Update README.md

README.md

@@ -5,12 +5,11 @@ task_categories:
 tags:
 - ui
 - user-interface
-- synthetic
 - web-design
 - gui
-pretty_name: Synthetic UI Dataset
+pretty_name: Web UI Dataset
 size_categories:
-- 1K<n<10K
+- n<1K
 dataset_info:
   features:
   - name: image
@@ -31,31 +30,30 @@ dataset_info:
         '5': text
   splits:
   - name: train
-    num_examples: 4500
-  - name: val
-    num_examples: 500
+    num_examples: 185
+  - name: validation
+    num_examples: 45
 configs:
 - config_name: default
   data_files:
   - split: train
-    path: data/train-*
+    path: train/*
   - split: validation
-    path: data/val/*
+    path: val/*
 language:
 - ru
 - en
 ---
 
-# Synthetic UI Dataset
+# Web UI Dataset
 
 ## Dataset Description
 
-This dataset contains synthetically generated images of User Interfaces designed for object detection tasks. It includes diverse layouts and styles to robustly train models on identifying common web elements across various screen sizes.
+This dataset consists of real-world screenshots of web user interfaces, annotated for object detection. It is designed to be used in pair with the [Synthetic UI Dataset](https://huggingface.co/datasets/egnch/synthetic-ui) for fine-tuning and model validation.
 
-- **Total Images:** 5000
-- **Viewport Range:** 375px to 1920px
+- **Total Images:** 250
 - **Task:** Object Detection
-- **Source:** Synthetic Generation
+- **Source:** Annotation of websites screenshots
 
 ## Dataset Structure
 
@@ -74,18 +72,15 @@ The dataset is split into training and validation sets with a **90/10 ratio**:
 
 | Split | Percentage | Number of Images |
 | :--- | :--- | :--- |
-| **Train** | 90% | ~4,500 |
-| **Validation** | 10% | ~500 |
-
-### Resolution & Diversity
-The images cover a wide range of viewport widths to simulate real-world usage scenarios, ranging from **375px** (mobile devices) up to **1920px** (desktop monitors).
+| **Train** | 80% | 185 |
+| **Validation** | 20% | 45 |
 
 ## Usage
 
 ```python
 from datasets import load_dataset
 
-dataset = load_dataset("egnch/synthetic-ui")
+dataset = load_dataset("egnch/real-ui")
 
 # Example: View the first training example
 print(dataset["train"][0])
@@ -97,12 +92,12 @@ print(dataset["train"][0])
 
 | Class Label | Description | Count | Distribution (Approx.) | 
  | ----- | ----- | ----- | ----- |
-| **text** | Text content blocks, paragraphs, labels | 29720 | 40% | 
-| **button** | Buttons of various styles | 16563 | 20% | 
-| **header** | Visual headers and highlights | 12047 | 15% | 
-| **image** | Visual content, avatars, banners | 7857 | 15% | 
-| **input** | Input fields, text areas, dropdowns | 4295 | 5% | 
-| **checkbox** | Checkboxes, radio buttons, switches | 2574 | 5% | 
+| **text** | Text content blocks, paragraphs, labels | 2938 | ~50% | 
+| **button** | Buttons of various styles | 955 | ~15% | 
+| **image** | Visual content, avatars, banners | 508 | ~10% | 
+| **header** | Visual headers and highlights | 446 | ~10% | 
+| **input** | Input fields, text areas, dropdowns | 431 | ~10% | 
+| **checkbox** | Checkboxes, radio buttons, switches | 263 | ~5% | 
 
 ### Licensing