Update README.md with latest visuals

README.md

@@ -1,14 +1,12 @@
 # TensorflowJs Chessboard Prediction from Screenshots in HTML5
 
-Given a screenshot which has an online chessboard in it somewhere, it finds the chessboard and predicts the layout of the pieces on it. Everything runs client-side live using [TensorflowJs](https://js.tensorflow.org/)
+Given a screenshot of a chessboard from lichess.org/chess.com, it tries to find the chessboard and pieces on it, [*Try it yourself*](http://elucidation.github.io/ChessboardFenTensorflowJs/).
 
-<img src="readme_input.png" width=300px> <img src="readme_prediction.png" width=300px>
-
-## [Live Demo](http://elucidation.github.io/ChessboardFenTensorflowJs/)
+![image](https://github.com/Elucidation/ChessboardFenTensorflowJs/assets/434925/1d348bb4-c915-413c-a3e2-cc07c70e7192)
 
 ## How it works
 
-This uses a frozen [Tensorflow Chessbot](https://github.com/Elucidation/tensorflow_chessbot/tree/chessfenbot) model. Unlike that repo this runs completely in javascript using TensorflowJs, all client-side.
+This uses a frozen [Tensorflow Chessbot](https://github.com/Elucidation/tensorflow_chessbot/tree/chessfenbot) model. Unlike that repo this runs completely in javascript using [TensorflowJs](https://js.tensorflow.org/), all client-side. 
 
 ### Board detection
 
@@ -22,18 +20,26 @@ The image is blurred and then the sobel gradients X and Y are used to find stron
 ### ML Prediction
 
 Given 256x256px aligned chessboard image, it runs a TensorflowJs model to predict pieces on it.
-We freeze a model graph and weights from [Tensorflow Chessbot](https://github.com/Elucidation/tensorflow_chessbot/tree/chessfenbot), and load it up in Javascript using [TensorflowJs](https://js.tensorflow.org/), allowing everything to run locally client-side.
-
-<img src="readme_cropped_input.png" width=300px> <img src="readme_prediction.png" width=300px>
 
 The model was trained using 32x32 px grayscale tiles of chessboard pieces. For each tile it independently predicts one of 13 classes, 6 white pieces, 6 black pieces, or an empty tile.
 
+We freeze the model graph and weights from [Tensorflow Chessbot](https://github.com/Elucidation/tensorflow_chessbot/tree/chessfenbot), and load it up in Javascript using TensorflowJs, allowing everything to run without a server.
+
+![image](https://github.com/Elucidation/ChessboardFenTensorflowJs/assets/434925/24e1c90b-1f94-4f60-8dcf-bb7f8065b4b3)
+
+
+
 ## Running locally
 
 A web server of some sort is needed to allow cross-origin sharing when running locally.
 
-For example, one can use `http-server`.
+For example, one can use 
+
+```python -m http.server```
+
+or
 
 ```
 http-server -o --cors -c-1 -a localhost
 ```
+