update docs

docs/manual/models.md

@@ -1,6 +1,6 @@
 # MiDaS Models
 
-There are variety of different MiDaS models available. To be able to use them with Unity Sentis, the official models were converted to ONNX using [this colab notebook][colab]. You'll find links to the pretrained models in ONNX format below.
+There are variety of different MiDaS models available. To be able to use them with Unity Sentis, the official models were converted to ONNX using [this colab notebook][colab]. You'll find links to the pretrained models in ONNX format below or on the [GitHub Release page][gh_release].
 
 
 ## Overview
@@ -21,7 +21,7 @@ There are variety of different MiDaS models available. To be able to use them wi
 | [dpt_large_384][12]           | 1.27 GB  | 3.0             |
 
 
-## Usage
+## Get The Models
 
 To keep the package size reasonable, only the @Doji.AI.Depth.ModelType.midas_v21_small_256 model is included with the package when downloading from the Asset Store. To use other models you have to downloaded them first.
 
@@ -32,6 +32,8 @@ Otherwise you can always manually download the ONNX models from the links above
 
 ## Which Model To Use
 
+### Overview
+
 You should choose the appropriate model type based on your requirements, considering factors such as accuracy, model size and performance.
 
 The available models usually have a tradeoff between memory & performance and the accuracy/quality of the depth estimation.
@@ -42,7 +44,14 @@ The [official MiDaS documentation][docs_official] does a fairly good job of show
 
 Generally, if you have a hard realtime requirement, e.g. when you want to do depth estimation at runtime or on mobile devices, you may want to use smaller models like midas_v21_small_256 or dpt_swin2_tiny_256. If you need best quality (editor tools) or depth estimation needs to happen just once, you might be able to use models like dpt_swin2_large_384 or dpt_beit_large_384. Keep in mind the larger memory requirements for these model though.
 
+### Examples
+
+The comparison below is only meant to give a rough overview of the capabilities of each model.
+Judging the quality of a depth map from just a 2D image is hard. Consider using the WebcamSample that is included with the package to see how the different models perform when when projecting the estimated depth back into 3D as a point cloud.
+![samples](../images/model_samples.webp)
+
 [colab]: https://github.com/julienkay/com.doji.midas/blob/master/tools/MiDaS_ONNX_Export.ipynb
+[gh_release]: https://github.com/julienkay/com.doji.midas/releases/tag/v1.0.0
 [docs_official]: https://github.com/isl-org/MiDaS
 [1]: https://github.com/julienkay/com.doji.midas/releases/download/v1.0.0/midas_v21_small_256.onnx
 [2]: https://github.com/julienkay/com.doji.midas/releases/download/v1.0.0/midas_v21_384.onnx