reverting gradio

gradio_app.py

@@ -206,7 +206,7 @@ download_models()
 # -----------------------------
 # Step 2: Inference Logic
 # -----------------------------
-def run_epic_inference(video_path, target_pose, mode):
+def run_epic_inference(video_path, num_frames, target_pose, mode):
     temp_input_path = "/app/temp_input.mp4"
     output_dir = "/app/output_anchor"
     video_output_path = f"{output_dir}/masked_videos/output.mp4"
@@ -229,6 +229,7 @@ def run_epic_inference(video_path, target_pose, mode):
         "--camera", "target",
         "--mask",
         "--target_pose", theta, phi, r, x, y,
+        "--video_length", num_frames,
         "--save_name", "output",
         "--mode", mode,
     ]
@@ -254,8 +255,10 @@ def print_output_directory(out_dir):
     return result
 
 def inference(video_path, num_frames, fps, target_pose, mode):
-    logs, video_masked = run_epic_inference(video_path, target_pose, mode)
-    return logs, video_masked
+    logs, video_masked = run_epic_inference(video_path, num_frames, target_pose, mode)
+
+    result_dir = print_output_directory("/app/output_anchor")
+
 
     MODEL_PATH = "/app/pretrained/CogVideoX-5b-I2V"
     ckpt_steps = 500
@@ -265,6 +268,8 @@ def inference(video_path, num_frames, fps, target_pose, mode):
 
     video_root_dir = "/app/output_anchor"
     out_dir = "/app/output"
+    return logs + result_dir, video_masked
+
 
     command = [
         "python", "/app/inference/cli_demo_camera_i2v_pcd.py",