adding aspect ratio

gradio_app.py

@@ -30,7 +30,7 @@ def download_models():
             subprocess.check_call(["bash", "download/download_models.sh"])
             print("✅ Models downloaded.")
         except subprocess.CalledProcessError as e:
-            print(f"❌ Model download failed: {e}")
+            print(f"Model download failed: {e}")
     else:
         print("✅ Pretrained models already exist.")
 
@@ -84,9 +84,9 @@ def get_anchor_video(video_path, fps, num_frames, target_pose, mode,
         "--window_size", str(window_size),
         "--overlap", str(overlap),
         "--max_res", str(max_res),
-        # "--sample_size", sample_size if sample_size else "384,672",
+        "--sample_size", sample_size if sample_size else "384,672",
         "--seed", str(seed_input),
-        "--height", str(height),  # Fixed height
+        "--height", str(height),
         "--width", str(width),
         "--target_aspect_ratio", w.strip(), h.strip()
     ]   
@@ -95,7 +95,7 @@ def get_anchor_video(video_path, fps, num_frames, target_pose, mode,
         result = subprocess.run(command, capture_output=True, text=True, check=True)
         logs += result.stdout
     except subprocess.CalledProcessError as e:
-        logs += f"❌ Inference failed:\n{e.stderr}{e.stdout}"
+        logs += f"Inference failed:\n{e.stderr}{e.stdout}"
         return None, logs
 
     return str(video_output_path), logs
@@ -136,7 +136,7 @@ def inference(
         "--controlnet_transformer_num_layers", str(controlnet_transformer_num_layers),
 
     ]
-        # Conditionally append optional flags
+
     if upscale:
         command.extend(["--upscale", "--upscale_factor", str(upscale_factor)])
 
@@ -152,9 +152,6 @@ def inference(
     video_output = f"{out_dir}/00000_{seed}_out.mp4"
     return video_output if os.path.exists(video_output) else None, logs
 
-
-
-
 # -----------------------------
 # UI
 # -----------------------------
@@ -168,11 +165,10 @@ with demo:
             with gr.Row():
                 with gr.Column():
                     with gr.Row():
-                        near_far_estimated = gr.Checkbox(label="Near Far Estimation", value=True) # integrate it with 
+                        near_far_estimated = gr.Checkbox(label="Near Far Estimation", value=True) 
                         pose_input = gr.Textbox(label="Target Pose (θ φ r x y)", placeholder="e.g., 0 30 -0.6 0 0")
                         fps_input = gr.Number(value=24, label="FPS")
-                        aspect_ratio_inputs=gr.Textbox(label="Target Aspect Ratio (e.g., 2,3)"),
-
+                        aspect_ratio_inputs=gr.Textbox(label="Target Aspect Ratio (e.g., 2,3)")
                         num_frames_input = gr.Number(value=49, label="Number of Frames")
                         radius_input = gr.Number(value = 1.0, label="Radius Scale")
                         mode_input = gr.Dropdown(choices=["gradual"], value="gradual", label="Camera Mode")