145 lines
4.9 KiB
Python
145 lines
4.9 KiB
Python
# https://blender.stackexchange.com/questions/38009/3x4-camera-matrix-from-blender-camera
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import bpy
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from mathutils import Matrix
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import pickle
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import numpy as np
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#---------------------------------------------------------------
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# 3x4 P matrix from Blender camera
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#---------------------------------------------------------------
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# BKE_camera_sensor_size
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def get_sensor_size(sensor_fit, sensor_x, sensor_y):
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if sensor_fit == 'VERTICAL':
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return sensor_y
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return sensor_x
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# BKE_camera_sensor_fit
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def get_sensor_fit(sensor_fit, size_x, size_y):
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if sensor_fit == 'AUTO':
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if size_x >= size_y:
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return 'HORIZONTAL'
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else:
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return 'VERTICAL'
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return sensor_fit
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# Build intrinsic camera parameters from Blender camera data
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#
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# See notes on this in
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# blender.stackexchange.com/questions/15102/what-is-blenders-camera-projection-matrix-model
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# as well as
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# https://blender.stackexchange.com/a/120063/3581
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def get_calibration_matrix_K_from_blender(camd):
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if camd.type != 'PERSP':
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raise ValueError('Non-perspective cameras not supported')
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scene = bpy.context.scene
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f_in_mm = camd.lens
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scale = scene.render.resolution_percentage / 100
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resolution_x_in_px = scale * scene.render.resolution_x
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resolution_y_in_px = scale * scene.render.resolution_y
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sensor_size_in_mm = get_sensor_size(camd.sensor_fit, camd.sensor_width, camd.sensor_height)
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sensor_fit = get_sensor_fit(
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camd.sensor_fit,
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scene.render.pixel_aspect_x * resolution_x_in_px,
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scene.render.pixel_aspect_y * resolution_y_in_px
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)
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pixel_aspect_ratio = scene.render.pixel_aspect_y / scene.render.pixel_aspect_x
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if sensor_fit == 'HORIZONTAL':
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view_fac_in_px = resolution_x_in_px
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else:
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view_fac_in_px = pixel_aspect_ratio * resolution_y_in_px
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pixel_size_mm_per_px = sensor_size_in_mm / f_in_mm / view_fac_in_px
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s_u = 1 / pixel_size_mm_per_px
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s_v = 1 / pixel_size_mm_per_px / pixel_aspect_ratio
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# Parameters of intrinsic calibration matrix K
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u_0 = resolution_x_in_px / 2 - camd.shift_x * view_fac_in_px
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v_0 = resolution_y_in_px / 2 + camd.shift_y * view_fac_in_px / pixel_aspect_ratio
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skew = 0 # only use rectangular pixels
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K = Matrix(
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((s_u, skew, u_0),
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( 0, s_v, v_0),
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( 0, 0, 1)))
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return K
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# Returns camera rotation and translation matrices from Blender.
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#
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# There are 3 coordinate systems involved:
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# 1. The World coordinates: "world"
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# - right-handed
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# 2. The Blender camera coordinates: "bcam"
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# - x is horizontal
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# - y is up
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# - right-handed: negative z look-at direction
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# 3. The desired computer vision camera coordinates: "cv"
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# - x is horizontal
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# - y is down (to align to the actual pixel coordinates
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# used in digital images)
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# - right-handed: positive z look-at direction
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def get_3x4_RT_matrix_from_blender(cam):
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# bcam stands for blender camera
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R_bcam2cv = Matrix(
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((1, 0, 0),
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(0, -1, 0),
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(0, 0, -1)))
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# Transpose since the rotation is object rotation,
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# and we want coordinate rotation
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# R_world2bcam = cam.rotation_euler.to_matrix().transposed()
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# T_world2bcam = -1*R_world2bcam @ location
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#
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# Use matrix_world instead to account for all constraints
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location, rotation = cam.matrix_world.decompose()[0:2]
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R_world2bcam = rotation.to_matrix().transposed()
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# Convert camera location to translation vector used in coordinate changes
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# T_world2bcam = -1*R_world2bcam @ cam.location
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# Use location from matrix_world to account for constraints:
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T_world2bcam = -1*R_world2bcam @ location
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# Build the coordinate transform matrix from world to computer vision camera
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R_world2cv = R_bcam2cv@R_world2bcam
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T_world2cv = R_bcam2cv@T_world2bcam
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# put into 3x4 matrix
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RT = Matrix((
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R_world2cv[0][:] + (T_world2cv[0],),
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R_world2cv[1][:] + (T_world2cv[1],),
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R_world2cv[2][:] + (T_world2cv[2],)
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))
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return RT
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def get_3x4_P_matrix_from_blender(cam):
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K = get_calibration_matrix_K_from_blender(cam.data)
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RT = get_3x4_RT_matrix_from_blender(cam)
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return K@RT, K, RT
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def run_script(scene):
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with open(PICKLE_PATH, 'rb') as file:
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matrices = pickle.load(file)
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projection_matrix, _, _ = get_3x4_P_matrix_from_blender(scene.camera)
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matrices.append(np.array(projection_matrix))
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with open(PICKLE_PATH, 'wb') as file:
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pickle.dump(matrices, file)
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def setup_script(scene):
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matrices = []
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with open(PICKLE_PATH, 'wb') as file:
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pickle.dump(matrices, file)
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PICKLE_PATH = "/tmp/pickle.truc"
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# clear handlers
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bpy.app.handlers.render_init.clear()
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bpy.app.handlers.frame_change_pre.clear()
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bpy.app.handlers.frame_change_post.clear()
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# add handler
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bpy.app.handlers.render_init.append(setup_script)
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bpy.app.handlers.frame_change_post.append(run_script)
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