Load camera parameters from calibration xml
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@ -11,6 +11,8 @@ import os
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import collections
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import collections
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import sys
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import sys
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import xmltodict as xmltodict
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sys.path.append('../')
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sys.path.append('../')
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import renderer
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import renderer
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import co
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import co
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@ -201,6 +203,16 @@ def create_data(out_root, idx, n_samples, imsize, patterns, K, baseline, blend_i
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print(f'create sample {idx + 1}/{n_samples} took {time.time() - tic}[s]')
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print(f'create sample {idx + 1}/{n_samples} took {time.time() - tic}[s]')
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def load_camera_parameters():
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with open('calibration_result.xml') as f:
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cam_mat = xmltodict.parse(f.read())
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# weird casting cause the values are str(float) (eg. '123.'), but we want int
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imsize = [int(float(x)) for x in cam_mat['opencv_storage']['img_shape']['data'].split()]
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K_shape = int(cam_mat['opencv_storage']['cam_int']['rows']), int(cam_mat['opencv_storage']['cam_int']['cols'])
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K = np.array(cam_mat['opencv_storage']['cam_int']['data'].split(), dtype=float).reshape(K_shape).T
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return imsize, K
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if __name__ == '__main__':
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if __name__ == '__main__':
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np.random.seed(42)
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np.random.seed(42)
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@ -230,11 +242,9 @@ if __name__ == '__main__':
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objs = get_objs(shapenet_root, obj_classes)
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objs = get_objs(shapenet_root, obj_classes)
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# camera parameters
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# camera parameters
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imsize = (488, 648)
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imsize, K = load_camera_parameters()
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imsizes = [(imsize[0] // (2 ** s), imsize[1] // (2 ** s)) for s in range(4)]
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imsizes = [(imsize[0] // (2 ** s), imsize[1] // (2 ** s)) for s in range(4)]
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# K = np.array([[567.6, 0, 324.7], [0, 570.2, 250.1], [0 ,0, 1]], dtype=np.float32)
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K = np.array([[1929.5936336276382, 0, 113.66561071478046], [0, 1911.2517985448746, 473.70108079885887], [0, 0, 1]],
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dtype=np.float32)
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focal_lengths = [K[0, 0] / (2 ** s) for s in range(4)]
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focal_lengths = [K[0, 0] / (2 ** s) for s in range(4)]
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baseline = 0.075
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baseline = 0.075
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blend_im = 0.6
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blend_im = 0.6
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