Update README.md

README.md

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 license: cc
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+
+# Google WIT Vietnamese
+
+This data repos contain extracted data from [Google WIT](https://github.com/google-research-datasets/wit/blob/main/DATA.md). The extracted data is all for Vietnamese language. 
+
+Given `x` is a data point in the OG dataset which has keys following OG `field_name`, the criteria to filter is
+```python
+criteria = lambda x: x.get("language", "") == "vi" and x.get("caption_reference_description", "")
+```
+
+## Text-related details
+
+All `.tsv.gz` files follow OG data files in terms of file names and file structures.
+
+### Train split
+
+`wit_v1.train.*.tsv.gz`
+
+Train data length of each file (not including the header),
+```
+17690
+17756
+17810
+17724
+17619
+17494
+17624
+17696
+17777
+17562
+```
+Total 176752
+
+### Validation split
+
+`wit_v1.val.*.tsv.gz`
+
+Val data length of each file (not including the header),
+```
+292
+273
+275
+320
+306
+```
+Total 1466
+
+### Test split
+
+`wit_v1.test.*.tsv.gz`
+
+Test data length of each file (not including the header),
+```
+215
+202
+201
+201
+229
+```
+Total 1048
+
+## Image-related details
+
+### Image URL only
+
+`*.image_url_list.txt` are simply lists of image urls from `*.tsv.gz` files
+
+Image url length of each file (train, val, test, all)
+```
+157281
+1271
+900
+159452
+```
+Google Research has made sure that all sets don't share same exact images.
+
+### Downloaded Images
+
+⚠ Please for the love of the gods, read this section carefully.
+
+For `all.index.fmt_id.image_url_list.tsv`, from left to right, without headers, the columns are `index`, `fmt_id`, `image_url`. It is to map `image_url` (in `all.image_url_list.txt`) to `fmt_id`. It's for downloading images.
+
+`fmt_id` is:
+- used to name images (with proper image extensions) in `images/`.
+- `index` but filled with 6 zeros
+
+Downloading time was less than 36 hours with:
+- 90 Mbps
+- Processor	Intel(R) Core(TM) i7-8550U CPU @ 1.80GHz   1.99 GHz
+- No asynchronous 
+
+For `fail.index.fmt_id.status.image_url_list.tsv`, from left to right, without headers, the columns are `index`, `fmt_id`, `status`, `image_url`. It is to track image urls (during downloading) that are inaccessible.
+
+3367 image urls returned 404 (`status` values). In other words, we were able to download 97.88839275% of images.
+
+`images/` folder takes disk space of:
+- 215 GBs (uncompressed)
+- 209 GBs (compressed)
+
+We use Pillow to open each image to make sure that downloaded images are usable. We also log all faulty files in `corrupted_image_list.json`. There are less than 70 image files.
+
+For `corrupted_image_list.json`, for each item in this list, the keys are `file_name`, `error`. `file_name` is `fmt_id` with extension but without `images/`. Some errors are either:
+- files exceed Pillow default limit
+- files are truncated
+
+To actually load those files, the following code can be used to change Pillow behavior
+```python
+from PIL import Image, ImageFile
+
+# For very big image files
+Image.MAX_IMAGE_PIXELS = None
+
+# For truncated image files
+ImageFile.LOAD_TRUNCATED_IMAGES = True
+```
+
+Zip `images/` folder,
+```bash
+zip -r images.zip images/
+zip images.zip --out spanned_images.zip -s 40g
+```
+https://superuser.com/questions/336219/how-do-i-split-a-zip-file-into-multiple-segments
+
+Unzip `spanned_images.*` files,
+```bash
+zip -s 0 spanned_images.zip --out images.zip
+unzip images.zip
+```
+https://unix.stackexchange.com/questions/40480/how-to-unzip-a-multipart-spanned-zip-on-linux