removed orientation mode

gradio/app.py

@@ -11,7 +11,7 @@ from diffusers.utils import export_to_video
 from inference import load_model, inference_on_image
 
 # -----------------------
-# 1. Load your model here
+# 1. Load model
 # -----------------------
 args = argparse.Namespace()
 args.blur2vid_hf_repo_path = "tedlasai/blur2vid"
@@ -19,8 +19,6 @@ args.pretrained_model_path = "THUDM/CogVideoX-2b"
 args.model_config_path = "training/configs/outsidephotos.yaml"
 args.video_width = 1280
 args.video_height = 720
-# args.video_width = 960
-# args.video_height = 540
 args.seed = None
 
 pipe, model_config = load_model(args)
@@ -29,8 +27,8 @@ OUTPUT_DIR = Path("/tmp/generated_videos")
 OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
 
 
-@spaces.GPU(timeout=300)
-def generate_video_from_image(image: Image.Image, interval_key: str, orientation_mode: str, num_inference_steps: int) -> str:
+@spaces.GPU(timeout=300, duration=200)
+def generate_video_from_image(image: Image.Image, interval_key: str, num_inference_steps: int) -> str:
     """
     Wrapper for Gradio. Takes an image and returns a video path.
     """
@@ -43,19 +41,6 @@ def generate_video_from_image(image: Image.Image, interval_key: str, orientation
     print("Device:", torch.cuda.get_device_name(0))
     print("bf16 supported:", torch.cuda.is_bf16_supported())
 
-    if orientation_mode == "Landscape (1280×720)":
-        print("Chosing resolution 1280×720 (landscape)")
-        args.video_width = 1280
-        args.video_height = 720
-    elif orientation_mode == "Portrait (720×1280)":
-        print("Choosing resolution 720×1280 (portrait)")
-        args.video_height = 1280
-        args.video_width = 720
-    else:
-        print("Unknown orientation mode", orientation_mode, "defaulting to 1280x720")
-        args.video_width = 1280
-        args.video_height = 720
-
     args.num_inference_steps = num_inference_steps
 
     video_id = uuid.uuid4().hex
@@ -84,7 +69,8 @@ with gr.Blocks(css="footer {visibility: hidden}") as demo:
         - 🌐 **Project page:** <https://blur2vid.github.io/>  
         - 💻 **Code:** <https://github.com/tedlasai/blur2vid/>  
 
-        Upload a blurry image and the model will generate a short video containing the recovered motion depending on your selection.
+        Upload a blurry image and the model will generate a short video showing the recovered motion based on your selection.
+        Note: The image will be resized to 1280×720. We recommend uploading landscape-oriented images.
         """
     )
 
@@ -104,20 +90,6 @@ with gr.Blocks(css="footer {visibility: hidden}") as demo:
                     interactive=True,
                 )
 
-            with gr.Row():
-                mode_choice = gr.Radio(
-                    label="Orientation",
-                    choices=["Landscape (1280×720)", "Portrait (720×1280)"],
-                    value="Landscape (1280×720)",
-                    interactive=True,
-                )
-
-            gr.Markdown(
-                "<span style='font-size: 12px; color: gray;'>"
-                "Note: Model was trained on 1280×720 (Landscape). Portrait mode will degrade performance."
-                "</span>"
-            )
-
             num_inference_steps = gr.Slider(
                 label="Number of inference steps",
                 minimum=4,
@@ -139,7 +111,7 @@ with gr.Blocks(css="footer {visibility: hidden}") as demo:
 
     generate_btn.click(
         fn=generate_video_from_image,
-        inputs=[image_in, tense_choice, mode_choice, num_inference_steps],   # ← include tense_choice!
+        inputs=[image_in, tense_choice, num_inference_steps],
         outputs=video_out,
         api_name="predict",
     )