ludvigla
commented
1 year ago This is likely an issue related to your installation of magick. Can you load and process images without issues using magick?
https://cran.r-project.org/web/packages/magick/vignettes/intro.html
Following is the sessionInfo() output: R version 4.1.0 (2021-05-18) Platform: x86_64-conda-linux-gnu (64-bit) Running under: CentOS Linux 7 (Core)
Matrix products: default BLAS/LAPACK: /public/packages/conda/miniconda3/envs/r4-base/lib/libopenblasp-r0.3.15.so
locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages: [1] STutility_0.1.0 ggplot2_3.3.3 SeuratObject_4.0.1 Seurat_4.0.2
loaded via a namespace (and not attached): [1] uuid_0.1-4 systemfonts_1.0.2 plyr_1.8.6
[4] igraph_1.2.6 lazyeval_0.2.2 sp_1.4-5
[7] splines_4.1.0 crosstalk_1.1.1 listenv_0.8.0
[10] scattermore_0.7 digest_0.6.27 foreach_1.5.1
[13] htmltools_0.5.1.1 viridis_0.6.1 magick_2.7.2
[16] tiff_0.1-8 gdata_2.18.0 fansi_0.5.0
[19] magrittr_2.0.1 tensor_1.5 cluster_2.1.2
[22] doParallel_1.0.16 ROCR_1.0-11 globals_0.14.0
[25] matrixStats_0.59.0 gmodels_2.18.1 spatstat.sparse_2.0-0
[28] jpeg_0.1-8.1 colorspace_2.0-1 ggrepel_0.9.1
[31] xfun_0.23 dplyr_1.0.6 crayon_1.4.1
[34] jsonlite_1.7.2 spatstat.data_2.1-0 zeallot_0.1.0
[37] survival_3.2-11 zoo_1.8-9 iterators_1.0.13
[40] glue_1.4.2 polyclip_1.10-0 gtable_0.3.0
[43] leiden_0.3.8 future.apply_1.7.0 abind_1.4-5
[46] scales_1.1.1 DBI_1.1.1 miniUI_0.1.1.1
[49] Rcpp_1.0.6 viridisLite_0.4.0 xtable_1.8-4
[52] spData_0.3.8 units_0.7-1 reticulate_1.20
[55] spatstat.core_2.1-2 bit_4.0.4 spdep_1.1-8
[58] proxy_0.4-25 akima_0.6-2.1 htmlwidgets_1.5.3
[61] httr_1.4.2 RColorBrewer_1.1-2 ellipsis_0.3.2
[64] ica_1.0-2 farver_2.1.0 pkgconfig_2.0.3
[67] uwot_0.1.10 deldir_0.2-10 utf8_1.2.1
[70] labeling_0.4.2 tidyselect_1.1.1 rlang_0.4.11
[73] manipulateWidget_0.11.0 reshape2_1.4.4 later_1.2.0
[76] munsell_0.5.0 tools_4.1.0 dbscan_1.1-8
[79] generics_0.1.0 ggridges_0.5.3 stringr_1.4.0
[82] fastmap_1.1.0 goftest_1.2-2 bit64_4.0.5
[85] knitr_1.33 fitdistrplus_1.1-5 rgl_0.106.8
[88] purrr_0.3.4 RANN_2.6.1 readbitmap_0.1.5
[91] pbapply_1.4-3 future_1.21.0 nlme_3.1-152
[94] mime_0.10 ggiraph_0.7.10 rstudioapi_0.13
[97] hdf5r_1.3.3 compiler_4.1.0 plotly_4.9.3
[100] png_0.1-7 e1071_1.7-7 spatstat.utils_2.1-0
[103] Morpho_2.8 tibble_3.1.2 stringi_1.6.2.9004
[106] lattice_0.20-44 Matrix_1.3-4 classInt_0.4-3
[109] shinyjs_2.0.0 vctrs_0.3.8 pillar_1.6.1
[112] LearnBayes_2.15.1 lifecycle_1.0.0 spatstat.geom_2.1-0
[115] lmtest_0.9-38 RcppAnnoy_0.0.18 data.table_1.14.0
[118] cowplot_1.1.1 irlba_2.3.3 Rvcg_0.19.2
[121] raster_3.4-10 httpuv_1.6.1 patchwork_1.1.1
[124] colorRamps_2.3 R6_2.5.0 imager_0.42.8
[127] promises_1.2.0.1 KernSmooth_2.23-20 gridExtra_2.3
[130] bmp_0.3 parallelly_1.25.0 codetools_0.2-18
[133] boot_1.3-28 MASS_7.3-54 gtools_3.9.2
[136] withr_2.4.2 sctransform_0.3.2 expm_0.999-6
[139] mgcv_1.8-36 parallel_4.1.0 grid_4.1.0
[142] rpart_4.1-15 tidyr_1.1.3 coda_0.19-4
[145] class_7.3-19 Rtsne_0.15 sf_0.9-8
[148] shiny_1.6.0