Cleanup install and dependencies (#5)
* Remove set_grad_enable * Remove unused resources * Install sub-packages * Import config files * Add missing LightGlue dependencymain
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5d9d89c0b9
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1709021473
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@ -1,8 +1,6 @@
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import torch
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from pathlib import Path
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from pathlib import Path
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from omegaconf import OmegaConf
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from omegaconf import OmegaConf
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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import resource
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from collections import defaultdict
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from collections import defaultdict
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from tqdm import tqdm
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from tqdm import tqdm
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import numpy as np
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import numpy as np
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@ -22,12 +20,6 @@ from ..models.cache_loader import CacheLoader
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from ..datasets import get_dataset
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from ..datasets import get_dataset
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rlimit = resource.getrlimit(resource.RLIMIT_NOFILE)
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resource.setrlimit(resource.RLIMIT_NOFILE, (4096, rlimit[1]))
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torch.set_grad_enabled(False)
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def eval_dataset(loader, pred_file, suffix=""):
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def eval_dataset(loader, pred_file, suffix=""):
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results = defaultdict(list)
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results = defaultdict(list)
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results["num_pos" + suffix] = 0
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results["num_pos" + suffix] = 0
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@ -1,9 +1,7 @@
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import torch
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from pathlib import Path
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from pathlib import Path
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from omegaconf import OmegaConf
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from omegaconf import OmegaConf
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from pprint import pprint
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from pprint import pprint
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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import resource
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from collections import defaultdict
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from collections import defaultdict
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from collections.abc import Iterable
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from collections.abc import Iterable
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from tqdm import tqdm
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from tqdm import tqdm
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@ -30,12 +28,6 @@ from ..utils.tools import AUCMetric
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from .eval_pipeline import EvalPipeline
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from .eval_pipeline import EvalPipeline
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rlimit = resource.getrlimit(resource.RLIMIT_NOFILE)
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resource.setrlimit(resource.RLIMIT_NOFILE, (4096, rlimit[1]))
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torch.set_grad_enabled(False)
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class HPatchesPipeline(EvalPipeline):
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class HPatchesPipeline(EvalPipeline):
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default_conf = {
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default_conf = {
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"data": {
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"data": {
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@ -3,7 +3,6 @@ from pathlib import Path
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from omegaconf import OmegaConf
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from omegaconf import OmegaConf
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from pprint import pprint
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from pprint import pprint
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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import resource
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from collections import defaultdict
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from collections import defaultdict
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from collections.abc import Iterable
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from collections.abc import Iterable
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from tqdm import tqdm
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from tqdm import tqdm
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@ -23,11 +22,6 @@ from .eval_pipeline import EvalPipeline
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from .utils import eval_relative_pose_robust, eval_poses, eval_matches_epipolar
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from .utils import eval_relative_pose_robust, eval_poses, eval_matches_epipolar
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rlimit = resource.getrlimit(resource.RLIMIT_NOFILE)
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resource.setrlimit(resource.RLIMIT_NOFILE, (4096, rlimit[1]))
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torch.set_grad_enabled(False)
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class MegaDepth1500Pipeline(EvalPipeline):
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class MegaDepth1500Pipeline(EvalPipeline):
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default_conf = {
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default_conf = {
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@ -31,6 +31,7 @@ dependencies = [
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"kornia",
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"kornia",
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"seaborn",
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"seaborn",
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"joblib",
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"joblib",
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"lightglue @ git+https://github.com/cvg/LightGlue.git",
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]
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]
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urls = {Repository = "https://github.com/cvg/glue-factory"}
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urls = {Repository = "https://github.com/cvg/glue-factory"}
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@ -44,8 +45,8 @@ extra = [
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]
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]
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dev = ["black", "flake8", "jupyter"]
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dev = ["black", "flake8", "jupyter"]
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[tool.setuptools]
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[tool.setuptools.packages.find]
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packages = ["gluefactory", "gluefactory_nonfree"]
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include = ["gluefactory*"]
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[tool.setuptools.package-data]
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[tool.setuptools.package-data]
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gluefactory = ["datasets/megadepth_scene_lists/*.txt"]
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gluefactory = ["datasets/megadepth_scene_lists/*.txt", "configs/*.yaml"]
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