_append = target_dims - x.ndim
if dims_to_append < 0:
rais... | 753 | 33.272727 | 100 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/models/diffusion/dpm_solver/dpm_solver.py | import torch
import torch.nn.functional as F
import math
from tqdm import tqdm
class NoiseScheduleVP:
def __init__(
self,
schedule='discrete',
betas=None,
alphas_cumprod=None,
continuous_beta_0=0.1,
continuous_beta_1=20.,
):
"""Cr... | 65,968 | 56.165511 | 308 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/models/diffusion/dpm_solver/sampler.py | """SAMPLING ONLY."""
import torch
from .dpm_solver import NoiseScheduleVP, model_wrapper, DPM_Solver
MODEL_TYPES = {
"eps": "noise",
"v": "v"
}
class DPMSolverSampler(object):
def __init__(self, model, **kwargs):
super().__init__()
self.model = model
to_torch = lambda x: x.clone... | 2,990 | 33.37931 | 122 | py |
PAIR-Diffusion | PAIR-Diffusion-main/ldm/data/util.py | import torch
from ldm.modules.midas.api import load_midas_transform
class AddMiDaS(object):
def __init__(self, model_type):
super().__init__()
self.transform = load_midas_transform(model_type)
def pt2np(self, x):
x = ((x + 1.0) * .5).detach().cpu().numpy()
return x
def n... | 629 | 25.25 | 62 | py |
revisiting-transfer | revisiting-transfer-main/src/fine-tuning.py | #!/usr/bin/env python
# coding: utf-8
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--base", type=str, help="choose RadImageNet or ImageNet")
parser.add_argument(
"--target", type=str, help="choose isic, chest, pcam-middle, thyroid, breast"
)
parser.add_argument("--k", type=int, help="whi... | 9,275 | 27.897196 | 102 | py |
revisiting-transfer | revisiting-transfer-main/src/filter_plot.py | from matplotlib import pyplot as plt
import matplotlib.gridspec as gridspec
import pandas as pd
import numpy as np
import pickle
from tensorflow.keras import backend as K
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.applications.imagenet_utils import preprocess_input
from te... | 3,481 | 31.849057 | 82 | py |
revisiting-transfer | revisiting-transfer-main/src/CCA.py | import pandas as pd
import numpy as np
import pickle
from tensorflow.keras import backend as K
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.applications.imagenet_utils import preprocess_input
from tensorflow.keras.applications import ResNet50
from keras.models import load_mo... | 5,251 | 34.972603 | 88 | py |
revisiting-transfer | revisiting-transfer-main/src/base_AUC.py | from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.applications.imagenet_utils import preprocess_input
from keras.models import load_model
from matplotlib import pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import argparse
from io_fun.data_import impo... | 2,036 | 33.525424 | 85 | py |
revisiting-transfer | revisiting-transfer-main/src/prediction_similarity.py | from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.applications.imagenet_utils import preprocess_input
from keras.models import load_model
from matplotlib import pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import argparse
from io_fun.data_import impo... | 4,682 | 35.023077 | 86 | py |
revisiting-transfer | revisiting-transfer-main/src/io_fun/pcam_converter.py | import numpy as np
from keras.utils import HDF5Matrix
import imageio
# set data paths
train_img_path = "../../data/PCam_raw/camelyonpatch_level_2_split_train_x.h5"
train_label_path = "../../data/PCam_raw/camelyonpatch_level_2_split_train_y.h5"
val_img_path = "../../data/PCam_raw/camelyonpatch_level_2_split_valid_x.h5"... | 2,454 | 32.175676 | 86 | py |
revisiting-transfer | revisiting-transfer-main/src/io_fun/data_import.py | import pandas as pd
import os
import numpy as np
from sklearn.model_selection import train_test_split
from .data_paths import get_path
from sklearn import preprocessing
import cv2
from numpy.random import seed
import tensorflow as tf
# set seeds for reproducibility
seed(1)
tf.random.set_seed(2)
def import_ISIC(img_d... | 19,322 | 37.879276 | 173 | py |
StARformer | StARformer-main/gym/experiment.py | import os
import gym
import numpy as np
import torch
import wandb
import argparse
import pickle
import random
import sys
from datetime import datetime
import setproctitle
from evaluation.evaluate_episodes import evaluate_episode, evaluate_episode_rtg
from models.decision_transformer import DecisionTransformer
from mo... | 15,962 | 41.342175 | 168 | py |
StARformer | StARformer-main/gym/evaluation/evaluate_episodes.py | import numpy as np
import torch
def evaluate_episode(
env,
state_dim,
act_dim,
model,
max_ep_len=1000,
device='cuda',
target_return=None,
mode='normal',
state_mean=0.,
state_std=1.,
):
model.eval()
model.to(device=device)
wi... | 4,814 | 31.755102 | 106 | py |
StARformer | StARformer-main/gym/training/seq_trainer.py | import numpy as np
import torch
from training.trainer import Trainer
class SequenceTrainer(Trainer):
def train_step(self):
states, actions, rewards, action_target, mask, rtg, timesteps = self.get_batch(self.batch_size)
# action_target = torch.clone(actions)
state_preds, action_preds, re... | 1,118 | 30.971429 | 121 | py |
StARformer | StARformer-main/gym/training/act_trainer.py | import numpy as np
import torch
from training.trainer import Trainer
class ActTrainer(Trainer):
def train_step(self):
states, actions, rewards, dones, rtg, _, attention_mask = self.get_batch(self.batch_size)
state_target, action_target, reward_target = torch.clone(states), torch.clone(actions), ... | 959 | 31 | 116 | py |
StARformer | StARformer-main/gym/training/trainer.py | import numpy as np
import torch
import time
class Trainer:
def __init__(self, model, optimizer, batch_size, get_batch, loss_fn, scheduler=None, eval_fns=None):
self.model = model
self.optimizer = optimizer
self.batch_size = batch_size
self.get_batch = get_batch
self.loss_... | 2,476 | 30.35443 | 116 | py |
StARformer | StARformer-main/gym/models/model.py | import numpy as np
import torch
import torch.nn as nn
class TrajectoryModel(nn.Module):
def __init__(self, state_dim, act_dim, max_length=None):
super().__init__()
self.state_dim = state_dim
self.act_dim = act_dim
self.max_length = max_length
def forward(self, states, action... | 638 | 28.045455 | 81 | py |
StARformer | StARformer-main/gym/models/trajectory_gpt2.py | # coding=utf-8
# Copyright 2018 The OpenAI Team Authors and HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License... | 35,866 | 45.220361 | 180 | py |
StARformer | StARformer-main/gym/models/starformer.py | from einops import rearrange, repeat
from einops.layers.torch import Rearrange
import torch
import torch.nn as nn
import torch.nn.functional as F
import math
from timm.models.layers import trunc_normal_
class GELU(nn.Module):
def __init__(self):
super().__init__()
def forward(self, inpu... | 19,721 | 42.72949 | 151 | py |
StARformer | StARformer-main/gym/models/mlp_bc.py | import numpy as np
import torch
import torch.nn as nn
from models.model import TrajectoryModel
class MLPBCModel(TrajectoryModel):
"""
Simple MLP that predicts next action a from past states s.
"""
def __init__(self, state_dim, act_dim, hidden_size, n_layer, dropout=0.1, max_length=1, **kwargs):
... | 1,722 | 32.134615 | 102 | py |
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