update readme

Author: younghyopark

README.md

@@ -2,7 +2,7 @@ VisionProTeleop
 ===========
 
 
-> **🎉 UPDATE: Now supporting Low-Latency Video Streaming!** You can now stream back your robot's camera feed back to Vision Pro via webRTC protocol, alongside the original hand tracking data stream. No complicated network setting required. Download the app, `pip install avp_stream`, and you're done!
+> **🎉 UPDATE: Now supporting Low-Latency Video Streaming!** You can now stream back your robot's camera feed back to Vision Pro via webRTC protocol, alongside the original hand tracking data stream. No complicated network setting required.  Update the app, `pip install --upgrade avp_stream`, and you're done!
 
 
 <div align="center">
@@ -40,26 +40,30 @@ If you use this repository in your work, consider citing:
 
 ### Step 1. Install the app on Vision Pro 
 
-![](assets/visionpro_main.png)
 
-This app is now officially on VisionOS App Store! You can search for **[Tracking Streamer](https://apps.apple.com/us/app/tracking-streamer/id6478969032)** from the App Store and install the app. 
+This app is officially on VisionOS App Store! You can search for **[Tracking Streamer](https://apps.apple.com/us/app/tracking-streamer/id6478969032)** from the App Store and install the app. 
 
-If you want to play around with the app, you can build/install the app yourself too. To learn how to do that, take a look at this [documentation](/how_to_install.md). This requires (a) Apple Developer Account, (b) Vision Pro Developer Strap, and (c) a Mac with Xcode installed. 
+
+> If you want to play around with the app, you can build/install the app yourself too. To learn how to do that, take a look at this [documentation](/how_to_install.md). This requires (a) Apple Developer Account, (b) Vision Pro Developer Strap, and (c) a Mac with Xcode installed. 
 
 
 ### Step 2. Run the app on Vision Pro 
 
-After installation, click on the app on Vision Pro and click `Start`. That's it!  Vision Pro is now streaming the tracking data over your wifi network. 
+After installation, click and open the app on Vision Pro. It should show something like this. Click **START with Video Streaming** if you want to stream back videos from your robot over webRTC. Otherwise, click the left button. That's it!  
+
+Vision Pro is now streaming the tracking data over your wifi network via gRPC, and ready to receive video stream via webRTC. 
+
+
+![](assets/app-screenshot.png)
 
-**Tip**  Remember the IP address before you click start; you need to specify this IP address to subscribe to the data. Once you click start, the app will immediately enter into pass-through mode. Click on the digital crown to stop streaming.  
 
 
 ### Step 3. Receive the hand tracking data from anywhere
 
 The following python package allows you to receive the data stream from any device that's connected to the same WiFi network. First, install the package: 
 
 ```
-pip install avp_stream
+pip install --upgrade avp_stream 
 ```
 
 Then, add this code snippet to any of your projects you were developing: 
@@ -74,9 +78,9 @@ while True:
     print(r['head'], r['right_wrist'], r['right_fingers'])
 ```
 
-### Step 4. [🎉NEW FEATURE] Stream video feeds back to Vision Pro! 
+### Step 4. [🎉V2 Update🎉] Stream video feeds back to Vision Pro! 
 
-Streaming your robot's video feed back to Vision Pro requires one additional line: `start_video_streaming`. 
+Streaming your robot's video feed back to Vision Pro requires one additional line: `start_video_streaming`. This feature is only supported on the latest version of the VisionOS app, and python package. Make sure you upgrade both python library / visionOS app. 
 
 ```python
 from avp_stream import VisionProStreamer
@@ -86,7 +90,7 @@ s = VisionProStreamer(ip = avp_ip)
 # you can simply start a video stream 
 # by defining which video device you want to use
 s.start_video_streaming(device="/dev/video0", format="v4l2", \
-                        size="640x480", fps=30)
+                        size="640x480", fps=30, stereo=False)
 
 while True:
     r = s.latest
@@ -103,7 +107,16 @@ You can also:
   s.start_video_streaming(device="/dev/video0", format="v4l2", \
                         size="640x480", fps=30)
   ```
-- work without a physical camera and send over synthetically generated frames (i.e., rendered from simulation)
+
+- send over as a stereo camera feed   (assumes side-by-side concatenated image)
+
+  ```python
+  s = VisionProStreamer(ip = avp_ip)
+  s.start_video_streaming(device="/dev/video0", format="v4l2", \
+                        size="640x480", fps=30, stereo=True)
+  ```
+
+- work without a physical camera and send over synthetically generated frames (i.e., simulation renderings, or purely synthetic images)
   ```python
   s = VisionProStreamer(ip = avp_ip)
   # define your own image generating function, and register
@@ -114,7 +127,14 @@ You can also:
 
 which is explained in detail in [examples](examples) folder. 
 
-> **NOTE**:  Finding the right combination of `device`, `format`, `size`, and `fps` can sometime be tricky, since camera models only support certain combination. Also, depending on your operation system and how you plugged the camera, the `device` might have been mounted on a different directory. 
+**Note:** Finding the right combination of `device`, `format`, `size`, and `fps` can sometime be tricky, since camera models only support certain combination. Also, depending on your operation system and how you plugged the camera, the camera might have been mounted on a different directory. To find the right combination of these parameters, you can use the following script: 
+
+```bash
+python test_video_devices.py --live
+```
+When it's the right combination, it'll show up a live feed of the selected camera. 
+
+
 
 
 
@@ -168,15 +188,19 @@ Refer to the image above to see what order the joints are represented in each ha
 
 ## App Features
 
-### Status Window 
+### Status / Control Window 
 
+Status window is a good way to monitor the networking status, and control the life cycle of the app. It is shown in full view when you first start the app, but automatically gets minimized when video frame comes in. You can also minimize / maximize as you need. 
+
+![](assets/status-window.png)
 
 
 ### Modifying the Video Viewport
 
+You can also modify the video viewport -- how far they are from your eyes. 
+
 
 
-### Temporarily Hiding Video Stream  
 
 
 ## Acknowledgements 

assets/app-screenshot.png

@@ -13,7 +13,7 @@
 import time
 
 def main():
-    VISION_PRO_IP = "10.29.249.251" 
+    VISION_PRO_IP = "192.168.86.21" 
 
     streamer = VisionProStreamer(ip=VISION_PRO_IP, record=True)
 

assets/status-window.png

@@ -12,7 +12,7 @@
 import time
 
 # Replace with your Vision Pro's IP address
-VISION_PRO_IP = '10.29.249.251'
+VISION_PRO_IP = '192.168.86.21'
 
 
 # Example 1: Animated gradient