inst/doc/head_pose.R

In fastai: Interface to 'fastai'

## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE,eval = FALSE,echo = T)

## -----------------------------------------------------------------------------
#  library(fastai)
#  library(magrittr)
#  
#  path = 'biwi_head_pose'
#  fname = '09/frame_00667_rgb.jpg'
#  
#  img = Image_create(paste(path,fname,sep = '/'))
#  img %>% show() %>% plot()
#  cal = readr::read_lines(paste(path,'01/rgb.cal',sep = '/'), n_max = 3) %>% trimws() %>%
#    strsplit('\\s') %>% do.call(rbind,.) %>% apply(.,2,as.numeric)

## -----------------------------------------------------------------------------
#  img2txt_name <- function(f) {
#    paste(
#      substr(f, 1, nchar(f)-7), 'pose.txt',
#      sep = ''
#  
#    )
#  }
#  
#  convert_biwi <- function(coords) {
#    c1 = coords[1] * cal[1,][1]/coords[3] + cal[1,][3]
#    c2 = coords[2] * cal[2,][2]/coords[3] + cal[2,][3]
#    return(tensor(c1,c2))
#  }
#  
#  get_ctr <- function(f) {
#    # trick to make dataloaders work
#    f = as.character(f)
#    ctr = readr::read_lines(img2txt_name(f), skip = 4, n_max = 1) %>% trimws() %>%
#      strsplit('\\s') %>% unlist() %>% as.numeric()
#    convert_biwi(ctr)
#  }
#  
#  get_ip <- function(img, pts) {
#    TensorPoint_create(pts, img_size = img$size)
#  }

## -----------------------------------------------------------------------------
#  ctr = readr::read_lines(img2txt_name(paste(path,fname,sep = '/')),
#                          skip = 4, n_max = 1) %>% trimws() %>%
#        strsplit('\\s') %>% unlist() %>% as.numeric()

## -----------------------------------------------------------------------------
#  ctr = get_ctr(paste(path,fname,sep = '/'))
#  ax = img %>% show(figsize = c(6, 6))
#  img %>% get_ip(ctr) %>% show(ctx = ax) %>% plot()

## -----------------------------------------------------------------------------
#  dblock = DataBlock(blocks = list(ImageBlock(), PointBlock()),
#                     get_items = get_image_files(),
#                     splitter = FuncSplitter(function(x) x$parent$name == '13'),
#                     get_y = get_ctr,
#                     batch_tfms = list(aug_transforms(size = c(120,160)),
#                                       Normalize_from_stats(imagenet_stats()
#                                                            )
#                                       )
#                     )
#  
#  dls = dblock %>% dataloaders(path, path = path, bs = 64)
#  
#  dls %>% show_batch(max_n = 9, figsize = c(9,6))

## -----------------------------------------------------------------------------
#  learn = cnn_learner(dls, resnet34())
#  
#  learn %>% lr_find()
#  
#  learn %>% plot_lr_find()
#  
#  lr = 2e-2
#  
#  learn %>% fit_one_cycle(5, slice(lr))

## -----------------------------------------------------------------------------
#  learn %>% show_results(dpi = 200)