Removed invalid tasks names

README.md

@@ -4,8 +4,6 @@ task_categories:
 - image-segmentation
 task_ids:
   - semantic-segmentation
-  - portrait-segmentation
-  - face-parsing
 size_categories:
 - 10K<n<100K
 annotations_creators:
@@ -49,6 +47,8 @@ dataset_info:
 
 # EasyPortrait - Face Parsing and Portrait Segmentation Dataset
 
+![easyportrait](support_images/main.jpg)
+
 We introduce a large-scale image dataset **EasyPortrait** for portrait segmentation and face parsing. Proposed dataset can be used in several tasks, such as background removal in conference applications, teeth whitening, face skin enhancement, red eye removal or eye colorization, and so on. 
 
 EasyPortrait dataset size is about **26GB**, and it contains **20 000** RGB images (~17.5K FullHD images) with high quality annotated masks. This dataset is divided into training set, validation set and test set by subject `user_id`. The training set includes 14000 images, the validation set includes 2000 images, and the test set includes 4000 images.
@@ -57,6 +57,9 @@ Training images were received from 5,947 unique users, while validation was from
 
 For more information see our paper [EasyPortrait – Face Parsing and Portrait Segmentation Dataset](https://arxiv.org/abs/2304.13509).
 
+## The model results trained on the EasyPortrait dataset
+
+
 ## Structure
 ```
 .
@@ -102,7 +105,7 @@ where:
 - `width` - image width
 - `height` - image height
 - `brightness` - image brightness
-- `train`, `test`, `valid` are the binary columns for train / test / val subsets respectively 
+- `train`, `test`, `valid` are the binary columns for train / test / val subsets respectively
 
 ## Authors and Credits
 - [Alexander Kapitanov](https://www.linkedin.com/in/hukenovs)