From f192cf806e4a878c67265d1234e6fd054af1f255 Mon Sep 17 00:00:00 2001 From: gdamms Date: Sat, 17 Dec 2022 15:05:14 +0100 Subject: [PATCH] get proj mat and nasty read --- get_proj.py | 114 +++++++++++++++++++++++++++++++++++++++++++++ main.py | 30 ++++++++++++ matrices_reader.py | 36 ++++++++++++++ torus.blend | Bin 0 -> 2141928 bytes 4 files changed, 180 insertions(+) create mode 100644 get_proj.py create mode 100644 main.py create mode 100644 matrices_reader.py create mode 100644 torus.blend diff --git a/get_proj.py b/get_proj.py new file mode 100644 index 0000000..be6a2d1 --- /dev/null +++ b/get_proj.py @@ -0,0 +1,114 @@ +# https://blender.stackexchange.com/questions/38009/3x4-camera-matrix-from-blender-camera + +import bpy +from mathutils import Matrix +from mathutils import Vector + +#--------------------------------------------------------------- +# 3x4 P matrix from Blender camera +#--------------------------------------------------------------- + +# Build intrinsic camera parameters from Blender camera data +# +# See notes on this in +# blender.stackexchange.com/questions/15102/what-is-blenders-camera-projection-matrix-model +def get_calibration_matrix_K_from_blender(camd): + f_in_mm = camd.lens + scene = bpy.context.scene + resolution_x_in_px = scene.render.resolution_x + resolution_y_in_px = scene.render.resolution_y + scale = scene.render.resolution_percentage / 100 + sensor_width_in_mm = camd.sensor_width + sensor_height_in_mm = camd.sensor_height + pixel_aspect_ratio = scene.render.pixel_aspect_x / scene.render.pixel_aspect_y + if (camd.sensor_fit == 'VERTICAL'): + # the sensor height is fixed (sensor fit is horizontal), + # the sensor width is effectively changed with the pixel aspect ratio + s_u = resolution_x_in_px * scale / sensor_width_in_mm / pixel_aspect_ratio + s_v = resolution_y_in_px * scale / sensor_height_in_mm + else: # 'HORIZONTAL' and 'AUTO' + # the sensor width is fixed (sensor fit is horizontal), + # the sensor height is effectively changed with the pixel aspect ratio + pixel_aspect_ratio = scene.render.pixel_aspect_x / scene.render.pixel_aspect_y + s_u = resolution_x_in_px * scale / sensor_width_in_mm + s_v = resolution_y_in_px * scale * pixel_aspect_ratio / sensor_height_in_mm + + + # Parameters of intrinsic calibration matrix K + alpha_u = f_in_mm * s_u + alpha_v = f_in_mm * s_v + u_0 = resolution_x_in_px * scale / 2 + v_0 = resolution_y_in_px * scale / 2 + skew = 0 # only use rectangular pixels + + K = Matrix( + ((alpha_u, skew, u_0), + ( 0 , alpha_v, v_0), + ( 0 , 0, 1 ))) + return K + +# Returns camera rotation and translation matrices from Blender. +# +# There are 3 coordinate systems involved: +# 1. The World coordinates: "world" +# - right-handed +# 2. The Blender camera coordinates: "bcam" +# - x is horizontal +# - y is up +# - right-handed: negative z look-at direction +# 3. The desired computer vision camera coordinates: "cv" +# - x is horizontal +# - y is down (to align to the actual pixel coordinates +# used in digital images) +# - right-handed: positive z look-at direction +def get_3x4_RT_matrix_from_blender(cam): + # bcam stands for blender camera + R_bcam2cv = Matrix( + ((1, 0, 0), + (0, -1, 0), + (0, 0, -1))) + + # Transpose since the rotation is object rotation, + # and we want coordinate rotation + # R_world2bcam = cam.rotation_euler.to_matrix().transposed() + # T_world2bcam = -1*R_world2bcam * location + # + # Use matrix_world instead to account for all constraints + location, rotation = cam.matrix_world.decompose()[0:2] + R_world2bcam = rotation.to_matrix().transposed() + + # Convert camera location to translation vector used in coordinate changes + # T_world2bcam = -1*R_world2bcam*cam.location + # Use location from matrix_world to account for constraints: + T_world2bcam = -1*R_world2bcam @ location + + # Build the coordinate transform matrix from world to computer vision camera + # NOTE: Use * instead of @ here for older versions of Blender + # TODO: detect Blender version + R_world2cv = R_bcam2cv@R_world2bcam + T_world2cv = R_bcam2cv@T_world2bcam + + # put into 3x4 matrix + RT = Matrix(( + R_world2cv[0][:] + (T_world2cv[0],), + R_world2cv[1][:] + (T_world2cv[1],), + R_world2cv[2][:] + (T_world2cv[2],) + )) + return RT + +def get_3x4_P_matrix_from_blender(cam): + K = get_calibration_matrix_K_from_blender(cam.data) + RT = get_3x4_RT_matrix_from_blender(cam) + return K@RT, K, RT + + + +def run_script(scene): + # projection_matrix = scene.camera.matrix_world + projection_matrix, _, _ = get_3x4_P_matrix_from_blender(scene.camera) + with open('/home/damien/Documents/3A/projet-be/imgs/torus/matrices.txt', 'a') as f: + f.write(projection_matrix.__repr__() + '\n\n') + +f = open('/home/damien/Documents/3A/projet-be/imgs/torus/matrices.txt', 'w') +f.close() +bpy.app.handlers.frame_change_post.append(run_script) diff --git a/main.py b/main.py new file mode 100644 index 0000000..d81b802 --- /dev/null +++ b/main.py @@ -0,0 +1,30 @@ +import cv2 +import numpy as np + +from matrices_reader import * + +VOXEL_SIZE = 1e-3 +X_MIN, X_MAX = -2.0, 2.0 +Y_MIN, Y_MAX = -2.0, 2.0 +Z_MIN, Z_MAX = -2.0, 2.0 + +# grid = [[[ +# 1 for z in np.arange(Z_MIN, Z_MAX, VOXEL_SIZE) +# ] for y in np.arange(Y_MIN, Y_MAX, VOXEL_SIZE) +# ] for x in np.arange(X_MIN, X_MAX, VOXEL_SIZE) +# ] + +projection_matrices = matrices_reader('data/torus/matrices.txt') +nb_frame = len(projection_matrices) +point = np.array([1.0, 0.0, 0.0, 1.0]) + +for k in range(nb_frame): + + proj_mat = projection_matrices[k] + cam_point = proj_mat @ point + cam_point /= cam_point[2] + + frame = cv2.imread(f'data/torus/torus{k+1:04}.png') + cv2.circle(frame, (int(cam_point[0]), int(cam_point[1])), 2, (0, 0, 255)) + cv2.imshow('Frame', frame) + cv2.waitKey(0) \ No newline at end of file diff --git a/matrices_reader.py b/matrices_reader.py new file mode 100644 index 0000000..527cc08 --- /dev/null +++ b/matrices_reader.py @@ -0,0 +1,36 @@ +import re +import numpy as np + + +def matrices_reader(path: str) -> list[np.ndarray]: + """Read projection matrices. + + Args: + path (str): path to matrices.txt + + Returns: + list[np.ndarray]: list of projection matrix + """ + + with open(path, 'r') as f: + lines = f.readlines() + + k = 0 + world_matrices = [] + while k+3 < len(lines): + # Match matrices one by one + mat_str = "" + for line in lines[k:k+4]: + mat_str += line + float_reg = r"(-|\d|\.|e)+" + res = re.search( + f"Matrix\(\(\(({float_reg}), ({float_reg}), ({float_reg}), ({float_reg})\),\n +\(({float_reg}), ({float_reg}), ({float_reg}), ({float_reg})\),\n\ +\(({float_reg}), ({float_reg}), ({float_reg}), ({float_reg})\)\)\)", mat_str) + + # Convert string to np.ndarray + values = [float(res.group(i)) for i in range(1,len(res.groups()) + 1, 2)] + world_mat = np.array([[values[4*i + j] for j in range(4)] for i in range(3)]) + world_matrices.append(world_mat) + + k += 4 + + return world_matrices[1:] diff --git a/torus.blend b/torus.blend new file mode 100644 index 0000000000000000000000000000000000000000..0d1bfdaf6fd27e5884264230f2acf446b446ea29 GIT binary patch literal 2141928 zcmeEv31Ah~)&FDxMivD(c8wbbRAf&ekUj7~mOvt)s39Z|5(!C6!s?Qss88H*LvR6# z8)~&uwM9ih!20^HR&8y?)>{1Pf>yhKpLCJ=pELLV-psq1c}o%s#JMoJb7#&u_uk(* zcfWUD?&N~0`2{mBSTcObkQsFA(==^J&yj`SHqs5b1bL;BUsUF=_VdFQy5fSOVx1%g zQilAf-X_0^4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW z4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW z4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW z4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4*?GW4}lgSkerm1czV~aT_*MHdFtXb z&phLfL4yXqaN&i6-yS^pg11x89q>X*%ISBUeA0u3Joh)lD}W*RNV-(kxrC!l=2b)+i%;x#*%v zht3}~@U7#!b)7?T9~VRX9?6kGAfbEr?$dH}bKjl6V1ZFrUvDfYoj0yrY3lptTUHyl z-hPL1$C|s0yY9KyxaYpL#(np%GuEzKZ`{9rz3Jb(_I`SIk8#@_cN#a}a*NS){q@F@ 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