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__init__.py
drzeeshanahmed_IntelliGenes/intelligenes/__init__.py
from . import intelligenes from . import selection from . import classification
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selection.py
drzeeshanahmed_IntelliGenes/intelligenes/selection.py
# (Packages/Libraries) Matrix Manipulation import pandas as pd # (Packages/Libraries) Statistical Analysis & Machine Learning from sklearn.model_selection import train_test_split from sklearn.preprocessing import MinMaxScaler from sklearn.feature_selection import SelectKBest, chi2, f_classif, RFE from sklearn....
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test.py
Hiram1026_misaligned_RGB-IR_detection/test.py
import argparse import json import os from pathlib import Path from threading import Thread import numpy as np import torch import yaml from tqdm import tqdm from models.experimental import attempt_load from utils.datasets import create_dataloader, create_dataloader_rgb_ir from utils.general import coco8...
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global_var.py
Hiram1026_misaligned_RGB-IR_detection/global_var.py
# @Time : 2021/6/22 下午4:46 # @Author : Richard FANG # @File : global_var.py.py # @Software: PyCharm def _init(): # 初始化 global _global_dict _global_dict = {} def set_value(key, value): # 定义一个全局变量 _global_dict[key] = value def get_value(key): # 获得一个全局变量,不存在则提示读取对应变量失败 try: return ...
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train.py
Hiram1026_misaligned_RGB-IR_detection/train.py
import argparse import logging import math import os import random import time import torch from copy import deepcopy from pathlib import Path from threading import Thread import numpy as np import torch.distributed as dist import torch.nn as nn import torch.nn.functional as F import torch.optim as opti...
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hubconf.py
Hiram1026_misaligned_RGB-IR_detection/hubconf.py
"""YOLOv5 PyTorch Hub models https://pytorch.org/hub/ultralytics_yolov5/ Usage: import torch model = torch.hub.load('ultralytics/yolov5', 'yolov5s') """ from pathlib import Path import torch from models.yolo import Model from utils.general import check_requirements, set_logging from utils.google_utils impor...
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detect_twostream.py
Hiram1026_misaligned_RGB-IR_detection/detect_twostream.py
import argparse import time from pathlib import Path import cv2 import torch import torch.backends.cudnn as cudnn import numpy as np from numpy import random from models.experimental import attempt_load from utils.datasets import LoadStreams, LoadImages from utils.general import check_img_size, check_requ...
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export.py
Hiram1026_misaligned_RGB-IR_detection/models/export.py
"""Exports a YOLOv5 *.pt model to ONNX and TorchScript formats Usage: $ export PYTHONPATH="$PWD" && python models/export.py --weights yolov5s.pt --img 640 --batch 1 """ import argparse import sys import time from pathlib import Path sys.path.append(Path(__file__).parent.parent.absolute().__str__()) # to run '$ ...
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yolo.py
Hiram1026_misaligned_RGB-IR_detection/models/yolo.py
# YOLOv5 YOLO-specific modules import argparse import logging import sys from copy import deepcopy from pathlib import Path sys.path.append(Path(__file__).parent.parent.absolute().__str__()) # to run '$ python *.py' files in subdirectories logger = logging.getLogger(__name__) from models.common import * from models...
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experimental.py
Hiram1026_misaligned_RGB-IR_detection/models/experimental.py
# YOLOv5 experimental modules import numpy as np import torch import torch.nn as nn from models.common import Conv, DWConv from utils.google_utils import attempt_download class CrossConv(nn.Module): # Cross Convolution Downsample def __init__(self, c1, c2, k=3, s=1, g=1, e=1.0, shortcut=False): # ch...
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yolo_test.py
Hiram1026_misaligned_RGB-IR_detection/models/yolo_test.py
# YOLOv5 YOLO-specific modules import argparse import logging import sys from copy import deepcopy from pathlib import Path sys.path.append(Path(__file__).parent.parent.absolute().__str__()) # to run '$ python *.py' files in subdirectories logger = logging.getLogger(__name__) from models.common import * from models...
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common.py
Hiram1026_misaligned_RGB-IR_detection/models/common.py
# YOLOv5 common modules import math from copy import copy from pathlib import Path from matplotlib import style import numpy as np import pandas as pd import requests import torch import torch.nn as nn from PIL import Image from torch.cuda import amp import torch.nn.functional as F from utils.dataset...
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Hiram1026_misaligned_RGB-IR_detection/utils/general.py
# YOLOv5 general utils import glob import logging import math import os import platform import random import re import subprocess import time from itertools import repeat from multiprocessing.pool import ThreadPool from pathlib import Path import cv2 import numpy as np import pandas as pd import torch import torchvis...
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datasets.py
Hiram1026_misaligned_RGB-IR_detection/utils/datasets.py
# Dataset utils and dataloaders import glob import logging import math import os import random import shutil import time from itertools import repeat from multiprocessing.pool import ThreadPool from pathlib import Path from threading import Thread import cv2 import numpy as np import torch import torch.nn.functional ...
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ds_fusion.py
Hiram1026_misaligned_RGB-IR_detection/utils/ds_fusion.py
import numpy as np import pandas as pd import os import full_arrange def IIM_of_Li(data): [evidence_number, data_frame_number] = data.shape for i in range(evidence_number): print(str(i) + 'th evidence is ' + str(data[i, :])) # 对于识别框架内每一个命题 new_data = np.zeros((evidence_number, data_frame_num...
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torch_utils.py
Hiram1026_misaligned_RGB-IR_detection/utils/torch_utils.py
# YOLOv5 PyTorch utils import datetime import logging import math import os import platform import subprocess import time from contextlib import contextmanager from copy import deepcopy from pathlib import Path from typing import OrderedDict from matplotlib.pyplot import step import torch import torch.backends.cudnn ...
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autoanchor.py
Hiram1026_misaligned_RGB-IR_detection/utils/autoanchor.py
# Auto-anchor utils import numpy as np import torch import yaml from scipy.cluster.vq import kmeans from tqdm import tqdm from utils.general import colorstr def check_anchor_order(m): # Check anchor order against stride order for YOLOv5 Detect() module m, and correct if necessary a = m.anchor_grid.prod(-1)....
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gradcam.py
Hiram1026_misaligned_RGB-IR_detection/utils/gradcam.py
#!/usr/bin/env python # -*- coding:utf-8 -*- # Author: Richard Fang import torch from torch.autograd import Variable from torch.autograd import Function from torchvision import models from torchvision import utils import cv2 import sys import numpy as np import argparse import warnings warnings.filterwarnings("ignore"...
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plots.py
Hiram1026_misaligned_RGB-IR_detection/utils/plots.py
# Plotting utils import glob import math import os import random from copy import copy from pathlib import Path import cv2 import matplotlib import matplotlib.pyplot as plt import numpy as np import pandas as pd import seaborn as sns import torch import yaml from PIL import Image, ImageDraw, ImageFont from scipy.sign...
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google_utils.py
Hiram1026_misaligned_RGB-IR_detection/utils/google_utils.py
# Google utils: https://cloud.google.com/storage/docs/reference/libraries import os import platform import subprocess import time from pathlib import Path import requests import torch def gsutil_getsize(url=''): # gs://bucket/file size https://cloud.google.com/storage/docs/gsutil/commands/du s = subprocess....
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metrics.py
Hiram1026_misaligned_RGB-IR_detection/utils/metrics.py
# Model validation metrics from pathlib import Path import matplotlib.pyplot as plt import numpy as np import torch from . import general def fitness(x): # Model fitness as a weighted combination of metrics w = [0.0, 0.0, 0.6, 0.0, 0.4] # weights for [P, R, mAP@0.5, mAP@0.5:0.95] return (x[:, :5] * w)...
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loss.py
Hiram1026_misaligned_RGB-IR_detection/utils/loss.py
# Loss functions import torch import torch.nn as nn from utils.general import bbox_iou from utils.torch_utils import is_parallel def smooth_BCE(eps=0.1): # https://github.com/ultralytics/yolov3/issues/238#issuecomment-598028441 # return positive, negative label smoothing BCE targets return 1.0 - 0.5 * eps,...
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activations.py
Hiram1026_misaligned_RGB-IR_detection/utils/activations.py
# Activation functions import torch import torch.nn as nn import torch.nn.functional as F # SiLU https://arxiv.org/pdf/1606.08415.pdf ---------------------------------------------------------------------------- class SiLU(nn.Module): # export-friendly version of nn.SiLU() @staticmethod def forward(x): ...
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example_request.py
Hiram1026_misaligned_RGB-IR_detection/utils/flask_rest_api/example_request.py
"""Perform test request""" import pprint import requests DETECTION_URL = "http://localhost:5000/v1/object-detection/yolov5s" TEST_IMAGE = "zidane.jpg" image_data = open(TEST_IMAGE, "rb").read() response = requests.post(DETECTION_URL, files={"image": image_data}).json() pprint.pprint(response)
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Hiram1026_misaligned_RGB-IR_detection/utils/flask_rest_api/restapi.py
""" Run a rest API exposing the yolov5s object detection model """ import argparse import io import torch from PIL import Image from flask import Flask, request app = Flask(__name__) DETECTION_URL = "/v1/object-detection/yolov5s" @app.route(DETECTION_URL, methods=["POST"]) def predict(): if not request.method ...
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log_dataset.py
Hiram1026_misaligned_RGB-IR_detection/utils/wandb_logging/log_dataset.py
import argparse import yaml from wandb_utils import WandbLogger WANDB_ARTIFACT_PREFIX = 'wandb-artifact://' def create_dataset_artifact(opt): with open(opt.data) as f: data = yaml.safe_load(f) # data dict logger = WandbLogger(opt, '', None, data, job_type='Dataset Creation') if __name__ == '__ma...
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Hiram1026_misaligned_RGB-IR_detection/utils/wandb_logging/wandb_utils.py
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Hiram1026_misaligned_RGB-IR_detection/utils/aws/resume.py
# Resume all interrupted trainings in yolov5/ dir including DDP trainings # Usage: $ python utils/aws/resume.py import os import sys from pathlib import Path import torch import yaml sys.path.append('./') # to run '$ python *.py' files in subdirectories port = 0 # --master_port path = Path('').resolve() for last ...
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general.cpython-38.pyc
Hiram1026_misaligned_RGB-IR_detection/utils/__pycache__/general.cpython-38.pyc
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loss.cpython-37.pyc
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general.cpython-37.pyc
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datasets.cpython-37.pyc
Hiram1026_misaligned_RGB-IR_detection/utils/__pycache__/datasets.cpython-37.pyc
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google_utils.cpython-37.pyc
Hiram1026_misaligned_RGB-IR_detection/utils/__pycache__/google_utils.cpython-37.pyc
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torch_utils.cpython-38.pyc
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autoanchor.cpython-38.pyc
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datasets.cpython-38.pyc
Hiram1026_misaligned_RGB-IR_detection/utils/__pycache__/datasets.cpython-38.pyc
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loss.cpython-38.pyc
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ds_fusion.cpython-37.pyc
Hiram1026_misaligned_RGB-IR_detection/utils/__pycache__/ds_fusion.cpython-37.pyc
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plots.cpython-37.pyc
Hiram1026_misaligned_RGB-IR_detection/utils/__pycache__/plots.cpython-37.pyc
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metrics.cpython-38.pyc
Hiram1026_misaligned_RGB-IR_detection/utils/__pycache__/metrics.cpython-38.pyc
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wandb_utils.cpython-38.pyc
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wandb_utils.cpython-37.pyc
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dm_build.py
jgashler_rjg/build_scripts/dm_build.py
import maya.cmds as mc import platform from importlib import reload groups = 'G:' if platform.system() == 'Windows' else '/groups' mc.scriptEditorInfo(suppressWarnings=True,suppressInfo=True) import rjg.build.buildPart as rBuild import rjg.post.finalize as rFinal import rjg.libs.file as rFile reload(rBuild) reload(rF...
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jgashler/rjg
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corrective_info.py
jgashler_rjg/build_scripts/corrective_info.py
''' Format for corrective blendshape lists index 0: path to file containing blendshape targets. targets should be individual meshes with names unique from anything in the main file indices 1+: tuple or list objects that contain the following 0: (str) name of main mesh that has the blendshape applied to it 1: (...
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monster_build.py
jgashler_rjg/build_scripts/monster_build.py
import maya.cmds as mc from importlib import reload import rjg.build.buildPart as rBuild import rjg.post.finalize as rFinal import rjg.build.prop as rProp reload(rProp) reload(rBuild) reload(rFinal) mp = 'C:/Users/jgash/Documents/maya/projects/W24/monster_geo.mb' gp = 'C:/Users/jgash/Documents/maya/projects/W24/monst...
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jgashler/rjg
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2,283,989
build_ui.py
jgashler_rjg/build_scripts/build_ui.py
from PySide2 import QtWidgets, QtCore, QtGui import maya.cmds as mc import platform from typing import Optional from importlib import reload from pipe.m.local import get_main_qt_window import rjg reload(rjg) import rjg.build_scripts.build as build reload(build) class RigBuildUI(QtWidgets.QDialog): def __init__...
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jgashler/rjg
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dm_bone_dict.py
jgashler_rjg/build_scripts/dm_bone_dict.py
# Class containing a dictionary to define relationship between bone and rig # # Key: bone name as str (no suffix; 'boneName01_LOC' will be found by using key 'boneName01') # Value: list containing [parentInSkeleton, parentInRig, optional: commandFlag followed by extra arguments] # bone_dict = { # 'polySurface1' :...
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jgashler/rjg
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2,283,991
rayden_build.py
jgashler_rjg/build_scripts/rayden_build.py
import maya.cmds as mc import platform from importlib import reload groups = 'G:' if platform.system() == 'Windows' else '/groups' mc.scriptEditorInfo(suppressWarnings=True,suppressInfo=True) import rjg.build.buildPart as rBuild import rjg.post.finalize as rFinal import rjg.build.prop as rProp import rjg.libs.file as...
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jgashler/rjg
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9/5/2024, 10:47:35 PM (Europe/Amsterdam)
2,283,992
robin_clothes.py
jgashler_rjg/build_scripts/robin_clothes.py
import maya.cmds as mc import rjg.post.dataIO.ng_weights as rWeightNgIO import rjg.libs.util as rUtil def robin_clothes(skin_src, skin_trg_grp): bind_joints = [jnt.split('.')[0] for jnt in mc.ls('*.bindJoint')] geo = mc.ls(mc.select(skin_trg_grp, hierarchy=True), selection=True) mc.select(skin_trg_grp, hi...
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jgashler/rjg
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2,283,993
build.py
jgashler_rjg/build_scripts/build.py
import maya.cmds as mc import maya.mel as mel import sys, platform from importlib import reload groups = 'G:' if platform.system() == 'Windows' else '/groups' mc.scriptEditorInfo(suppressWarnings=True,suppressInfo=True) import rjg.build.buildPart as rBuild import rjg.post.finalize as rFinal import rjg.build.prop as r...
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Python
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jgashler/rjg
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2,283,994
sk_bone_dict.py
jgashler_rjg/build_scripts/sk_bone_dict.py
# Class containing a dictionary to define relationship between bone and rig # # Key: bone name as str (no suffix; 'boneName01_LOC' will be found by using key 'boneName01') # Value: list containing [parentInSkeleton, parentInRig, optional: commandFlag followed by extra arguments] # bone_dict = { # 'polySurface1' :...
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jgashler/rjg
8
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GPL-3.0
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2,283,995
robin_build.py
jgashler_rjg/build_scripts/robin_build.py
import maya.cmds as mc import platform from importlib import reload groups = 'G:' if platform.system() == 'Windows' else '/groups' mc.scriptEditorInfo(suppressWarnings=True,suppressInfo=True) import rjg.build.buildPart as rBuild import rjg.post.finalize as rFinal import rjg.build.prop as rProp import rjg.libs.file as...
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jgashler/rjg
8
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9/5/2024, 10:47:35 PM (Europe/Amsterdam)
2,283,996
rayden_clothes.py
jgashler_rjg/build_scripts/rayden_clothes.py
import maya.cmds as mc import rjg.post.dataIO.ng_weights as rWeightNgIO import rjg.libs.util as rUtil from importlib import reload import platform, time groups = 'G:' if platform.system() == 'Windows' else '/groups' reload(rUtil) manual_skins = [ 'Pants', 'Underbelt', 'Boots', #'Houlster', 'Seco...
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jgashler/rjg
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2,283,997
fk.py
jgashler_rjg/build/fk.py
import maya.cmds as mc from importlib import reload import rjg.build.chain as rChain import rjg.libs.control.ctrl as rCtrl reload(rChain) reload(rCtrl) class Fk: def __init__(self, side=None, part=None, guide_list=None, gimbal=None, offset=None, pad='auto', ctrl_scale=1, remove_last=True, add_jo...
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Python
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jgashler/rjg
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2,283,998
spline.py
jgashler_rjg/build/spline.py
import maya.cmds as mc from importlib import reload import rjg.libs.attribute as rAttr import rjg.build.chain as rChain import rjg.libs.control.ctrl as rCtrl import rjg.build.guide as rGuide import rjg.libs.transform as rXform reload(rAttr) reload(rChain) reload(rCtrl) reload (rGuide) reload(rXform) class Spline: ...
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Python
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jgashler/rjg
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9/5/2024, 10:47:35 PM (Europe/Amsterdam)
2,283,999
rigBase.py
jgashler_rjg/build/rigBase.py
import maya.cmds as mc from importlib import reload import rjg.libs.file as rFile reload(rFile) ''' Base class for rigModule. Creates base hierarchy for rig and loads in the model and guides. ''' class RigBase(): def __init__(self, model_path=None, guide_path=None): self.model_path = model_path se...
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Python
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jgashler/rjg
8
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0
GPL-3.0
9/5/2024, 10:47:35 PM (Europe/Amsterdam)