Outputs = self.call(cast_inputs, *args, **kwargs)įile "/home/bhb/Cloud/Code/Git/3D_Person_Pose_Estimation_from_2D_Singelview_Image_Data/src/ShAReD_Net/model/modules/base.py", line 126, in callįile "/home/bhb/Cloud/Code/Git/3D_Person_Pose_Estimation_from_2D_Singelview_Image_Data/src/ShAReD_Net/model/modules/base.py", line 62, in callīig_normal = self.big_normal(big_shared2_shc, scale_2)įile "/home/bhb/Cloud/Code/Git/3D_Person_Pose_Estimation_from_2D_Singelview_Image_Data/src/venv/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py", line 568, in _call_įile "/home/bhb/Cloud/Code/Git/3D_Person_Pose_Estimation_from_2D_Singelview_Image_Data/src/venv/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py", line 615, in _call Mod_name, mod_spec, pkg_name, script_name)įile "/usr/lib/python3.6/runpy.py", line 85, in _run_codeįile "/home/bhb/Cloud/Code/Git/3D_Person_Pose_Estimation_from_2D_Singelview_Image_Data/src/ShAReD_Net/model/modules/base.py", line 204, in įile "/home/bhb/Cloud/Code/Git/3D_Person_Pose_Estimation_from_2D_Singelview_Image_Data/src/ShAReD_Net/model/modules/base.py", line 191, in mainįile "/home/bhb/Cloud/Code/Git/3D_Person_Pose_Estimation_from_2D_Singelview_Image_Data/src/ShAReD_Net/model/modules/base.py", line 175, in runįile "/home/bhb/Cloud/Code/Git/3D_Person_Pose_Estimation_from_2D_Singelview_Image_Data/src/venv/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/base_layer.py", line 822, in _call_ n_path(target, run_name='_main_')įile "/usr/lib/python3.6/runpy.py", line 263, in run_pathįile "/usr/lib/python3.6/runpy.py", line 96, in _run_module_code With preserve_aspect_ratio=True, the aspect ratio is preserved, so size is the maximum for each dimension: max_10_20 = tf.image.File "/home/bhb/.vscode/extensions/ms-python.python-200/pythonFiles/ptvsd_launcher.py", line 48, in įile "/home/bhb/.vscode/extensions/ms-python.python-200/pythonFiles/lib/python/old_ptvsd/ptvsd/_main_.py", line 432, in mainįile "/home/bhb/.vscode/extensions/ms-python.python-200/pythonFiles/lib/python/old_ptvsd/ptvsd/_main_.py", line 316, in run_file The return value has type float32, unless the method is ResizeMethod.NEAREST_NEIGHBOR, then the return dtype is the dtype of images: nn = tf.image.resize(image,, method= 'nearest') For these pixels, only input pixels inside the image will be included in the filter sum, and the output value will be appropriately normalized. Note: Near image edges the filtering kernel may be partially outside the image boundaries. For synthetic images (especially those lacking proper prefiltering), less ringing than Keys cubic kernel but less sharp. mitchellcubic: Mitchell-Netravali Cubic non-interpolating filter. antialias has no effect when used with area interpolation it always anti-aliases.
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