Update app.py

app.py

@@ -1,26 +1,35 @@
 import os
+import uuid
 import streamlit as st
 import torch
 from diffusers.utils import load_image
 
+# Versuch, die Pipeline zu importieren
 try:
     from diffusers import CogVideoXImageToVideoPipeline
     pipeline_available = True
 except ImportError:
     pipeline_available = False
-    st.error("Failed to import `CogVideoXImageToVideoPipeline`. Please run `pip install diffusers`.")
+    st.error(
+        "Failed to import `CogVideoXImageToVideoPipeline`. "
+        "Please run `pip install diffusers`."
+    )
 
 st.title("Image to Video with Hugging Face")
 st.write("Upload an image and provide a prompt to generate a video.")
 
 if pipeline_available:
-    uploaded_file = st.file_uploader("Upload an image (JPG or PNG):", type=["jpg", "jpeg", "png"])
-    prompt = st.text_input("Enter your prompt:", "A little girl is riding a bicycle at high speed. Focused, detailed, realistic.")
+    uploaded_file = st.file_uploader(
+        "Upload an image (JPG or PNG):", type=["jpg", "jpeg", "png"]
+    )
+    prompt = st.text_input(
+        "Enter your prompt:",
+        "A little girl is riding a bicycle at high speed. Focused, detailed, realistic."
+    )
 
     if uploaded_file and prompt:
         try:
             # Save uploaded file
-            import uuid
             file_name = f"{uuid.uuid4()}_uploaded_image.jpg"
             with open(file_name, "wb") as f:
                 f.write(uploaded_file.read())
@@ -40,21 +49,25 @@ if pipeline_available:
             pipe.vae.enable_tiling()
             pipe.vae.enable_slicing()
 
-
             # Generate video
             with st.spinner("Generating video... This may take a while."):
                 try:
-                # Attempt to generate the video
-                video_frames = pipe(
-                    prompt=prompt,
-                    image=image,
-                    num_videos_per_prompt=1,
-                    num_inference_steps=50,
-                    num_frames=81,
-                    guidance_scale=6,
-                    generator=torch.Generator(device=device).manual_seed(42),
-                ).frames[0]
-            except Exception as e:
-                # Handle errors gracefully
-                st.error(f"An error occurred during video generation: {e}")
+                    # Attempt to generate the video
+                    video_frames = pipe(
+                        prompt=prompt,
+                        image=image,
+                        num_videos_per_prompt=1,
+                        num_inference_steps=50,
+                        num_frames=81,
+                        guidance_scale=6,
+                        generator=torch.Generator(device=device).manual_seed(42),
+                    ).frames[0]
+
+                    st.video(video_frames)
+                    st.success("Video generated successfully!")
+
+                except Exception as e:
+                    st.error(f"An error occurred during video generation: {e}")
 
+        except Exception as e:
+            st.error(f"An error occurred while processing the uploaded file: {e}")