docs: refresh how-to-download-images.md (#10164)

- Use v2 API
- Give more specific guidelines for when to use AWS
- Use "images" consistently in openfoodfacts domain name
- While there, lightly copyedit

docs/api/how-to-download-images.md

@@ -1,29 +1,29 @@
 # How to download product images
 
 The preferred method of downloading Open Food Facts images depends on what you
-which to achieve.
+wish to achieve.
 
-If you want to download a limited number of images, especially if these images
-have been uploaded recently, you should [download the image from Open Food
+If you want to download a few images (say up to 10), especially if these images
+have been uploaded recently, you should [download the image from the Open Food
 Facts
 server](./how-to-download-images.md#download-from-open-food-facts-server).
 
-If you plan to download a large amount of images, you should on the contrary
-[use Open Food Facts images dataset hosted on
+If you plan to download more images, you should instead
+[use the Open Food Facts images dataset hosted on
 AWS](./how-to-download-images.md#download-from-aws).
 
 ## Download from AWS
 
-If you want to download a large number of images, this is the recommended
-option, as AWS S3 will be faster and allow concurrent download, contrary to
+If you want to download many images, this is the recommended
+option, as AWS S3 is faster and allows concurrent download, unlike the
 Open Food Facts server, where you should preferably download images one at a
 time. See [AWS Images dataset](./aws-images-dataset.md) for more information
-about how to download images from AWS dataset.
+about how to download images from the AWS dataset.
 
 ## Download from Open Food Facts server
 
-All images are hosted under
-[https://images.openfoodfacts.org/images/products/](https://static.openfoodfacts.org/images/products/) folder. 
+All images are hosted under the
+[https://images.openfoodfacts.org/images/products/](https://images.openfoodfacts.org/images/products/) folder. 
 But you have to build the right URL from the product info.
 
 ### Computing single product image folder
@@ -32,13 +32,13 @@ Images of a product are stored in a single directory. The path of this
 directory can be inferred easily from the product barcode.
 There are two cases:
 
-1. If the product barcode length is lower or equal to 8 (ex: "22222222"), the directory path is
+1. If the product barcode is 8 digits long or shorter (ex: "22222222"), the directory path is
 simply the barcode: `https://images.openfoodfacts.org/images/products/{barcode}`.
 
-2. Otherwise, we split the 9 first part of the code by group of three digits to get the three first folder names, and use the rest of the name as the last folder name^[split-regexp].
-   For example, the barcode `3435660768163` is split as : `343/566/076/8163`, thus products images will be in `https://images.openfoodfacts.org/images/products/343/566/076/8163`
+2. Otherwise, split the first 9 digits of the barcode into 3 groups of 3 digits to get the first 3 folder names, and use the rest of the barcode as the last folder name^[split-regexp].
+   For example, barcode `3435660768163` is split into: `343/566/076/8163`, thus product images will be in `https://images.openfoodfacts.org/images/products/343/566/076/8163`
 
-^[split-regexp]: The following regex can be used to split the barcode into subfolders: `r"^(...)(...)(...)(.*)$"`
+^[split-regexp]: The following regex can be used to split the barcode into subfolders: `/^(...)(...)(...)(.*)$/`
 
 ### Computing single image file name
 
@@ -49,7 +49,7 @@ Above we get the folder name, now we need the filename inside that folder for a
 To get the image file names, we have to use the database dump or the API. 
 All images information are stored in the `images` field. 
 
-Eg. For product [3168930010883](https://world.openfoodfacts.org/api/v0/product/3168930010883.json),
+Eg. For product [3168930010883](https://world.openfoodfacts.org/api/v2/product/3168930010883.json),
 we have (trimmed the data):
 
 ```json
@@ -123,7 +123,7 @@ The available resolutions can be found in the `sizes` subfield.
 #### Filename for a raw image
 
 For a raw image (the one under a numeric key in images field), 
-filename is very easy to compute: 
+the filename is very easy to compute: 
 * just take the image digit + `.jpg` for full resolution
 * image digit + `.` + resolution + `.jpg` for a lower resolution
 
@@ -158,7 +158,7 @@ So, adding the folder part, the final url for our example is:
 
 ## A python snippet
 
-So if we have the product_data in a dict, a Python code doing it would be something like:
+So if we have the product_data in a dict, Python code for doing it would be something like:
 
 ```python
 def get_image_url(product_data, image_name, resolution="full"):