Update app.py

app.py

@@ -1,101 +1,44 @@
 import os
 import streamlit as st
 import torch
+from diffusers.utils import load_image
 
 try:
     from diffusers import CogVideoXImageToVideoPipeline
     pipeline_available = True
-except ImportError as e:
+except ImportError:
     pipeline_available = False
-    st.error("Failed to import CogVideoXImageToVideoPipeline.")
-    st.write(f"Debug info: {e}")
+    st.error("Failed to import `CogVideoXImageToVideoPipeline`. Please run `pip install diffusers`.")
 
-
-# Streamlit interface
 st.title("Image to Video with Hugging Face")
 st.write("Upload an image and provide a prompt to generate a video.")
 
-import subprocess
-
-subprocess.run(["streamlit", "config", "set", "browser.gatherUsageStats", "false"])
-
-
-
-# Check if the pipeline is available before proceeding
-if not pipeline_available:
-    st.error("The required pipeline is unavailable. Please ensure you have the correct version of the diffusers library.")
-else:
-    # File uploader for the input image
+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.")
 
-    # Cache migration step
-    st.write("Migrating the cache for model files...")
-    try:
-        from transformers.utils import move_cache
-        move_cache()
-        st.write("Cache migration completed successfully.")
-    except Exception as e:
-        st.error(f"Cache migration failed: {e}")
-        st.write("Proceeding without cache migration...")
-
     if uploaded_file and prompt:
         try:
-            st.write(f"Uploaded file: {uploaded_file.name}")
-            st.write(f"Prompt: {prompt}")
-
             # Save uploaded file
-            st.write("Saving uploaded image...")
-            with open("uploaded_image.jpg", "wb") as f:
+            import uuid
+            file_name = f"{uuid.uuid4()}_uploaded_image.jpg"
+            with open(file_name, "wb") as f:
                 f.write(uploaded_file.read())
             st.write("Uploaded image saved successfully.")
 
             # Load the image
-            from diffusers.utils import load_image
-            st.write("Loading image...")
-            image = load_image("uploaded_image.jpg")
-            st.write("Image loaded successfully.")
+            image = load_image(file_name)
 
-            # Initialize the pipeline
-            st.write("Initializing the pipeline...")
+            # Initialize pipeline
+            device = "cuda" if torch.cuda.is_available() else "cpu"
             pipe = CogVideoXImageToVideoPipeline.from_pretrained(
                 "THUDM/CogVideoX1.5-5B-I2V",
                 torch_dtype=torch.bfloat16,
                 cache_dir="./huggingface_cache",
-                force_download=True  # Ensure fresh download
             )
-            st.write("Pipeline initialized successfully.")
-
-            # Enable optimizations
             pipe.enable_sequential_cpu_offload()
             pipe.vae.enable_tiling()
             pipe.vae.enable_slicing()
 
             # Generate video
-            st.write("Generating video... This may take a while.")
-            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="cuda").manual_seed(42),
-            ).frames[0]
-            st.write("Video generated successfully.")
-
-            # Export video
-            st.write("Exporting video...")
-            from diffusers.utils import export_to_video
-            video_path = "output.mp4"
-            export_to_video(video_frames, video_path, fps=8)
-            st.write("Video exported successfully.")
-
-            # Display video
-            st.video(video_path)
-
-        except Exception as e:
-            st.error(f"An error occurred: {e}")
-            st.write(f"Debug info: {e}")
-    else:
-        st.write("Please upload an image and provide a prompt to get started.")
+            with st.spinner("Generating video