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Collections-OCR
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added OCR duration to output

This commit is contained in:
magpiedin 2019-11-29 14:12:45 -06:00
parent 77a647b090
commit c6825cb949
1 changed files with 26 additions and 10 deletions
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36
ocrCloudVision.R
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@ -1,6 +1,6 @@
# A script to use Google Cloud Vision to OCR/parse/mangle Collections label-images
# Note!
# - this may take a few seconds per label-image
# - this may take >30 seconds per label-image
# - running >1000 API calls/month incurs a fee
# (c) 2019 The Field Museum - MIT License (https://opensource.org/licenses/MIT)
# https://github.com/fieldmuseum/Collections-OCR
@ -24,6 +24,9 @@ imagenames <- gsub(".jp.*|.JP.*", "", imagelist)
# Setup table for OCRed text
imagesOCR <- data.frame("image" = rep("", NROW(imagelist)),
"imagesize_MB" = rep("", NROW(imagelist)),
"ocr_start" = rep("", NROW(imagelist)),
"ocr_duration" = rep("", NROW(imagelist)),
"line_count" = rep("", NROW(imagelist)),
"text" = rep("", NROW(imagelist)),
stringsAsFactors = F)
@ -35,8 +38,9 @@ imagesOCR$line_count <- as.integer(imagesOCR$line_count)
# # add image_dir if use prompt above
if (!dir.exists("ocr_text")) { # paste0(image_dir, "_out")
dir.create("ocr_text") # paste0(image_dir, "_out")
print("output directory created")
} else {
print("output directory exists")
print("output directory already exists")
}
@ -52,21 +56,33 @@ for (i in 1:NROW(imagelist)) {
# quality = 80)
# OCR image
# CHECK/FIX THIS FXN ####
# ### NOTE! This can take over ~30s per image
print(paste(i, "- starting OCR -", Sys.time()))
imagesOCR$ocr_start[i] <- as.character(Sys.time())
start <- Sys.time()
ocr_list <- gcv_get_image_annotations(imagePaths = paste0("images/", imagelist[i]),
feature = "DOCUMENT_TEXT_DETECTION",
savePath = paste0("ocr_text/",
imagenames[i], "_text.csv"))
feature = "DOCUMENT_TEXT_DETECTION") #,
# savePath = paste0("ocr_text/",
# imagenames[i], "_text.csv"))
print(paste(i, "- finishing OCR -", Sys.time()))
end <- Sys.time()
# Add raw text to dataframe
imagesOCR$text[i] <- read_file(ocr_list$local_path) # CHECK/FIX THIS PATH ####
imagesOCR$text[i] <- ocr_list$description
# Add filename & count of lines in row
# Add OCR duration (in seconds), & text-lines per image, filename, filesize (in MB)
imagesOCR$ocr_duration[i] <- as.integer(end) - as.integer(start)
imagesOCR$line_count[i] <- str_count(ocr_list$description, "\n+")
imagesOCR$image[i] <- imagelist[i]
imagesOCR$line_count[i] <- str_count(ocr_list$local_path, "\n+")
imagesOCR$imagesize_MB[i] <- round(file.info(paste0("images/",
imagelist[i]))$size
/ 1000000, 2)
# show progress
print(paste(i, " - ", Sys.time()))
print(paste(i, "- done -", Sys.time()))
# rate limit to max of 240/min (Vision API limit = 1800/min)
Sys.sleep(0.25)