Update app.py

app.py

@@ -36,32 +36,39 @@ import os
 from inference.flovd_demo import generate_video
 
 def run_inference(prompt, image, pose_type, speed, use_flow_integration, cam_pose_name):
-    os.makedirs("input_images", exist_ok=True)
-    image_path = "input_images/input_image.png"
-    image.save(image_path)
+    try:
+        os.makedirs("input_images", exist_ok=True)
+        image_path = "input_images/input_image.png"
+        image.save(image_path)
 
-    generate_video(
-        prompt=prompt,
-        image_path=image_path,
-        fvsm_path="./ckpt/FVSM/FloVD_FVSM_Controlnet.pt",  # Expected to be downloaded from HF dataset
-        omsm_path="./ckpt/OMSM",  # Expected to be downloaded from HF dataset
-        output_path="./outputs",
-        num_frames=49,
-        fps=16,
-        width=None,
-        height=None,
-        seed=42,
-        guidance_scale=6.0,
-        dtype=torch.float16,
-        controlnet_guidance_end=0.4,
-        use_dynamic_cfg=False,
-        pose_type=pose_type,
-        speed=float(speed),
-        use_flow_integration=use_flow_integration,
-        cam_pose_name=cam_pose_name,
-        depth_ckpt_path="./ckpt/others/depth_anything_v2_metric_hypersim_vitb.pth"
-    )
-    return f"./outputs/generated_videos/{prompt[:30].strip().replace(' ', '_')}_{cam_pose_name or 'default'}.mp4"
+        generate_video(
+            prompt=prompt,
+            image_path=image_path,
+            fvsm_path="./ckpt/FVSM/FloVD_FVSM_Controlnet.pt",
+            omsm_path="./ckpt/OMSM",
+            output_path="./outputs",
+            num_frames=49,
+            fps=16,
+            width=None,
+            height=None,
+            seed=42,
+            guidance_scale=6.0,
+            dtype=torch.float16,
+            controlnet_guidance_end=0.4,
+            use_dynamic_cfg=False,
+            pose_type=pose_type,
+            speed=float(speed),
+            use_flow_integration=use_flow_integration,
+            cam_pose_name=cam_pose_name,
+            depth_ckpt_path="./ckpt/others/depth_anything_v2_metric_hypersim_vitb.pth"
+        )
+        return f"./outputs/generated_videos/{prompt[:30].strip().replace(' ', '_')}_{cam_pose_name or 'default'}.mp4"
+
+    except Exception as e:
+        print("🔥 Inference failed:")
+        import traceback
+        traceback.print_exc()
+        return f"⚠️ Error during inference: {e}"
 
 with gr.Blocks() as demo:
     gr.Markdown("## 🎥 FloVD: Optical Flow + CogVideoX Video Generation")