Upload 5 files
Browse files- Dataset_Scraper.7z +3 -0
- HeadsNet-2-6.7z +3 -0
- fix_ply.blend +0 -0
- fix_ply.py +33 -0
- nan_check.py +18 -0
Dataset_Scraper.7z
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version https://git-lfs.github.com/spec/v1
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oid sha256:4daaf5218628fd767985030c6e6cadac425ed5ace3fc6f9557fbe135eea8e4e7
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size 52184
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HeadsNet-2-6.7z
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version https://git-lfs.github.com/spec/v1
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oid sha256:9ab339e7b10dd320c0eb9f917654cf0a19bb453e5f34f02197981c2e989de067
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size 5074033744
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fix_ply.blend
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Binary file (903 kB). View file
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fix_ply.py
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# https://github.com/mrbid
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import bpy
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import glob
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import pathlib
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if not isdir(outputDir): mkdir(outputDir)
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importDir = "ply/"
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outputDir = "ply_norm/"
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if not isdir(outputDir): mkdir(outputDir)
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for file in glob.glob(importDir + "*.ply"):
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model_name = pathlib.Path(file).stem
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if pathlib.Path(outputDir+model_name+'.ply').is_file() == True: continue
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bpy.ops.wm.ply_import(filepath=file)
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bpy.ops.wm.ply_export(
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filepath=outputDir+model_name+'.ply',
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filter_glob='*.ply',
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check_existing=False,
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ascii_format=False,
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export_selected_objects=False,
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apply_modifiers=True,
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export_triangulated_mesh=True,
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export_normals=True,
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export_uv=False,
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export_colors='SRGB',
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global_scale=1.0,
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forward_axis='Y',
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up_axis='Z'
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)
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bpy.ops.object.select_all(action='SELECT')
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bpy.ops.object.delete(use_global=False)
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bpy.ops.outliner.orphans_purge()
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bpy.ops.outliner.orphans_purge()
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bpy.ops.outliner.orphans_purge()
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nan_check.py
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# https://github.com/mrbid
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import sys
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import numpy as np
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from time import time_ns
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# print everything / no truncations
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np.set_printoptions(threshold=sys.maxsize)
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# load training data
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st = time_ns()
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train_x = []
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train_y = []
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print("Loading...")
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with open("train_x.dat", 'rb') as f: data = np.fromfile(f, dtype=np.float32)
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with open("train_y.dat", 'rb') as f: data = np.fromfile(f, dtype=np.float32)
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print("NaN's detected:", np.count_nonzero(np.isnan(data)))
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timetaken = (time_ns()-st)/1e+9
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print("Time Taken:", "{:.2f}".format(timetaken), "seconds")
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