Update README.md

README.md

@@ -10,6 +10,9 @@ pipeline_tag: image-feature-extraction
 
 This is fashion image feature extractor model.
 
+You can find object-detection model -> [https://huggingface.co/yainage90/fashion-object-detection](https://huggingface.co/yainage90/fashion-object-detection)
+You can find details of model in this github repo -> [fashion-visual-search](https://github.com/yainage90/fashion-visual-search)
+
 # 1. Model Architecture
 
 I used [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) for base image encoder model. Just added a 128 size fully connected layer to lower embedding size.
@@ -26,11 +29,10 @@ Initially, anchor - positive - negative pairs were explicitly constructed in a 1
 User posting images from onthelook and kream were crawled and preprocessed. First, raw data of image-product thumbnail combinations from posts were collected. Then, object detection was performed on posting images, and category classification was performed on product thumbnails to pair images of the same category together. For thumbnail category classification, a trained category classifier was used. Finally, about 290,000 anchor-positive image pairs were created for 6 categories: tops, bottoms, outer, shoes, bags, and hats.
 Finally, approximately 290,000 anchor-positive image pairs were created for 6 categories: tops, bottoms, outer, shoes, bags, and hats.
 
+<img src="data_sample.png" width="300" alt="data sample">
 
-You can find object-detection model -> [https://huggingface.co/yainage90/fashion-object-detection](https://huggingface.co/yainage90/fashion-object-detection)
-
-You can find details of model in this github repo -> [fashion-visual-search](https://github.com/yainage90/fashion-visual-search)
 
+# 3. Usage
 
 ```python
 from PIL import Image