diff --git a/README.md b/README.md
index b639ff7..4606d94 100644
--- a/README.md
+++ b/README.md
@@ -55,6 +55,20 @@ You can also use the Gradio to run the script with an interface. To do so, run t
 python app.py
 ```
 
+## Google Colab
+
+Google Colab users can using it by executing the following command and accessing the generated Gradio Public URL.  
+(Probably, I think this is currently only available in the Colab Pro.)
+
+```bash
+%cd /content
+!git clone https://github.com/Flode-Labs/vid2densepose.git
+%cd /content/vid2densepose
+!pip install -r requirements.txt
+!git clone https://github.com/facebookresearch/detectron2.git
+!python app.py  --share
+```
+
 ## Integration with MagicAnimate
 
 For integration with MagicAnimate:
diff --git a/app.py b/app.py
index ec144e7..f053ab0 100644
--- a/app.py
+++ b/app.py
@@ -9,6 +9,7 @@
 from densepose.vis.densepose_results import DensePoseResultsFineSegmentationVisualizer as Visualizer
 import tempfile
 import shutil
+import argparse
 
 # Function to process video
 def process_video(input_video_path):
@@ -46,7 +47,7 @@ def process_video(input_video_path):
         # Visualizer outputs black for background, but we want the 0 value of
         # the colormap, so we initialize the array with that value
         arr = cv2.applyColorMap(np.zeros((height, width), dtype=np.uint8), cmap)
-        out_frame = Visualizer(alpha=1, cmap=cmap).visualize(arr, results)        
+        out_frame = Visualizer(alpha=1, cmap=cmap).visualize(arr, results)
         out.write(out_frame)
 
     # Release resources
@@ -64,5 +65,9 @@ def process_video(input_video_path):
     title="Video 2 DensePose"
 )
 
+parser = argparse.ArgumentParser(description='Convert your videos to densepose and use it on MagicAnimate')
+parser.add_argument('--share', action='store_true', default=False, help='Share the app on Gradio')
+args = parser.parse_args()
+
 # Run the app
-iface.launch()
+iface.launch(share=args.share)