[Docs] Translate data_transform.md to English

docs/en/get_started/build.md

@@ -2,7 +2,7 @@
 
 ### Build on Linux or macOS
 
-After cloning the repo with
+Clone the repo with
 
 ```bash
 git clone https://github.com/open-mmlab/mmcv.git
@@ -24,7 +24,7 @@ You can either
   MMCV_WITH_OPS=0 pip install -e .
   ```
 
-- install the full version
+- or install the full version
 
   ```bash
   pip install -e .

docs/en/get_started/introduction.md

@@ -22,7 +22,7 @@ research projects as below:
 - [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab image and video generative models toolbox.
 - [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab model deployment framework.
 
-It provides the following functionalities.
+It provides the following functionalities:
 
 - Universal IO APIs
 - Image/Video processing

docs/en/understand_mmcv/cnn.md

@@ -106,15 +106,15 @@ An example json file could be like:
 
 The default links of the pre-trained models hosted on OpenMMLab AWS could be found [here](https://github.com/open-mmlab/mmcv/blob/master/mmcv/model_zoo/open_mmlab.json).
 
-You may override default links by putting `open-mmlab.json` under `MMCV_HOME`. If `MMCV_HOME` is not find in the environment, `~/.cache/mmcv` will be used by default. You may `export MMCV_HOME=/your/path` to use your own path.
+You may override default links by putting `open-mmlab.json` under `MMCV_HOME`. If `MMCV_HOME` is not found in your environment, `~/.cache/mmcv` will be used by default. You may use your own path with `export MMCV_HOME=/your/path`.
 
 The external json files will be merged into default one. If the same key presents in both external json and default json, the external one will be used.
 
 #### Load Checkpoint
 
-The following types are supported for `filename` argument of `mmcv.load_checkpoint()`.
+The following types are supported for `filename` of `mmcv.load_checkpoint()`.
 
 - filepath: The filepath of the checkpoint.
 - `http://xxx` and `https://xxx`: The link to download the checkpoint. The `SHA256` postfix should be contained in the filename.
-- `torchvision://xxx`: The model links in `torchvision.models`.Please refer to [torchvision](https://pytorch.org/docs/stable/torchvision/models.html) for details.
+- `torchvision://xxx`: The model links in `torchvision.models`. Please refer to [torchvision](https://pytorch.org/docs/stable/torchvision/models.html) for details.
 - `open-mmlab://xxx`: The model links or filepath provided in default and additional json files.

docs/en/understand_mmcv/data_process.md

@@ -2,7 +2,7 @@
 
 ### Image
 
-This module provides some image processing methods, which requires `opencv` to be installed.
+This module provides some image processing methods, which requires `opencv` to be installed first.
 
 #### Read/Write/Show
 
@@ -118,7 +118,7 @@ mmcv.imflip(img, direction='vertical')
 
 #### Crop
 
-`imcrop` can crop the image with one or some regions, represented as (x1, y1, x2, y2).
+`imcrop` can crop the image with one or more regions. Each region is represented by the upper left and lower right coordinates as (x1, y1, x2, y2).
 
 ```python
 import mmcv
@@ -140,7 +140,7 @@ patches = mmcv.imcrop(img, bboxes, scale=1.2)
 
 #### Padding
 
-There are two methods `impad` and `impad_to_multiple` to pad an image to the
+There are two methods, `impad` and `impad_to_multiple`, to pad an image to the
 specific size with given values.
 
 ```python
@@ -165,7 +165,7 @@ img_ = mmcv.impad_to_multiple(img, 32)
 
 ### Video
 
-This module provides the following functionalities.
+This module provides the following functionalities:
 
 - A `VideoReader` class with friendly apis to read and convert videos.
 - Some methods for editing (cut, concat, resize) videos.