Create app.py

app.py

@@ -0,0 +1,44 @@
+import os
+import gradio as gr
+import subprocess
+from lib.config import args
+
+def process_video(video_path, task):
+    """
+    Function to process the input video and run the NeuralBody pipeline.
+    """
+    # Save uploaded video locally
+    input_video = "input_video.mp4"
+    os.system(f"cp {video_path} {input_video}")
+
+    # Map tasks to functions in run.py
+    task_map = {
+        "Dataset Processing": "dataset",
+        "Network Inference": "network",
+        "Evaluation": "evaluate",
+        "Visualization": "visualize",
+    }
+
+    if task not in task_map:
+        return "Invalid task selected!"
+
+    # Run corresponding function in run.py
+    args.type = task_map[task]  # Set the correct function call in run.py
+    subprocess.run(["python", "run.py"], check=True)
+
+    return f"Task '{task}' completed! Check the output directory."
+
+# Gradio UI
+iface = gr.Interface(
+    fn=process_video,
+    inputs=[
+        gr.Video(label="Upload Video"),
+        gr.Radio(["Dataset Processing", "Network Inference", "Evaluation", "Visualization"], label="Select Task"),
+    ],
+    outputs="text",
+    title="NeuralBody: Video-Based 3D Reconstruction",
+    description="Upload a video and choose a task to perform using the NeuralBody pipeline."
+)
+
+if __name__ == "__main__":
+    iface.launch()