| | |
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| | | cv2_img = cv2.imread(os.path.join(args.data_dir, name + '.jpg')) |
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| | | if args.batch_size == 1: |
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| | | error_string = 'y %.2f, p %.2f, r %.2f' % (torch.sum(torch.abs(yaw_predicted - label_yaw)), torch.sum(torch.abs(pitch_predicted - label_pitch)), torch.sum(torch.abs(roll_predicted - label_roll))) |
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| | | cv2.putText(cv2_img, error_string, (30, cv2_img.shape[0]- 30), fontFace=1, fontScale=1, color=(0,0,255), thickness=1) |
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| | | utils.plot_pose_cube(cv2_img, yaw_predicted[0], pitch_predicted[0], roll_predicted[0]) |
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| | | cv2.putText(cv2_img, error_string, (30, cv2_img.shape[0]- 30), fontFace=1, fontScale=1, color=(0,0,255), thickness=2) |
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| | | # utils.plot_pose_cube(cv2_img, yaw_predicted[0], pitch_predicted[0], roll_predicted[0], size=100) |
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| | | utils.draw_axis(cv2_img, yaw_predicted[0], pitch_predicted[0], roll_predicted[0], tdx = 200, tdy= 200, size=100) |
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| | | cv2.imwrite(os.path.join('output/images', name + '.jpg'), cv2_img) |
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| | | |
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| | | print('Test error in degrees of the model on the ' + str(total) + |
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