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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+test.las filter=lfs diff=lfs merge=lfs -text

README.md

@@ -4,5 +4,3 @@ app_file: app.py
 sdk: gradio
 sdk_version: 3.43.1
 ---
-
-This is a technology demonstration of Trimble AI's 3D Point Cloud Segmentation running on Trimble Cloud Core's Pegasus Processing Framework.  The point cloud is uploaded on behalf of the user into Pegasus, then the result is offered as a downloadable link.  

app.py

@@ -8,6 +8,7 @@ import gradio as gr
 username = os.environ.get("CLIENT_ID")
 passwd = os.environ.get("CLIENT_SECRETS")
 
+
 def authorization():
     url = "https://stage.id.trimblecloud.com/oauth/token"
     credential_pair = f"{username}:{passwd}"
@@ -125,27 +126,31 @@ def download_output(auth_token, output_filename):
 
     return download_url
 
+
 def predict(input_file):
     input_filename = "input.las"
     output_filename = "output.las"
     auth_token = authorization()
     file_upload_url = create_file(auth_token, input_filename)
     upload_file(file_upload_url, input_file)
-    execution_id = start_execution(
-        auth_token, input_filename, output_filename
-    )
+    execution_id = start_execution(auth_token, input_filename, output_filename)
     download_url = track_execution(auth_token, execution_id, output_filename)
 
     html_content = f'<a href="{download_url}">Download output file</a>'
 
+    return (
+        "Inference has finished. Click the download button to access the output file",
+        html_content,
+    )
 
-    return "Inference has finished. Click the download button to access the output file", html_content
 
 demo = gr.Interface(
-    title="Point Cloud inference on the Trimble Cloud",
+    title="Point Cloud Segmentation-Trimble Cloud",
     fn=predict,
     inputs=gr.File(file_types=[".las"], file_count="single"),
     outputs=[gr.Textbox(), "html"],
+    examples=["test.las"],
+    description="This is a technology demonstration of Trimble AI's 3D Point Cloud Segmentation running on Trimble Cloud Core's Pegasus Processing Framework. The point cloud is uploaded on behalf of the user into Pegasus, then the result is offered as a downloadable link.",
 )
 
-demo.queue(concurrency_count=512, max_size=512).launch()
+demo.queue(concurrency_count=512, max_size=512).launch()

test.las

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:727bbb3b6a5f4a4a1367992d72a4d0fdb7b6249bb1df965b420505f4f414fb57
+size 132575085