main

app.py

@@ -0,0 +1,155 @@
+import pathlib
+import shlex
+import subprocess
+import gradio as gr
+import PIL.Image
+import time
+import os
+import requests
+import json
+import ipywidgets as widgets
+from IPython.display import display
+from google.colab import files
+from IPython.display import display, HTML, Javascript
+from google.colab import output
+import gradio as gr
+
+# Define the base URL, the API key and Paths
+base_url = "https://hyperhuman.deemos.com/api/v2"
+api_key = os.getenv('API')
+image_path = "/content/sample_data/wooden_chair.jpg"
+
+result_path = "/content/"
+
+
+# Define the headers for the requests
+headers = {
+    "Authorization": f"Bearer {api_key}",
+    "Content-Type": "application/json"
+}
+
+def submit_task(image_path: str):
+    url = f"{base_url}/rodin"
+    #image_path = "/content/sample_data/wooden_chair.jpg"
+    # Get the uploaded file
+     #if uploader.value:
+       #uploaded_file = next(iter(uploader.value.values()))
+       #if 'name' not in uploaded_file:
+         #print("Error: 'name' not found in task response")
+         #return
+
+
+       #image_path = uploaded_file['metadata']['name']
+
+          # Save the uploaded file to disk
+   # with open(image_path, 'wb') as f:
+   #      f.write(uploaded_file['content'])
+    #else:
+     # print("No file uploaded. Please upload an image.")
+
+    # Read the image file
+    with open(image_path, 'rb') as image_file:
+        image_data = image_file.read()
+
+    # Prepare the multipart form data
+    files = {
+        'images': (os.path.basename(image_path), image_data, 'image/jpeg')
+    }
+
+    # Set the tier to Rodin Regular
+    data = {
+        'tier': 'Regular'
+    }
+
+    # Prepare the headers.
+    headers = {
+        'Authorization': f'Bearer {api_key}',
+    }
+
+    # Note that we are not sending the data as JSON, but as form data.
+    # This is because we are sending a file as well.
+    response = requests.post(url, files=files, data=data, headers=headers)
+    print(response)
+    return response.json()
+
+# Function to check the status of a task
+def check_status(subscription_key):
+    url = f"{base_url}/status"
+    data = {
+        "subscription_key": subscription_key
+    }
+    response = requests.post(url, headers=headers, json=data)
+    return response.json()
+
+# Function to download the results of a task
+def download_results(task_uuid):
+    url = f"{base_url}/download"
+    data = {
+        "task_uuid": task_uuid
+    }
+    response = requests.post(url, headers=headers, json=data)
+    return response.json()
+
+
+
+def submit_task2(image_path: str):
+  # Submit the task and get the task UUID
+  task_response = submit_task(image_path)
+  if 'uuid' not in task_response:
+      print("Error: 'uuid' not found in task response")
+      return
+
+  task_uuid = task_response['uuid']
+  subscription_key = task_response['jobs']['subscription_key']
+
+  # Poll the status endpoint every 5 seconds until the task is done
+  status = []
+  while len(status) == 0 or not all(s['status'] in ['Done', 'Failed'] for s in status):
+      time.sleep(5)
+      status_response = check_status(subscription_key)
+      status = status_response['jobs']
+      for s in status:
+          print(f"job {s['uuid']}: {s['status']}")
+
+  # Download the results once the task is done
+  download_response = download_results(task_uuid)
+  download_items = download_response['list']
+
+  # Print the download URLs and download them locally.
+  for item in download_items:
+      print(f"File Name: {item['name']}, URL: {item['url']}")
+      dest_fname = os.path.join(result_path, item['name'])
+      os.makedirs(os.path.dirname(dest_fname), exist_ok=True)
+      with open(dest_fname, 'wb') as f:
+          response = requests.get(item['url'])
+          f.write(response.content)
+          print(f"Downloaded {dest_fname}")
+          return dest_fname
+
+
+
+
+
+
+def run(image_path: str) -> str:
+
+   return submit_task2(image_path)
+
+with gr.Blocks() as demo:
+   with gr.Group():
+        image = gr.Image(label="Input image", show_label=False, type="filepath")
+        run_button = gr.Button("Run")
+        result = gr.Model3D(label="Result", show_label=False)
+
+        run_button.click(
+            fn=run,
+            inputs=[
+                image
+            ],
+            outputs=result,
+            api_name="image-to-3d",
+            concurrency_id="gpu",
+            concurrency_limit=1,
+        )
+
+demo.launch(auth=("user", os.getenv('PASS')),share=True,debug=True)