Update README.md

README.md

@@ -58,6 +58,30 @@ You can use this as an example.
 
    At this step, we should have darknet annotations(.txt) and a training list(.txt).
 
+   Upon labeling, the format of annotations generated by [BBox-Label-Tool](https://github.com/puzzledqs/BBox-Label-Tool) is:
+
+   class_number
+
+   box1_x1 box1_y1 box1_width box1_height
+
+   box2_x1 box2_y1 box2_width box2_height
+
+   ....
+
+   After conversion, the format of annotations converted by [scripts/convert.py](https://github.com/Guanghan/darknet/blob/master/scripts/convert.py) is:
+
+   class_number box1_x1_ratio box1_y1_ratio box1_width_ratio box1_height_ratio
+
+   class_number box2_x1_ratio box2_y1_ratio box2_width_ratio box2_height_ratio
+
+   ....
+
+   Note that each image corresponds to an annotation file. But we only need one single training list of images. Remember to put the folder "images" and folder "annotations" in the same parent directory, as the darknet code look for annotation files this way (by default). 
+
+   You can download some examples to understand the format:
+
+
+
 3. Modify Some Code
 
    (1) In [src/yolo.c](https://github.com/Guanghan/darknet/blob/master/src/yolo.c), change class numbers and class names. (And also the paths to the training data and the annotations, i.e., the list we obtained from step 2. )