repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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MaskedDenoising | MaskedDenoising-main/data/dataset_video_train.py | import numpy as np
import random
import torch
from pathlib import Path
import torch.utils.data as data
import utils.utils_video as utils_video
class VideoRecurrentTrainDataset(data.Dataset):
"""Video dataset for training recurrent networks.
The keys are generated from a meta info txt file.
basicsr/data/... | 15,730 | 39.648579 | 133 | py |
MeTS-10 | MeTS-10-master/analysis/val02_counters/counters03_explore_madrid_nb.py | # ---
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MeTS-10 | MeTS-10-master/analysis/val02_counters/counters03_explore_london_nb.py | # ---
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from IPython.display impo... | 7,783 | 34.543379 | 120 | py |
MeTS-10 | MeTS-10-master/analysis/val02_counters/exploration_utils.py | import pandas as pd
import numpy as np
import folium
import geojson
import geopandas
import osmnx as ox
import networkx as nx
import seaborn as sns
from pathlib import Path
from matplotlib import pyplot as plt
from datetime import datetime, timedelta
MOVIE_BBOXES = {
"antwerp": {"bounds": [5100100, 5143700, 41530... | 8,512 | 39.345972 | 124 | py |
MeTS-10 | MeTS-10-master/analysis/val02_counters/counters01_prepare_data_nb.py | # -*- coding: utf-8 -*-
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MeTS-10 | MeTS-10-master/analysis/val02_counters/counters03_explore_berlin_nb.py | # -*- coding: utf-8 -*-
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MeTS-10 | MeTS-10-master/analysis/val02_counters/__init__.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 658 | 58.909091 | 89 | py |
MeTS-10 | MeTS-10-master/analysis/val02_counters/exploration_plots_nb.py | # -*- coding: utf-8 -*-
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MeTS-10 | MeTS-10-master/analysis/val02_counters/counters02_match_counters_nb.py | # ---
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import pandas as pd
impor... | 11,289 | 33.845679 | 118 | py |
MeTS-10 | MeTS-10-master/analysis/val03_meta/meta01_confidence_based_filtering.py | import ast
from pathlib import Path
import pandas as pd
BASEDIR = Path("/iarai/public/t4c/data_pipeline/release20221026_residential_unclassified_no_trust_filtering")
def simplified_filter(hw):
return hw in [
"motorway",
"motorway_link",
"trunk",
"trunk_link",
"primary",
... | 3,754 | 41.191011 | 147 | py |
MeTS-10 | MeTS-10-master/analysis/val03_meta/meta00_diagonal_vs_horizontal_vertical.py | from pathlib import Path
import geopandas as gpd
import pandas as pd
from shapely import LineString
from data_pipeline.data_helpers import get_bearing
MARGIN = 10
def main(DATA_ROOT: Path, RELEASE: str, YEAR: str, CITY: str, NUM_SPEED_FILES: int = 10):
gdf_edges = gpd.read_parquet(DATA_ROOT / RELEASE / YEAR /... | 3,921 | 35.314815 | 185 | py |
MeTS-10 | MeTS-10-master/analysis/dataset_description/data_specification.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 2,485 | 33.054795 | 99 | py |
MeTS-10 | MeTS-10-master/analysis/dataset_description/city_inventory.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 11,353 | 45.154472 | 338 | py |
MeTS-10 | MeTS-10-master/analysis/dataset_description/__init__.py | 0 | 0 | 0 | py | |
MeTS-10 | MeTS-10-master/analysis/dataset_description/speed_stats.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 30,171 | 42.601156 | 165 | py |
MeTS-10 | MeTS-10-master/analysis/dataset_description/pyqgis/speed_stats_pyqgis_density_8_18.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 3,570 | 32.373832 | 110 | py |
MeTS-10 | MeTS-10-master/analysis/dataset_description/pyqgis/pyqgis_speed_stats_lib.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 3,754 | 45.358025 | 121 | py |
MeTS-10 | MeTS-10-master/analysis/dataset_description/pyqgis/speed_stats_pyqgis_road_graph.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 4,128 | 33.123967 | 134 | py |
MeTS-10 | MeTS-10-master/analysis/dataset_description/pyqgis/__init__.py | 0 | 0 | 0 | py | |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber03_barcelona_spatial_coverage_nb.py | # ---
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from pathlib import Path
import geopan... | 12,237 | 30.541237 | 149 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber07_temporal-validation-week-barcelona_nb.py | # ---
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from path... | 20,254 | 34.410839 | 156 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber05_speed_differences_summary_nb.py | # -*- coding: utf-8 -*-
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from pathlib im... | 11,433 | 29.654155 | 160 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber06_gen_latex.py | if __name__ == "__main__":
for city in ["barcelona", "berlin", "london"]:
print(
f"""
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{{{city.title()}}}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... | 4,203 | 65.730159 | 399 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber07_temporal-validation-week-london_nb.py | # ---
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from datetime import datetime
from path... | 20,289 | 34.472028 | 156 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber04_berlin_speed_differences_nb.py | # -*- coding: utf-8 -*-
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from... | 29,603 | 30.59445 | 160 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber04_london_speed_differences_nb.py | # -*- coding: utf-8 -*-
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from... | 28,539 | 30.675916 | 160 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber07_temporal-validation-single-day_nb.py | # ---
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import os
import matplotlib.pyplot as ... | 8,223 | 27.655052 | 213 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber07_temporal-validation-week-berlin_nb.py | # ---
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from datetime import datetime
from path... | 20,290 | 34.535902 | 156 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/__init__.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 658 | 58.909091 | 89 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber03_spatial_coverage_city_comparison_nb.py | # ---
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from pathlib import Path
import folium... | 10,313 | 29.335294 | 160 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber03_berlin_spatial_coverage_nb.py | # ---
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from pathlib import Path
import geopan... | 12,310 | 31.48285 | 149 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber03_london_spatial_coverage_nb.py | # ---
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import geopan... | 11,902 | 31.881215 | 149 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber04_barcelona_speed_differences_nb.py | # -*- coding: utf-8 -*-
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import ast
from... | 26,805 | 31.374396 | 160 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/osm/uber02_berlin_match_uber_with_osm_nb.py | # ---
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import ast
from collections import defa... | 14,688 | 35.269136 | 153 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/osm/osm_inventory.py | import warnings
from pathlib import Path
import osmnx as ox
import pandas as pd
if __name__ == "__main__":
ox.config(use_cache=True, log_console=True)
OBASEPATH = Path("/iarai/public/t4c/osm")
for f in OBASEPATH.rglob("**/*.graphml"):
print(f"loading {f}")
# ox.load_graphml(f)
for f i... | 823 | 30.692308 | 95 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/osm/uber02_london_match_uber_with_osm_nb.py | # ---
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import ast
from collections import defa... | 16,219 | 36.116705 | 153 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/osm/uber02_barcelona_match_uber_with_osm_nb.py | # ---
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import ast
from collections import defa... | 14,692 | 35.279012 | 153 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/osm/__init__.py | 0 | 0 | 0 | py | |
MeTS-10 | MeTS-10-master/analysis/val01_uber/osm/uber01_osm_to_parquet_bypassing_osmnx.py | import argparse
import ast
import datetime
import logging
import os
import sys
import timeit
from pathlib import Path
import geopandas as gpd
import humanize
import xmltodict
from shapely.geometry import LineString
from shapely.geometry import Point
# TODO write to geopandas!
# https://stackoverflow.com/questions/1... | 6,058 | 35.721212 | 150 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/misc/__init__.py | 0 | 0 | 0 | py | |
MeTS-10 | MeTS-10-master/analysis/val01_uber/misc/csv_to_parquet.py | from pathlib import Path
import pandas as pd
import pyarrow as pa
import pyarrow.parquet as pq
if __name__ == "__main__":
csv_files = list(Path("/iarai/public/t4c/uber").rglob("*.csv"))
for i, csv_f in enumerate(csv_files):
parquet_f = csv_f.with_suffix(".parquet")
print(f"{i}/{len(csv_files)... | 641 | 29.571429 | 67 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber/uber_data_inventory_from_csvs.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 857 | 44.157895 | 89 | py |
MeTS-10 | MeTS-10-master/analysis/val01_uber/uber/__init__.py | 0 | 0 | 0 | py | |
MeTS-10 | MeTS-10-master/data_pipeline/test_dp02_speed_clusters.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 3,349 | 46.857143 | 137 | py |
MeTS-10 | MeTS-10-master/data_pipeline/data_helpers.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 8,034 | 43.392265 | 150 | py |
MeTS-10 | MeTS-10-master/data_pipeline/test_dp06_speed_classes.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 2,765 | 42.904762 | 127 | py |
MeTS-10 | MeTS-10-master/data_pipeline/road_graph_helpers.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 25,462 | 33.690736 | 139 | py |
MeTS-10 | MeTS-10-master/data_pipeline/dp03_road_graph.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 15,319 | 42.896848 | 166 | py |
MeTS-10 | MeTS-10-master/data_pipeline/ckmeans.py | # Copied from https://github.com/llimllib/ckmeans, WTFPL license
import numpy as np
def ssq(j, i, sum_x, sum_x_sq):
if j > 0:
muji = (sum_x[i] - sum_x[j - 1]) / (i - j + 1)
sji = sum_x_sq[i] - sum_x_sq[j - 1] - (i - j + 1) * muji**2
else:
sji = sum_x_sq[i] - sum_x[i] ** 2 / (i + 1)
... | 3,106 | 25.109244 | 83 | py |
MeTS-10 | MeTS-10-master/data_pipeline/dp06_speed_classes.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 13,168 | 44.254296 | 175 | py |
MeTS-10 | MeTS-10-master/data_pipeline/test_dp03_road_graph.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 6,212 | 46.068182 | 222 | py |
MeTS-10 | MeTS-10-master/data_pipeline/dummy_competition_setup_for_testing.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 22,042 | 33.988889 | 154 | py |
MeTS-10 | MeTS-10-master/data_pipeline/dp04_intersecting_cells.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 6,036 | 38.980132 | 150 | py |
MeTS-10 | MeTS-10-master/data_pipeline/test_dp04_intersecting_cells.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 2,623 | 43.474576 | 125 | py |
MeTS-10 | MeTS-10-master/data_pipeline/dp01_movie_aggregation.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 6,707 | 41.188679 | 150 | py |
MeTS-10 | MeTS-10-master/data_pipeline/dp05_free_flow.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 8,843 | 41.114286 | 159 | py |
MeTS-10 | MeTS-10-master/data_pipeline/__init__.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 786 | 48.1875 | 89 | py |
MeTS-10 | MeTS-10-master/data_pipeline/h5_helpers.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 1,796 | 40.790698 | 138 | py |
MeTS-10 | MeTS-10-master/data_pipeline/test_dp05_free_flow.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 3,126 | 45.671642 | 140 | py |
MeTS-10 | MeTS-10-master/data_pipeline/test_data_helpers.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 6,712 | 44.666667 | 148 | py |
MeTS-10 | MeTS-10-master/data_pipeline/dp02_speed_clusters.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 6,656 | 37.703488 | 150 | py |
MeTS-10 | MeTS-10-master/data_pipeline/test_dp01_movie_aggregation.py | # Copyright 2022 Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH.
# IARAI licenses this file to You 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 at
# http://www.apache.org/lice... | 2,798 | 48.105263 | 159 | py |
LISTA-CPSS | LISTA-CPSS-master/main.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
file : main.py
author: Xiaohan Chen
email : chernxh@tamu.edu
last_modified: 2018-10-13
Main script. Start running model from main.py.
"""
import os , sys
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # BE QUIET!!!!
# timing
import time
from datetime import timedelta
fr... | 16,900 | 34.807203 | 84 | py |
LISTA-CPSS | LISTA-CPSS-master/config.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
config.py
author: xhchrn
chernxh@tamu.edu
Set up experiment configuration using argparse library.
"""
import os
import sys
import datetime
import argparse
def str2bool(v):
return v.lower() in ( 'true' , '1' )
parser = argparse.ArgumentParser()
# Networ... | 10,853 | 38.043165 | 87 | py |
LISTA-CPSS | LISTA-CPSS-master/models/LISTA_cp.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
file : LISTA_cp.py
author: Xiaohan Chen
email : chernxh@tamu.edu
last_modified : 2018-10-21
Implementation of Learned ISTA with weight coupling.
"""
import numpy as np
import tensorflow as tf
import utils.train
from utils.tf import shrink_free
from models.LISTA_bas... | 3,653 | 31.336283 | 80 | py |
LISTA-CPSS | LISTA-CPSS-master/models/LISTA.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
file : LISTA.py
author: Xiaohan Chen
email : chernxh@tamu.edu
last_modified : 2018-10-21
Implementation of Learned ISTA proposed by LeCun et al in 2010.
"""
import numpy as np
import tensorflow as tf
import utils.train
from utils.tf import shrink
from models.LISTA_... | 3,968 | 32.352941 | 80 | py |
LISTA-CPSS | LISTA-CPSS-master/models/LAMP.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
file : LAMP.py
author: Xiaohan Chen
email : chernxh@tamu.edu
last_modified: 2018-10-15
Implementation of Learned AMP model.
"""
import numpy as np
import tensorflow as tf
import utils.train
from utils.tf import shrink_lamp
from models.LISTA_base import LISTA_base
... | 5,565 | 32.733333 | 80 | py |
LISTA-CPSS | LISTA-CPSS-master/models/LISTA_cs.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
file : LISTA_cs.py
author: xhchrn
email : chernxh@tamu.edu
date : 2018-10-21
Implementation of the original Learned ISTA for real world image compressive
sensing experiments.
"""
import numpy as np
import tensorflow as tf
import utils.train
from utils.tf import sh... | 4,909 | 34.071429 | 83 | py |
LISTA-CPSS | LISTA-CPSS-master/models/LISTA_cpss.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
file : LISTA_cpss.py
author: xhchrn
email : chernxh@tamu.edu
date : 2018-10-21
Implementation of Learned ISTA with support selection and coupled weights.
"""
import numpy as np
import tensorflow as tf
import utils.train
from utils.tf import shrink_ss
from models.L... | 3,942 | 31.319672 | 80 | py |
LISTA-CPSS | LISTA-CPSS-master/models/LISTA_ss.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
file : LISTA_ss.py
author: Xiaohan Chen
email : chernxh@tamu.edu
last_modified : 2018-10-21
Implementation of Learned ISTA with support selection technique.
"""
import numpy as np
import tensorflow as tf
import utils.train
from utils.tf import shrink_ss
from models... | 4,187 | 31.976378 | 80 | py |
LISTA-CPSS | LISTA-CPSS-master/models/LIHT_cs.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
file : LIHT_cs.py
author: xhchrn
email : chernxh@tamu.edu
date : 2018-10-21
Implementation of the original Learned ISTA for real world image compressive
sensing experiments.
"""
import numpy as np
import tensorflow as tf
import utils.train
from utils.tf import har... | 4,832 | 33.769784 | 83 | py |
LISTA-CPSS | LISTA-CPSS-master/models/LIHT.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
LISTA_cpss_corrected.py
author: xhchrn
chernxh@tamu.edu
date : 2018-10-21
Implementation of Learned ISTA with support selection and coupled weights like
in LAMP, without setting thresholds to zeros if they are minor to zero.
"""
import numpy as np
import ten... | 3,898 | 31.764706 | 80 | py |
LISTA-CPSS | LISTA-CPSS-master/models/__init__.py | 0 | 0 | 0 | py | |
LISTA-CPSS | LISTA-CPSS-master/models/LISTA_base.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
LISTA_base.py
author: xhchrn
email : chernxh@tamu.edu
date : 2018-10-03
A base class for all LISTA networks.
"""
import numpy as np
import numpy.linalg as la
import tensorflow as tf
import utils.train
class LISTA_base (object):
"""
Implementation of deep ... | 3,389 | 30.682243 | 84 | py |
LISTA-CPSS | LISTA-CPSS-master/models/LISTA_ss_cs.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
file : LISTA_ss_cs.py
author: xhchrn
email : chernxh@tamu.edu
date : 2018-10-25
Implementation of Learned ISTA with only support selection real world image
compressive sensing experiments.
"""
import numpy as np
import tensorflow as tf
import utils.train
from util... | 5,199 | 34.37415 | 83 | py |
LISTA-CPSS | LISTA-CPSS-master/models/LISTA_cpss_cs.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
file : LISTA_cpss_cs.py
author: xhchrn
email : chernxh@tamu.edu
date : 2018-10-21
Implementation of Learned ISTA with support selection and coupled weights for
real world image compressive sensing experiments.
"""
import numpy as np
import tensorflow as tf
import u... | 4,933 | 33.992908 | 80 | py |
LISTA-CPSS | LISTA-CPSS-master/utils/prob.py | #!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
file : prob.py
author: Xiaohan Chen
email : chernxh@tamu.edu
last_modified: 2018-10-03
Define problem class that is used experiments.
"""
import os
import numpy as np
import numpy.linalg as la
# import tensorflow as tf
from scipy.io import savemat, loadmat
class Pro... | 6,413 | 31.558376 | 84 | py |
LISTA-CPSS | LISTA-CPSS-master/utils/tf.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
file : utils/tf.py
author: Xiaohan Chen
email : chernxh@tamu.edu
last_modified: 2018-10-04
Utility functions implemented in TensorFlow, including:
- shrinkage functions
- circular padding
- activations
- subgradient functions
- related functions
"... | 6,409 | 26.869565 | 78 | py |
LISTA-CPSS | LISTA-CPSS-master/utils/data.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
file : data.py
author: Xiaohan Chen
email : chernxh@tamu.edu
last_modified: 2018-10-16
Utility methods for the real world images compressive sensing experiments.
"""
import os
import glob
import numpy as np
import tensorflow as tf
from PIL import Image
from tqdm im... | 4,164 | 32.32 | 84 | py |
LISTA-CPSS | LISTA-CPSS-master/utils/__init__.py | 0 | 0 | 0 | py | |
LISTA-CPSS | LISTA-CPSS-master/utils/train.py | #!/usss;k/bin/env python
# -*- coding: utf-8 -*-
"""
train.py
author: xhchrn
chernxh@tamu.edu
This file includes codes that set up training, do the training actually.
"""
import sys, os
import tensorflow as tf
import numpy as np
from utils.data import bsd500_cs_inputs
def setup_input_sc (test, p, tbs, vbs... | 33,750 | 37.136723 | 100 | py |
pbrt-v4 | pbrt-v4-master/src/pbrt/pbrt_lldbdataformatters.py | """
LLDB Formatters
1. Load Manually (everytime)
use lldb command 'command script import [PATH]/pbrt_lldbdataformatters.py' (without the quotes)
2. Load Automatically (add to ~/.lldbinit)
1) create ~/.lldbinit file if there isn't
2) open ~/.lldbinit
3) add 'command script import [PATH]/pbrt_lldbdatafo... | 9,411 | 33.988848 | 160 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/networks/equilibrium_u_net.py | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import torch
from torch import nn
from torch.nn import functional as F
class ConvBlock(nn.Module):
"""
A Convolutional Block that co... | 6,704 | 34.664894 | 98 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/networks/normalized_equilibrium_u_net.py | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import torch
from torch import nn
from torch.nn import functional as F
from utils.spectral_norm import conv_spectral_norm
import utils.spectra... | 7,553 | 38.34375 | 155 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/networks/twolayer_linear_net.py | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import torch
from torch import nn
from torch.nn import functional as F
class LinearNet(nn.Module):
def __init__(self, input_size, bottl... | 1,205 | 29.923077 | 66 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/networks/resnet.py | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import torch
from torch import nn
from torch.nn import functional as F
import torch
import torch.nn as nn
class nblock_resnet(nn.Module):
... | 1,833 | 30.62069 | 81 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/networks/u_net.py | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import torch
from torch import nn
from torch.nn import functional as F
class ConvBlock(nn.Module):
"""
A Convolutional Block that co... | 7,115 | 36.0625 | 135 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/networks/__init__.py | 0 | 0 | 0 | py | |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/training/denoiser_training.py | import torch
import numpy as np
from solvers import new_equilibrium_utils as eq_utils
from torch import autograd
from utils import cg_utils
import gc
def train_denoiser(denoising_net, train_dataloader, test_dataloader,
measurement_process, optimizer,
save_location, loss_function, n_ep... | 10,567 | 44.551724 | 130 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/training/standard_training.py | import torch
import numpy as np
def train_solver(solver, train_dataloader, test_dataloader,
measurement_process, optimizer,
save_location, loss_function, n_epochs, forward_model=None,
use_dataparallel=False, device='cpu', scheduler=None, n_blocks=10,
... | 6,265 | 40.496689 | 89 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/training/new_equilibrium_training.py | import torch
import numpy as np
from solvers import new_equilibrium_utils as eq_utils
from torch import autograd
def train_solver(single_iterate_solver, train_dataloader, test_dataloader,
measurement_process, optimizer,
save_location, loss_function, n_epochs, forward_iterator, iterato... | 10,141 | 45.1 | 113 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/training/refactor_equilibrium_training.py | import torch
import numpy as np
from solvers import new_equilibrium_utils as eq_utils
from torch import autograd
from utils import cg_utils
def train_solver(single_iterate_solver, train_dataloader, test_dataloader,
measurement_process, optimizer,
save_location, loss_function, n_epochs... | 16,122 | 47.272455 | 130 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/training/equilibrium_training.py | import torch
import numpy as np
from solvers import equilibrium_utils as eq_utils
from torch import autograd
def train_solver(single_iterate_solver, train_dataloader, test_dataloader,
measurement_process, optimizer,
save_location, loss_function, n_epochs,
use_datapara... | 14,024 | 44.684039 | 129 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/scripts/fixedpoint/deblur_proxgrad_fixedeta_pre.py | import torch
import os
import random
import sys
import argparse
sys.path.append('/home-nfs/gilton/learned_iterative_solvers')
# sys.path.append('/Users/dgilton/PycharmProjects/learned_iterative_solvers')
import torch.nn as nn
import torch.optim as optim
from torchvision import transforms
import operators.blurs as blu... | 6,779 | 38.418605 | 122 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/scripts/fixedpoint/mri_grad_fixedeta_pre_and4.py | import torch
import os
import random
import sys
import argparse
sys.path.append('/home-nfs/gilton/learned_iterative_solvers')
# sys.path.append('/Users/dgilton/PycharmProjects/learned_iterative_solvers')
import torch.nn as nn
import torch.optim as optim
import operators.singlecoil_mri as mrimodel
from operators.opera... | 6,531 | 39.320988 | 121 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/scripts/fixedpoint/mri_prox_fixedeta_pre_and.py | import torch
import os
import random
import sys
import argparse
sys.path.append('/home-nfs/gilton/learned_iterative_solvers')
# sys.path.append('/Users/dgilton/PycharmProjects/learned_iterative_solvers')
import torch.nn as nn
import torch.optim as optim
import operators.singlecoil_mri as mrimodel
from operators.opera... | 6,521 | 39.259259 | 121 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/scripts/denoising/gaussian_dncnn_norm_denoise.py | import torch
import os
import random
import sys
import argparse
sys.path.append('/home-nfs/gilton/learned_iterative_solvers')
# sys.path.append('/Users/dgilton/PycharmProjects/learned_iterative_solvers')
import torch.nn as nn
import torch.optim as optim
from torchvision import transforms
import operators.operator as ... | 5,275 | 35.638889 | 121 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/scripts/denoising/gaussian_unet_denoise.py | import torch
import os
import random
import sys
import argparse
sys.path.append('/home-nfs/gilton/learned_iterative_solvers')
# sys.path.append('/Users/dgilton/PycharmProjects/learned_iterative_solvers')
import torch.nn as nn
import torch.optim as optim
from torchvision import transforms
import operators.operator as ... | 4,901 | 35.044118 | 121 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/scripts/denoising/mri_unet_denoise.py | import torch
import os
import random
import sys
import argparse
sys.path.append('/home-nfs/gilton/learned_iterative_solvers')
# sys.path.append('/Users/dgilton/PycharmProjects/learned_iterative_solvers')
import torch.nn as nn
import torch.optim as optim
import operators.operator as lin_operator
from operators.operato... | 4,447 | 36.066667 | 121 | py |
deep_equilibrium_inverse | deep_equilibrium_inverse-main/scripts/denoising/mri_dncnn_denoise.py | import torch
import os
import random
import sys
import argparse
sys.path.append('/home-nfs/gilton/learned_iterative_solvers')
# sys.path.append('/Users/dgilton/PycharmProjects/learned_iterative_solvers')
import torch.nn as nn
import torch.optim as optim
import operators.operator as lin_operator
from operators.operato... | 5,199 | 36.681159 | 121 | py |
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