add vision_make_grid support multiple tensors

NAMESPACE

@@ -176,6 +176,9 @@ S3method(transform_to_tensor,list)
 S3method(transform_to_tensor,matrix)
 S3method(transform_vflip,default)
 S3method(transform_vflip,torch_tensor)
+S3method(vision_make_grid,"magick-image")
+S3method(vision_make_grid,default)
+S3method(vision_make_grid,torch_tensor)
 export(base_loader)
 export(batched_nms)
 export(box_area)

NEWS.md

@@ -39,6 +39,7 @@
 
 ## Bug fixes and improvements
 
+* `vision_make_grid()` now accepts multiple 3D tensors with mixed uint8 and float dtype (#398).
 * `transform_random_affine()` now accepts a bare number for `shear`. It used to widen `degrees`
   instead of `shear`, which left the shear range incomplete and made the sampling fail (#390).
 * `item_transform_rotate()` no longer truncates the rotation angle to a whole number of degrees

R/collection-rf100-biology.R

@@ -104,6 +104,7 @@ rf100_biology_collection <- torch::dataset(
     size = c(81, 24, 12, 6.4, 1.8, 0.9 , 65.1,17.9,9,  0.3, 0.1, 0.05,
              1.4, 2.5, 0.8,   62, 16.8, 9,
              19, 5.3, 2.7,   69,9.0, 5.7,   192,55.6, 28,
-             45, 13, 4.5) * 1e6
+             45, 13, 4.5) * 1e6,
+    stringsAsFactors = FALSE
   )
 )

R/collection-rf100-damage.R

@@ -54,6 +54,7 @@ rf100_damage_collection <- torch::dataset(
       # asbestos
       "f53af703c4ce594c3950d7e732003f2d",      "8e99904ce49e7f0e830735fb22986868",      "4fef507d057690d1a55fa043696248cc"
     ),
-    size = c(21.5, 5.7, 1.4,   8.5, 2.3, 1.5,  28, 7.8, 4) * 1e6
+    size = c(21.5, 5.7, 1.4,   8.5, 2.3, 1.5,  28, 7.8, 4) * 1e6,
+    stringsAsFactors = FALSE
   )
 )

R/collection-rf100-doc.R

@@ -133,7 +133,8 @@ rf100_document_collection <- torch::dataset(
       "ca0b96eb696da512eed629895a433bad"
     ),
 
-    size = c(rep(50, 18), 32, 9, 5, 108, 32, 23) * 1e6 # placeholder; optional
+    size = c(rep(50, 18), 32, 9, 5, 108, 32, 23) * 1e6, # placeholder; optional
+    stringsAsFactors = FALSE
   ),
 
   initialize = function(

R/dataset-pascal.R

@@ -112,7 +112,8 @@ pascal_segmentation_dataset <- torch::dataset(
             "da459979d0c395079b5c75ee67908abb",
             "6c3384ef61512963050cb5d687e5bf1e",
             "6cd6e144f989b92b3379bac3b3de84fd"),
-    size = c("440 MB", "440 MB", "550 MB", "890 MB", "1.3 GB", "1.7 GB", "1.9 GB")
+    size = c("440 MB", "440 MB", "550 MB", "890 MB", "1.3 GB", "1.7 GB", "1.9 GB"),
+    stringsAsFactors = FALSE
   ),
   classes = pascal_voc_classes(),
   voc_colormap = c(

R/dataset-plankton.R

@@ -56,7 +56,8 @@ whoi_small_plankton_dataset <- torch::dataset(
             "170921030aee26f9676725a0c55a4420",
             "332ebc8b822058cd98f778099927c50e",
             "f0747ae16fc7cd6946ea54c3fe1f30b4"),
-    size = c(217e6, 396e6, 383e6, 112e6)
+    size = c(217e6, 396e6, 383e6, 112e6),
+    stringsAsFactors = FALSE
   ),
 
   initialize = function(
@@ -171,7 +172,8 @@ whoi_plankton_dataset <- torch::dataset(
             "0f4d47f240cd9c30a7dd786171fa40ca",
             "db827a7de8790cdcae67b174c7b8ea5e",
             "d3181d9ffaed43d0c01f59455924edca"),
-    size = c(rep(450e6, 4), rep(490e6, 13), rep(450e6, 2))
+    size = c(rep(450e6, 4), rep(490e6, 13), rep(450e6, 2)),
+    stringsAsFactors = FALSE
   )
 )
 
@@ -201,6 +203,7 @@ whoi_small_coralnet_dataset <- torch::dataset(
             "f4dd2d2effc1f9c02918e3ee614b85d3",
             "d66ec691a4c5c63878a9cfff164a6aaf",
             "7ea146b9b2f7b6cee99092bd44182d06"),
-    size = c(430e6, rep(380e6, 4), 192e6)
+    size = c(430e6, rep(380e6, 4), 192e6),
+    stringsAsFactors = FALSE
   )
 )

R/dataset-vggface2.R

@@ -49,7 +49,8 @@ vggface2_dataset <- torch::dataset(
             "bb7a323824d1004e14e00c23974facd3",
             "d08b10f12bc9889509364ef56d73c621",
             "d315386c7e8e166c4f60e27d9cc61acc"),
-    size = c(37.9e9, 62e6, 2.03e9, 3e6, 335e3)
+    size = c(37.9e9, 62e6, 2.03e9, 3e6, 335e3),
+    stringsAsFactors = FALSE
   ),
   initialize = function(
     root = tempdir(),

R/item-transforms-geometry.R

@@ -34,12 +34,11 @@
 #'
 #' after <- item_transform_rotate(before, angle = angle)
 #'
-#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)$to(torch_float())$div(255)
-#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)$to(torch_float())$div(255)
+#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)
+#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)
 #'
-#' grid <- vision_make_grid(
-#'   torch_stack(list(transform_resize(before_plot, c(600, 600)),
-#'                    transform_resize(after_plot, c(600, 600)))),
+#' grid <- vision_make_grid(transform_resize(before_plot, c(600, 600)),
+#'                          transform_resize(after_plot, c(600, 600)),
 #'   scale = TRUE
 #' )
 #' tensor_image_browse(grid)
@@ -241,14 +240,14 @@ item_transform_rotate.image_with_rotated_box <- function(x, angle, interpolation
 #'
 #' after <- item_transform_crop(before, top = 100, left = 200, height = 500, width = 800)
 #'
-#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)$to(torch_float())$div(255)
-#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)$to(torch_float())$div(255)
-#'
-#' before_plot <- transform_resize(before_plot, c(2000, 3000))
-#' after_plot <- transform_resize(after_plot, c(2000, 3000))
+#' before_plot <- before %>%
+#'   draw_bounding_boxes(colors = "blue", width = 10) %>%
+#'   transform_resize(c(2000, 3000))
+#' after_plot <- after %>%
+#'   draw_bounding_boxes(colors = "red", width = 10) %>%
+#'   transform_resize(c(2000, 3000))
 #'
-#' grid <- vision_make_grid(torch_stack(list(before_plot, after_plot)), scale = TRUE)
-#' tensor_image_browse(grid)
+#' tensor_image_browse(vision_make_grid(before_plot, after_plot, scale = TRUE))
 #' }
 #'
 #' @family item_unitary_transforms
@@ -399,10 +398,10 @@ item_transform_crop.image_with_rotated_box <- function(x, top, left, height, wid
 #'
 #' after <- item_transform_hflip(before)
 #'
-#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)$to(torch_float())$div(255)
-#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)$to(torch_float())$div(255)
+#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)
+#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)
 #'
-#' grid <- vision_make_grid(torch_stack(list(before_plot, after_plot)), scale = TRUE)
+#' grid <- vision_make_grid(before_plot, after_plot, scale = TRUE)
 #' tensor_image_browse(grid)
 #' }
 #'
@@ -502,11 +501,10 @@ item_transform_hflip.image_with_rotated_box <- function(x) {
 #'
 #' after <- item_transform_vflip(before)
 #'
-#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)$to(torch_float())$div(255)
-#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)$to(torch_float())$div(255)
+#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)
+#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)
 #'
-#' grid <- vision_make_grid(torch_stack(list(before_plot, after_plot)), scale = TRUE)
-#' tensor_image_browse(grid)
+#' tensor_image_browse(vision_make_grid(before_plot, after_plot, scale = TRUE))
 #' }
 #'
 #' @family item_unitary_transforms
@@ -613,14 +611,13 @@ item_transform_vflip.image_with_rotated_box <- function(x) {
 #'
 #' after <- item_transform_center_crop(before, size = c(1500, 1500))
 #'
-#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)$to(torch_float())$div(255)
-#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)$to(torch_float())$div(255)
+#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)
+#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)
 #'
 #' before_plot <- transform_resize(before_plot, c(1500, 1500))
 #' after_plot <- transform_resize(after_plot, c(1500, 1500))
 #'
-#' grid <- vision_make_grid(torch_stack(list(before_plot, after_plot)), scale = TRUE)
-#' tensor_image_browse(grid)
+#' tensor_image_browse(vision_make_grid(before_plot, after_plot, scale = TRUE))
 #' }
 #'
 #' @family item_unitary_transforms
@@ -917,14 +914,13 @@ item_transform_affine.dataset <- function(x, angle = 0, translate = c(0, 0),
 #'
 #' after <- item_transform_pad(before, padding = 100)
 #'
-#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)$to(torch_float())$div(255)
-#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)$to(torch_float())$div(255)
+#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)
+#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)
 #'
 #' before_plot <- transform_resize(before_plot, c(2000, 3000))
 #' after_plot <- transform_resize(after_plot, c(2000, 3000))
 #'
-#' grid <- vision_make_grid(torch_stack(list(before_plot, after_plot)), scale = TRUE)
-#' tensor_image_browse(grid)
+#' tensor_image_browse(vision_make_grid(before_plot, after_plot, scale = TRUE))
 #' }
 #'
 #' @family item_unitary_transforms
@@ -1087,11 +1083,10 @@ item_transform_pad.image_with_rotated_box <- function(x, padding, fill = 0, padd
 #'
 #' after <- item_transform_perspective(before, startpoints, endpoints)
 #'
-#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)$to(torch_float())$div(255)
-#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)$to(torch_float())$div(255)
+#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)
+#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)
 #'
-#' grid <- vision_make_grid(torch_stack(list(before_plot, after_plot)), scale = TRUE)
-#' tensor_image_browse(grid)
+#' tensor_image_browse(vision_make_grid(before_plot, after_plot, scale = TRUE))
 #' }
 #'
 #' @family item_unitary_transforms

R/item-transforms-random-geometry.R

@@ -25,11 +25,10 @@
 #'
 #' after <- item_transform_random_horizontal_flip(before)
 #'
-#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)$to(torch_float())$div(255)
-#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)$to(torch_float())$div(255)
+#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)
+#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)
 #'
-#' grid <- vision_make_grid(torch_stack(list(before_plot, after_plot)), scale = TRUE)
-#' tensor_image_browse(grid)
+#' tensor_image_browse(vision_make_grid(before_plot, after_plot, scale = TRUE))
 #' }
 #'
 #' @family item_random_transforms
@@ -111,11 +110,10 @@ item_transform_random_horizontal_flip.image_with_rotated_box <- function(x, p =
 #'
 #' after <- item_transform_random_vertical_flip(before)
 #'
-#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)$to(torch_float())$div(255)
-#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)$to(torch_float())$div(255)
+#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)
+#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)
 #'
-#' grid <- vision_make_grid(torch_stack(list(before_plot, after_plot)), num_rows = 1, scale = TRUE)
-#' tensor_image_browse(grid)
+#' tensor_image_browse(vision_make_grid(before_plot, after_plot, per_row = 1, scale = TRUE))
 #' }
 #'
 #' @family item_random_transforms
@@ -365,16 +363,15 @@ rescale_box_angle <- function(angle_deg, scale_w, scale_h) {
 #'
 #' after <- item_transform_random_crop(before, size = c(800, 1200))
 #'
-#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)$to(torch_float())$div(255)
-#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)$to(torch_float())$div(255)
+#' # the crop will changes the image size, so resize is needed before vision_make_grid
+#' before_plot <- before %>%
+#'   draw_bounding_boxes(colors = "blue", width = 10) %>%
+#'   transform_resize(c(600, 600))
+#' after_plot <- after %>%
+#'   draw_bounding_boxes(colors = "red", width = 10) %>%
+#'   transform_resize(c(600, 600))
 #'
-#' # the crop changes the image size, so resize before stacking into the grid
-#' grid <- vision_make_grid(
-#'   torch_stack(list(transform_resize(before_plot, c(600, 600)),
-#'                    transform_resize(after_plot, c(600, 600)))),
-#'   scale = TRUE
-#' )
-#' tensor_image_browse(grid)
+#' tensor_image_browse(vision_make_grid(before_plot, after_plot))
 #' }
 #'
 #' @family item_random_transforms
@@ -777,11 +774,10 @@ item_transform_random_rotation.image_with_segmentation_mask <- item_transform_ra
 #'
 #' after <- item_transform_random_erasing(before)
 #'
-#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)$to(torch_float())$div(255)
-#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)$to(torch_float())$div(255)
+#' before_plot <- draw_bounding_boxes(before, colors = "blue", width = 10)
+#' after_plot <- draw_bounding_boxes(after, colors = "red", width = 10)
 #'
-#' grid <- vision_make_grid(torch_stack(list(before_plot, after_plot)), scale = TRUE)
-#' tensor_image_browse(grid)
+#' tensor_image_browse(vision_make_grid(before_plot, after_plot, scale = TRUE))
 #' }
 #'
 #' @family item_random_transforms

R/models-faster_rcnn.R

@@ -980,7 +980,7 @@ mobilenet_v3_320_fpn_backbone <- function(pretrained = TRUE) {
 #' batch_normalized <- input$unsqueeze(1)    # Add batch dimension (1, 3, H, W)
 #'
 #' # ResNet-50 FPN V2
-#' model <- model_fasterrcnn_resnet50_fpn_v2(pretrained = TRUE, , detections_per_img = 5 )
+#' model <- model_fasterrcnn_resnet50_fpn_v2(pretrained = TRUE, detections_per_img = 5 )
 #' model$eval()
 #' torch::with_no_grad({pred <- model(batch_normalized)$detections[[1]]})
 #' labels <- coco_classes(as.integer(pred$labels))

R/models-mask_rcnn.R

@@ -562,7 +562,7 @@ maskrcnn_model_v2 <- torch::nn_module(
 #' batch <- input$unsqueeze(1)
 #'
 #' # Mask R-CNN ResNet-50 FPN
-#' model <- model_maskrcnn_resnet50_fpn(pretrained = TRUE, , detections_per_img = 5)
+#' model <- model_maskrcnn_resnet50_fpn(pretrained = TRUE, detections_per_img = 5)
 #' model$eval()
 #'
 #' torch::with_no_grad({pred <- model(batch)$detections[[1]]})

R/models-vgg.R

@@ -10,7 +10,7 @@ VGG <- torch::nn_module(
       torch::nn_linear(4096, 4096),
       torch::nn_relu(TRUE),
       torch::nn_dropout(),
-      torch::nn_linear(4096, num_classes),
+      torch::nn_linear(4096, num_classes)
     )
 
     if (init_weights)

R/target-transforms-detection.R

@@ -277,11 +277,7 @@ target_transform_sahi_crop.object_detection_target <- function(y, sahi_split, mi
 #' # Rotated boxes (red, drawn as polygons)
 #' after_plot <- draw_bounding_boxes(img, boxes = rotated_target$boxes, colors = "red", width = 10)
 #'
-#' grid <- vision_make_grid(
-#'   torch_stack(list(before_plot, after_plot))$to(torch_float32()),
-#'   scale = TRUE
-#' )
-#' tensor_image_browse(grid)
+#' tensor_image_browse(vision_make_grid(before_plot, after_plot, scale = TRUE))
 #' }
 #'
 #' @family target_transforms_detection

R/transforms-generics.R

@@ -358,7 +358,7 @@ transform_ten_crop <- function(img, size, vertical_flip = FALSE) {
 #'   class(item) <- "image_with_bounding_box"
 #'   draw_bounding_boxes(item, colors = "red")
 #' })
-#' grid <- vision_make_grid(torch_stack(preview), scale = FALSE, num_rows = 3)
+#' grid <- vision_make_grid(torch_stack(preview), scale = FALSE, per_row = 3)
 #' tensor_image_browse(grid)
 #' }
 #'