45 lines
1.5 KiB
Python
45 lines
1.5 KiB
Python
import numpy as np
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def camNormal2worldNormal(rot_c2w, camNormal):
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H,W,_ = camNormal.shape
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normal_img = np.matmul(rot_c2w[None, :, :], camNormal.reshape(-1,3)[:, :, None]).reshape([H, W, 3])
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return normal_img
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def worldNormal2camNormal(rot_w2c, normal_map_world):
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H,W,_ = normal_map_world.shape
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# normal_img = np.matmul(rot_w2c[None, :, :], worldNormal.reshape(-1,3)[:, :, None]).reshape([H, W, 3])
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# faster version
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# Reshape the normal map into a 2D array where each row represents a normal vector
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normal_map_flat = normal_map_world.reshape(-1, 3)
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# Transform the normal vectors using the transformation matrix
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normal_map_camera_flat = np.dot(normal_map_flat, rot_w2c.T)
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# Reshape the transformed normal map back to its original shape
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normal_map_camera = normal_map_camera_flat.reshape(normal_map_world.shape)
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return normal_map_camera
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def trans_normal(normal, RT_w2c, RT_w2c_target):
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# normal_world = camNormal2worldNormal(np.linalg.inv(RT_w2c[:3,:3]), normal)
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# normal_target_cam = worldNormal2camNormal(RT_w2c_target[:3,:3], normal_world)
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relative_RT = np.matmul(RT_w2c_target[:3,:3], np.linalg.inv(RT_w2c[:3,:3]))
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normal_target_cam = worldNormal2camNormal(relative_RT[:3,:3], normal)
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return normal_target_cam
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def img2normal(img):
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return (img/255.)*2-1
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def normal2img(normal):
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return np.uint8((normal*0.5+0.5)*255)
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def norm_normalize(normal, dim=-1):
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normal = normal/(np.linalg.norm(normal, axis=dim, keepdims=True)+1e-6)
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return normal |