pickle

Co-authored-by: pejour <pejour@users.noreply.github.com>
Co-authored-by: Damien Guillotin <damguillotin@gmail.com>

get_proj.py

@@ -2,7 +2,9 @@
 
 import bpy
 from mathutils import Matrix
-from mathutils import Vector
+import pickle
+import numpy as np
+
 
 #---------------------------------------------------------------
 # 3x4 P matrix from Blender camera
@@ -41,10 +43,12 @@ def get_calibration_matrix_K_from_blender(camd):
     v_0 = resolution_y_in_px * scale / 2
     skew = 0 # only use rectangular pixels
 
-    K = Matrix(
+    K = Matrix((
-        ((alpha_u, skew,    u_0),
+        (alpha_u,    skew, u_0),
-        (    0  , alpha_v, v_0),
+        (      0, alpha_v, v_0),
-        (    0  , 0,        1 )))
+        (      0,       0,   1)
+    ))
+
     return K
 
 # Returns camera rotation and translation matrices from Blender.
@@ -62,7 +66,7 @@ def get_calibration_matrix_K_from_blender(camd):
 #         used in digital images)
 #       - right-handed: positive z look-at direction
 def get_3x4_RT_matrix_from_blender(cam):
-    # bcam stands for blender camera
+#    # bcam stands for blender camera
     R_bcam2cv = Matrix(
         ((1, 0,  0),
          (0, -1, 0),
@@ -101,14 +105,28 @@ def get_3x4_P_matrix_from_blender(cam):
     RT = get_3x4_RT_matrix_from_blender(cam)
     return K@RT, K, RT
 
-
-
 def run_script(scene):
-    # projection_matrix = scene.camera.matrix_world
+    with open(PICKLE_PATH, 'rb') as file:
-    projection_matrix, _, _ = get_3x4_P_matrix_from_blender(scene.camera)
+        matrices = pickle.load(file)
-    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')
+    projection_matrix, _, _ = get_3x4_P_matrix_from_blender(scene.camera)
-f.close()
+    matrices.append(np.array(projection_matrix))
-bpy.app.handlers.frame_change_post.append(run_script)
+    
+    with open(PICKLE_PATH, 'wb') as file:
+        pickle.dump(matrices, file)
+
+def setup_script(scene):
+    matrices = []
+    with open(PICKLE_PATH, 'wb') as file:
+        pickle.dump(matrices, file)
+
+PICKLE_PATH = "/tmp/pickle.truc"
+
+# clear handlers
+bpy.app.handlers.render_init.clear()
+bpy.app.handlers.frame_change_pre.clear()
+bpy.app.handlers.frame_change_post.clear()
+
+# add handler
+bpy.app.handlers.render_init.append(setup_script)
+bpy.app.handlers.frame_change_pre.append(run_script)

main.py

@@ -1,16 +1,19 @@
 import cv2
 import numpy as np
 from itertools import product
-from rich.progress import track
+import pickle
 
 from matrices_reader import *
 
-VOXEL_SIZE = 2e-2
+PICKLE_PATH = "/tmp/pickle.truc"
+
+VOXEL_SIZE = 8e-2
 X_MIN, X_MAX = -2.0, 2.0
 Y_MIN, Y_MAX = -2.0, 2.0
 Z_MIN, Z_MAX = -2.0, 2.0
 
-projection_matrices = matrices_reader('data/torus/matrices.txt')
+with open(PICKLE_PATH, 'rb') as file:
+    projection_matrices = pickle.load(file)
 nb_frame = len(projection_matrices)
 
 points = np.array([[x, y, z, 1.0] for x, y, z in product(
@@ -18,10 +21,10 @@ points = np.array([[x, y, z, 1.0] for x, y, z in product(
     np.arange(Y_MIN, Y_MAX, VOXEL_SIZE),
     np.arange(Z_MIN, Z_MAX, VOXEL_SIZE))])
 
-background = np.array([18, 18, 18])
+background = np.array([255, 255, 255])
-
+print('ok')
 for k in range(nb_frame):
-    frame = cv2.imread(f'data/torus/torus{k+1:04}.png')
+    frame = cv2.imread(f'/tmp/masks/Image{k+1:04}.png')
     proj_mat = projection_matrices[k]
     
     cam_points = proj_mat @ points.T
@@ -35,13 +38,9 @@ for k in range(nb_frame):
     solid = np.invert(((frame[cam_points[1,:],cam_points[0,:]] == background)).all(1))
     cam_points = cam_points[:,solid]
     points = points[solid,:]
-
+print('ok')
 for k in range(nb_frame):
-    frame = cv2.imread(f'data/torus/torus{k+1:04}.png')
+    frame = cv2.imread(f'/tmp/images/Image{k+1:04}.png')
-    # frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
-    # frame = 255 * (frame == 18).astype(np.uint8)
-    # frame = cv2.filter2D(frame, -1, np.ones((5, 5)) / 25)
-    # frame = 255 * (frame > 255/2).astype(np.uint8)
 
     proj_mat = projection_matrices[k]