move convert dir to tools dir

Author: tzutalin

convert/README.md renamed to tools/README.md

@@ -1,12 +1,14 @@
-# Convert the label files to CSV
+# Additional tools
 
-## Introduction
+## Convert the label files to CSV
+
+### Introduction
 To train the images on [Google Cloud AutoML](https://cloud.google.com/automl), we should prepare the specific csv files follow [this format](https://cloud.google.com/vision/automl/object-detection/docs/csv-format).
 
 `label_to_csv.py` can convert the `txt` or `xml` label files to csv file. The labels files should strictly follow to below structure.
 
-## Structures
-* Images  
+### Structures
+* Images
     To train the object detection tasks, all the images should upload to the cloud storage and access it by its name. All the images should stay in the **same buckets** in cloud storage. Also, different classes should have their own folder as below.
     ```
     <bucket_name> (on the cloud storage)
@@ -21,7 +23,7 @@ To train the images on [Google Cloud AutoML](https://cloud.google.com/automl), w
     | ...
     ```
     Note, URI of the `class1_01.jpg` is `gs://<bucket_name>/class1/class1_01.jpg`
-* Labels  
+* Labels
     There are four types of training data - `TRAINING`, `VALIDATION`, `TEST` and `UNASSIGNED`. To assign different categories, we should create four directories.
     Inside each folder, users should create the class folders with the same name in cloud storage (see below structure).
     ```
@@ -33,22 +35,22 @@ To train the images on [Google Cloud AutoML](https://cloud.google.com/automl), w
     |    | -- class2
     |    |    | -- class2_01.txt (or .xml)
     |    |    | ...
-    |    | ... 
+    |    | ...
     | -- VALIDATION
     |    | -- class1
     |    |    | -- class1_02.txt (or .xml)
     |    |    | ...
     |    | -- class2
     |    |    | -- class2_02.txt (or .xml)
     |    |    | ...
-    |    | ... 
+    |    | ...
     | -- TEST
     |    | (same as TRAINING and VALIDATION)
     | -- UNASSIGNED
     |    | (same as TRAINING and VALIDATION)
     ```
-  
-## Usage
+
+### Usage
 
 To see the argument of `label_to_csv.py`,
 ```commandline
@@ -82,4 +84,4 @@ python label_to_csv.py \
 ```
 
 The output file is `res.csv` by default. Afterwards, upload the csv file to the cloud storage and you can start training!
-    
+