Create app.py

app.py

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+import gradio as gr
+import subprocess
+import os
+import gdown
+
+# Ensure 'checkpoint' directory exists
+os.makedirs("checkpoint", exist_ok=True)
+
+# Function to download the model weights from a Google Drive folder
+def download_weights_from_folder(google_drive_folder_link):
+    # Extract the folder ID from the Google Drive link
+    folder_id = google_drive_folder_link.split('/')[-1]
+    output_folder = "checkpoint"  # Directory to save the downloaded files
+
+    # Download all files in the Google Drive folder
+    gdown_url = f"https://drive.google.com/drive/folders/{folder_id}"
+    try:
+        gdown.download_folder(gdown_url, quiet=False, output=output_folder)
+        
+        # Check if the model file exists and rename if necessary
+        downloaded_model_path = os.path.join(output_folder, "model_state-415001.th")
+        if os.path.exists(downloaded_model_path):
+            return f"Downloaded model weights to {downloaded_model_path}"
+        else:
+            return "Model file 'model_state-415001.th' not found in the folder."
+    except Exception as e:
+        return f"Failed to download weights: {e}"
+
+download_weights("https://drive.google.com/drive/folders/1Bq0n-w1VT5l99CoaVg02hFpqE5eGLo9O")
+
+# Define a function to run your script with selected inputs
+def run_xportrait(
+    model_config, 
+    output_dir, 
+    resume_dir, 
+    seed, 
+    uc_scale, 
+    source_image, 
+    driving_video, 
+    best_frame, 
+    out_frames, 
+    num_mix, 
+    ddim_steps
+):
+    # Construct the command
+    command = [
+        "python3", "core/test_xportrait.py",
+        "--model_config", model_config,
+        "--output_dir", output_dir,
+        "--resume_dir", resume_dir,
+        "--seed", str(seed),
+        "--uc_scale", str(uc_scale),
+        "--source_image", source_image,
+        "--driving_video", driving_video,
+        "--best_frame", str(best_frame),
+        "--out_frames", str(out_frames),
+        "--num_mix", str(num_mix),
+        "--ddim_steps", str(ddim_steps)
+    ]
+    
+    # Run the command
+    try:
+        subprocess.run(command, check=True)
+        return f"Output saved in: {output_dir}"
+    except subprocess.CalledProcessError as e:
+        return f"An error occurred: {e}"
+
+# Set up Gradio interface
+app = gr.Interface(
+    fn=run_xportrait,
+    inputs=[
+        gr.Textbox(value="config/cldm_v15_appearance_pose_local_mm.yaml", label="Model Config Path"),
+        gr.Textbox(value="outputs", label="Output Directory"),
+        gr.Textbox(value="checkpoint/model_state-415001.th", label="Resume Directory"),
+        gr.Number(value=999, label="Seed"),
+        gr.Number(value=5, label="UC Scale"),
+        gr.Image(label="Source Image"),
+        gr.Video(label="Driving Video"),
+        gr.Number(value=36, label="Best Frame"),
+        gr.Number(value=-1, label="Out Frames"),
+        gr.Number(value=4, label="Number of Mix"),
+        gr.Number(value=30, label="DDIM Steps")
+    ],
+    outputs="text",
+    title="XPortrait Model Runner",
+    description="Run XPortrait with customizable parameters."
+)
+
+# Launch the Gradio app
+app.launch()