Upload folder using huggingface_hub

README.md

@@ -1,12 +1,6 @@
 ---
-title: Point Cloud Segmentation-Trimble Cloud
-emoji: 📊
-colorFrom: pink
-colorTo: pink
-sdk: gradio
-sdk_version: 3.47.1
+title: Point_Cloud_Segmentation-Trimble_Cloud
 app_file: app.py
-pinned: false
+sdk: gradio
+sdk_version: 3.43.1
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,151 @@
+import os
+import json
+import time
+import base64
+import requests
+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}"
+
+    payload = "grant_type=client_credentials&scope=DLPointCloudSegmentation"
+    headers = {
+        "Content-Type": "application/x-www-form-urlencoded",
+        "Authorization": f"Basic {base64.b64encode(credential_pair.encode('utf-8')).decode('utf-8')}",
+    }
+
+    response = requests.request("POST", url, headers=headers, data=payload)
+
+    response.raise_for_status()
+    print("Succesfully authenticated")
+    auth_token = json.loads(response.text)["access_token"]
+
+    return auth_token
+
+
+def create_file(auth_token, input_filename):
+    url = "https://cloud.stage.api.trimblecloud.com/dataocean/api/3.0/api/files"
+
+    payload = json.dumps({"file": {"path": input_filename, "regions": ["us1"]}})
+    headers = {
+        "Authorization": f"Bearer {auth_token}",
+        "Content-Type": "application/json",
+    }
+
+    response = requests.request("POST", url, headers=headers, data=payload)
+
+    response.raise_for_status()
+    print("File created successfully")
+    file_upload_url = json.loads(response.text)["file"]["upload"]["url"]
+    return file_upload_url
+
+
+def upload_file(url, file):
+    with open(file.name, "rb") as lasFile:
+        payload = lasFile.read()
+
+    headers = {"Content-Type": "application/octet-stream"}
+
+    response = requests.request("PUT", url, headers=headers, data=payload)
+
+    response.raise_for_status()
+    print("Upload was successful")
+
+
+def start_execution(auth_token, input_filename, output_filename="output.las"):
+    url = "https://cloud.stage.api.trimblecloud.com/Processing/api/1/api/executions"
+
+    payload = json.dumps(
+        {
+            "execution": {
+                "procedure_id": "a7c4f9c3-b21a-4c9c-b4df-3dc6ba8934d9",
+                "region": "aws-us1",
+                "parameters": {
+                    "source_path": input_filename,
+                    "regions": ["us1"],
+                    "output_path": output_filename,
+                },
+            }
+        }
+    )
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {auth_token}",
+    }
+
+    response = requests.request("POST", url, headers=headers, data=payload)
+
+    response.raise_for_status()
+    print("Execution has started")
+
+    execution_id = json.loads(response.text)["execution"]["id"]
+
+    return execution_id
+
+
+def track_execution(auth_token, execution_id, output_filename):
+    url = "https://cloud.stage.api.trimblecloud.com/Processing/api/1/api/executions"
+
+    payload = {}
+    headers = {
+        "Authorization": f"Bearer {auth_token}",
+    }
+
+    response = requests.request("GET", url, headers=headers, data=payload)
+
+    status = json.loads(response.text)["items"][0]["execution_status"]
+
+    while status != "FINISHED":
+        response = requests.request("GET", url, headers=headers, data=payload)
+        status = json.loads(response.text)["items"][0]["execution_status"]
+        time.sleep(1)
+
+    return download_output(auth_token, output_filename)
+
+
+def download_output(auth_token, output_filename):
+    url = f"https://cloud.stage.api.trimblecloud.com/dataocean/api/3.0/api/files?path={output_filename}"
+
+    payload = ""
+    headers = {
+        "Authorization": f"Bearer {auth_token}",
+        "Content-Type": "application/json",
+    }
+
+    response = requests.request("GET", url, headers=headers, data=payload)
+
+    response.raise_for_status()
+    print("File downloading")
+    response = json.loads(response.text)
+    download_url = response["file"]["download"]["url"]
+
+    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
+    )
+    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
+
+demo = gr.Interface(
+    title="Point Cloud inference on the Trimble Cloud",
+    fn=predict,
+    inputs=gr.File(file_types=[".las"], file_count="single"),
+    outputs=[gr.Textbox(), "html"],
+)
+
+demo.queue(default_enabled=False).launch()

requirements.txt

@@ -0,0 +1 @@
+requests