2022-12-17 14:05:14 +00:00
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import cv2
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import numpy as np
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2023-01-11 12:18:31 +00:00
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from itertools import product
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2023-01-11 16:12:13 +00:00
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import pickle
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2022-12-17 14:05:14 +00:00
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from matrices_reader import *
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2023-01-11 16:12:13 +00:00
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PICKLE_PATH = "/tmp/pickle.truc"
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2023-01-18 16:12:16 +00:00
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VOXEL_SIZE = 2e-2
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X_MIN, X_MAX = -2.0, 2.0
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2022-12-17 14:05:14 +00:00
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Y_MIN, Y_MAX = -2.0, 2.0
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Z_MIN, Z_MAX = -2.0, 2.0
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2023-01-11 16:12:13 +00:00
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with open(PICKLE_PATH, 'rb') as file:
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projection_matrices = pickle.load(file)
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nb_frame = len(projection_matrices) - 1
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2023-01-11 12:18:31 +00:00
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points = np.array([[x, y, z, 1.0] for x, y, z in product(
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np.arange(X_MIN, X_MAX, VOXEL_SIZE),
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np.arange(Y_MIN, Y_MAX, VOXEL_SIZE),
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np.arange(Z_MIN, Z_MAX, VOXEL_SIZE))])
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2023-01-18 16:12:16 +00:00
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points_tor = np.array([[np.cos(theta), np.sin(theta), 0.0, 1.0] for theta, phi, r in product(
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np.arange(0, 2*np.pi, 0.1),
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np.arange(0, 2*np.pi, 0.1),
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np.arange(0.0, 0.25, 0.1))])
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mask = np.array([255, 255, 255])
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# is_in = []
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# p = [0.0, 1.1, 0.0]
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2022-12-17 14:05:14 +00:00
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for k in range(nb_frame):
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2023-01-18 16:12:16 +00:00
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# points = np.array([p +[1.0]])
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frame = cv2.imread(f'/tmp/masks/Image{k+1:04}.png')
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proj_mat = projection_matrices[k]
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2023-01-11 12:18:31 +00:00
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cam_points = proj_mat @ points.T
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cam_points /= cam_points[2,:]
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cam_points = np.round(cam_points).astype(np.int32)
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visible = np.logical_and.reduce((0 <= cam_points[0,:], cam_points[0,:] < frame.shape[1], 0 <= cam_points[1,:], cam_points[1,:] < frame.shape[0]))
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cam_points = cam_points[:,visible]
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points = points[visible,:]
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2022-12-17 14:05:14 +00:00
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2023-01-18 16:12:16 +00:00
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solid = (frame[cam_points[1,:],cam_points[0,:]] == mask).all(axis=1)
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cam_points = cam_points[:,solid]
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points = points[solid,:]
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2023-01-18 16:12:16 +00:00
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# is_in.append(len(points) != 0)
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# points = np.array([p + [1.0]])
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for k in range(nb_frame):
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frame = cv2.imread(f'/tmp/masks/Image{k+1:04}.png')
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2023-01-11 12:18:31 +00:00
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proj_mat = projection_matrices[k]
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cam_points = proj_mat @ points.T
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cam_points /= cam_points[2,:]
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2023-01-18 16:12:16 +00:00
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cam_points = np.round(cam_points).astype(np.int32)
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for cam_point in cam_points.T:
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# cv2.circle(frame, (cam_point[0], cam_point[1]), 2, (255*is_in[k], 0, 255*(not is_in[k])))
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cv2.circle(frame, (cam_point[0], cam_point[1]), 2, (255, 0, 255))
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2023-01-11 12:18:31 +00:00
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2022-12-17 14:05:14 +00:00
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cv2.imshow('Frame', frame)
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cv2.waitKey(0)
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