Update app.py

app.py

@@ -8,20 +8,25 @@ import sys
 import traceback
 from huggingface_hub import hf_hub_download
 
+# For live system monitoring
+import psutil
+import GPUtil
+
 # =========================================
 # 1. Define Hugging Face dataset + weights
 # =========================================
 
-HF_DATASET_REPO = "roll-ai/FloVD-weights"  # your dataset repo on HF
+HF_DATASET_REPO = "roll-ai/FloVD-weights"
 
 WEIGHT_FILES = {
-    "ckpt/FVSM/FloVD_FVSM_Controlnet.pt": "FVSM/FloVD_FVSM_Controlet.pt",
+    "ckpt/FVSM/FloVD_FVSM_Controlnet.pt": "FVSM/FloVD_FVSM_Controlnet.pt",
     "ckpt/OMSM/selected_blocks.safetensors": "OMSM/selected_blocks.safetensors",
     "ckpt/OMSM/pytorch_lora_weights.safetensors": "OMSM/pytorch_lora_weights.safetensors",
     "ckpt/others/depth_anything_v2_metric_hypersim_vitb.pth": "others/depth_anything_v2_metric_hypersim_vitb.pth"
 }
-print("")
-print("Downloading model...", flush=True)
+
+print("\nDownloading model...", flush=True)
+
 def download_weights():
     print("🔄 Downloading model weights via huggingface_hub...")
     for hf_path, local_rel_path in WEIGHT_FILES.items():
@@ -49,13 +54,14 @@ def print_ckpt_structure(base_path="ckpt"):
         for f in files:
             print(f"{sub_indent}📄 {f}", flush=True)
 
-# Call it
 print_ckpt_structure()
+
 # =========================================
-# 2. Import the FloVD generation pipeline
+# 2. Import FloVD generation pipeline
 # =========================================
 
 from inference.flovd_demo import generate_video
+
 def run_inference(prompt, image, pose_type, speed, use_flow_integration, cam_pose_name):
     log_buffer = io.StringIO()
     sys_stdout = sys.stdout
@@ -67,7 +73,6 @@ def run_inference(prompt, image, pose_type, speed, use_flow_integration, cam_pos
         os.makedirs("input_images", exist_ok=True)
         image_path = "input_images/input_image.png"
 
-        # ✅ Convert NumPy to PIL if necessary
         if not isinstance(image, Image.Image):
             image = Image.fromarray(image.astype("uint8"))
 
@@ -110,11 +115,12 @@ def run_inference(prompt, image, pose_type, speed, use_flow_integration, cam_pos
 
     return (video_path if video_path and os.path.exists(video_path) else None), logs
 
+
 # =========================================
-# 3. Gradio App Interface
+# 3. Define FloVD Gradio Interface
 # =========================================
 
-demo = gr.Interface(
+video_interface = gr.Interface(
     fn=run_inference,
     inputs=[
         gr.Textbox(label="Prompt", value="A girl riding a bicycle through a park."),
@@ -137,8 +143,48 @@ demo = gr.Interface(
     description="Upload an image and prompt to generate motion-controlled video using FloVD and CogVideoX."
 )
 
-# -----------------------------
-# Launch the App
-# -----------------------------
+# =========================================
+# 4. Live System Monitor
+# =========================================
+
+def get_system_stats():
+    cpu = psutil.cpu_percent()
+    mem = psutil.virtual_memory()
+    disk = psutil.disk_usage('/')
+    try:
+        gpus = GPUtil.getGPUs()
+        gpu_info = "\n".join([
+            f"GPU {i}: {gpu.name}, {gpu.memoryUsed}MB / {gpu.memoryTotal}MB, Util: {gpu.load * 100:.1f}%"
+            for i, gpu in enumerate(gpus)
+        ]) if gpus else "No GPU detected"
+    except Exception as e:
+        gpu_info = f"GPU info error: {e}"
+
+    return (
+        f"🧠 CPU Usage: {cpu}%\n"
+        f"💾 RAM: {mem.used / 1e9:.2f} GB / {mem.total / 1e9:.2f} GB ({mem.percent}%)\n"
+        f"🗄️ Disk: {disk.used / 1e9:.2f} GB / {disk.total / 1e9:.2f} GB ({disk.percent}%)\n"
+        f"🎮 {gpu_info}"
+    )
+
+with gr.Blocks() as monitor_tab:
+    gr.Markdown("## 📊 Live System Resource Monitor")
+    stats_box = gr.Textbox(label="Live Stats", lines=10, interactive=False)
+    gr.Live(stats_box.update, fn=get_system_stats, every=2.0)
+
+# =========================================
+# 5. Combine Tabs: FloVD + Monitor
+# =========================================
+
+with gr.Blocks() as app:
+    with gr.Tab("🎥 Video Generator"):
+        video_interface.render()
+    with gr.Tab("📊 System Monitor"):
+        monitor_tab.render()
+
+# =========================================
+# 6. Launch App
+# =========================================
+
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0",debug=True, show_error=True, server_port=7860)
+    app.launch(server_name="0.0.0.0", server_port=7860, debug=True, show_error=True)