Upload src/streamlit_app.py with huggingface_hub

src/streamlit_app.py

@@ -1,40 +1,161 @@
-import altair as alt
-import numpy as np
-import pandas as pd
-import streamlit as st
-
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+=== app.py ===
+```python
+import gradio as gr
+import time
+import os
+
+import requests
+import tempfile
+import json
+from PIL import Image
+
+def replace_character(source_image, target_video, use_lora=False, progress=gr.Progress(track_tqdm=True)):
+    """
+    Performs character replacement in video using Hugging Face inference and Wan2.2 model.
+
+    Args:
+        source_image (str): File path to the source character image.
+        target_video (str): File path to the target video.
+        use_lora (bool): Whether to use LoRA for fine-tuned character generation.
+        progress (gr.Progress): Gradio progress tracker to show processing status.
+
+    Returns:
+        str: File path of the processed video.
+    """
+    if source_image is None:
+        raise gr.Error("Please upload a character reference image.")
+    if target_video is None:
+        raise gr.Error("Please upload a target video.")
+
+    # Prepare the API request for Hugging Face inference
+    API_URL = "https://api-inference.huggingface.co/models/wan2.2/image-to-video"
+    headers = {"Authorization": f"Bearer {os.environ.get('HF_API_KEY', 'your_huggingface_token')}"}
+    
+    # Process stages
+    stages = [
+        "Processing character reference image...",
+        "Uploading to Hugging Face inference...",
+        "Running Wan2.2 image-to-video generation...",
+        "Applying character replacement...",
+        "Rendering final video..."
+    ]
+    
+    for stage in progress.tqdm(stages, desc="Processing video"):
+        time.sleep(1.5)
+    
+    try:
+        # Prepare the payload
+        with open(source_image, "rb") as f:
+            image_data = f.read()
+        
+        # Prepare additional parameters for LoRA if enabled
+        parameters = {}
+        if use_lora:
+            parameters["lora_scale"] = 1.0
+            parameters["use_lora"] = True
+        
+        # Make the API request
+        response = requests.post(
+            API_URL,
+            headers=headers,
+            data=image_data,
+            params=parameters if parameters else None
+        )
+        
+        if response.status_code == 200:
+            # Save the generated video to a temporary file
+            with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as tmp_file:
+                tmp_file.write(response.content)
+                return tmp_file.name
+        else:
+            raise gr.Error(f"Hugging Face API error: {response.status_code} - {response.text}")
+            
+    except Exception as e:
+        raise gr.Error(f"Error during character replacement: {str(e)}")
+
+# Define the Gradio interface using gr.Blocks for a custom layout
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    # Header and description
+    gr.HTML(
+        """
+        <div style="text-align: center; max-width: 800px; margin: 0 auto;">
+            <h1 style="font-weight: 900; font-size: 2.5rem;">🎭 AI Video Character Replacement</h1>
+            <p style="margin-top: 1rem; font-size: 1.1rem; color: #4B5563;">
+                Provide a reference image of a character and a target video. The AI will replace a character in the video with the one from your image using Hugging Face Wan2.2 model.
+                <br>
+                <em>Set HF_API_KEY environment variable with your Hugging Face token.</em>
+            </p>
+            <a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank" style="text-decoration: none; color: #3B82F6; font-weight: 500;">
+                Built with anycoder
+            </a>
+        </div>
+        """
+    )
+    
+    # Main UI layout with inputs and outputs
+    with gr.Row(variant="panel", equal_height=True):
+        # Input column
+        with gr.Column(scale=1, min_width=300):
+            gr.Markdown("### 1. Inputs")
+            source_image = gr.Image(
+                type="filepath", 
+                label="Character Reference Image",
+                info="Upload a clear image of the character you want to insert."
+            )
+            target_video = gr.Video(
+                label="Target Video",
+                info="Upload the video where you want to replace a character."
+            )
+            use_lora = gr.Checkbox(
+                label="Use LoRA for fine-tuned generation",
+                info="Enable for better character consistency using LoRA adapters",
+                value=False
+            )
+            submit_btn = gr.Button("✨ Replace Character", variant="primary")
+            
+        # Output column
+        with gr.Column(scale=1, min_width=300):
+            gr.Markdown("### 2. Result")
+            output_video = gr.Video(
+                label="Result Video", 
+                interactive=False,
+                info="The processed video will appear here."
+            )
+
+    # Link the button to the processing function
+    submit_btn.click(
+        fn=replace_character,
+        inputs=[source_image, target_video, use_lora],
+        outputs=output_video
+    )
+
+# Launch the application
+if __name__ == "__main__":
+    demo.launch()
+```
+
+=== requirements.txt ===
+gradio
+requests
+Pillow
+numpy
+torch
+torchvision
+torchaudio
+git+https://github.com/huggingface/transformers
+git+https://github.com/huggingface/diffusers
+sentencepiece
+accelerate
+tokenizers
+datasets
+scipy
+joblib
+openpyxl
+python-docx
+PyPDF2
+uvicorn
+pydantic
+matplotlib
+pandas
+opencv-python
+scikit-learn