123 lines
3.5 KiB
R
123 lines
3.5 KiB
R
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# A script to use Google apps to OCR/parse/mangle Collections label-images
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# Note - this may take a few seconds per label-image
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# (c) 2019 The Field Museum - MIT License (https://opensource.org/licenses/MIT)
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# https://github.com/fieldmuseum/Collections-OCR
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library(googledrive)
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library(tidyr)
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library(readr)
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library(stringr)
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# get list of local JPG & JPEG image files [REVERT]
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imagelist <- list.files(path = "images/", pattern = ".jp|.JP")
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imagenames <- gsub(".jp.*|.JP.*", "", imagelist)
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# NOTE - update path to appropriate google folder
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googleFolder <- "https://drive.google.com/drive/folders/1fOI5JC1naQtfBZ2mXlWFlBOq2bKN17KA"
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# googleFolder <- readline("Paste the URL to a googledrive here: ")
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# Upload & OCR ####
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# Loop through each label-image
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for (i in 1:NROW(imagelist)) {
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# Setup Google Doc for image
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drive_upload(media = paste0("images/", imagelist[i]),
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path = as_id(googleFolder),
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name = paste0(imagenames[i], "_text"),
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type = "document",
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overwrite = FALSE)
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print(paste(i, " - ", Sys.time()))
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}
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# get list of OCR text files
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filelist <- drive_ls(path = as_id(googleFolder),
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recursive = FALSE)
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textlist <- filelist[grepl("_text", filelist$name)==TRUE,]
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# Retrieve OCR text ####
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# Setup table for OCRed text
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imagesOCR <- data.frame("image" = rep("", NROW(textlist)),
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"line_count" = rep("", NROW(textlist)),
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"text" = rep("", NROW(textlist)),
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stringsAsFactors = F)
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imagesOCR$line_count <- as.integer(imagesOCR$line_count)
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if (!dir.exists("ocr_text")) {
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dir.create("ocr_text")
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} else {
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print("'ocr_text' directory exists")
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}
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# Download the OCR'ed label-images
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for (i in 1:NROW(textlist)) {
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# Setup Google Doc for image
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dllist <- drive_download(file = as_id(textlist$id[i]),
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path = paste0("ocr_text/", textlist$name),
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type = "txt",
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overwrite = FALSE)
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# OCR the image to text
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imagesOCR$text[i] <- read_file(dllist$local_path)
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# include filename & count of lines in row
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imagesOCR$image[i] <- imagelist[i]
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imagesOCR$line_count[i] <- str_count(ocrText, "\n+")
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# show progress
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print(paste(i, " - ", Sys.time()))
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}
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# # loop through each label-image
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# for (i in 1:NROW(imagelist)) {
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#
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# # # Setup Google Doc for image
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# # drive_put(media = "images/PE78981_label.jpg",
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# # path = as_id("https://drive.google.com/drive/folders/1fOI5JC1naQtfBZ2mXlWFlBOq2bKN17KA"),
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# # name = "test_text",
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# # type = "document")
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#
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# # OCR the image to text
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# ocrText <- image_read(paste0("images/", imagelist[i])) %>%
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# image_ocr(language = c("eng", "lat", "deu"))
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# imagesOCR$text[i] <- ocrText
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#
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# # include filename & count of lines in row
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# imagesOCR$image[i] <- imagelist[i]
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# imagesOCR$line_count[i] <- str_count(ocrText, "\n+")
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#
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# # show progress
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# print(paste(i, " - ", Sys.time()))
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#
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# }
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# split text lines to separate columns
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ocrText <- separate(imagesOCR, text,
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into = paste0("Line",
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seq(1:max(imagesOCR$line_count, na.rm = T))),
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# into = seq(1:20), # if need consistent NCOL
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sep = "(\n)+",
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extra = "merge", fill = "right")
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# export CSV
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write.csv(ocrText,
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paste0("ocrText-",
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gsub("\\s+|:", "", Sys.time()),
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".csv"),
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na = "",
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row.names = F)
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