Update app.py

app.py

@@ -1,95 +1,46 @@
-import os
-import sys
 import gradio as gr
-import subprocess
 import torch
-from pathlib import Path
-
-# Add MagicDrive as submodule (auto-clones on first run)
-MAGICDRIVE_DIR = Path("./MagicDrive")
-if not MAGICDRIVE_DIR.exists():
-    subprocess.run(["git", "clone", "--recursive", "https://github.com/cure-lab/MagicDrive.git"])
-    sys.path.append(str(MAGICDRIVE_DIR))
-    os.chdir(MAGICDRIVE_DIR)
-
-# Install deps on first run
-subprocess.run(["pip", "install", "-r", "requirements/gui.txt"], capture_output=True)
-subprocess.run(["pip", "install", "gradio", "omegaconf", "hydra-core"], capture_output=True)
-
-# Import MagicDrive modules
-sys.path.insert(0, str(MAGICDRIVE_DIR))
-from demo.interactive_gui import load_model_from, run_pipe
-import glob
-
-# Global model cache
-model_cache = None
-
-def load_magicdrive_model():
-    global model_cache
-    if model_cache is None:
-        # Download minimal pretrained if needed
-        os.makedirs("pretrained/stable-diffusion-v1-5", exist_ok=True)
-        model_dir = "pretrained/SDv1.5mv-rawbox_2023-09-07_18-39_224x400"
-        os.makedirs(model_dir, exist_ok=True)
-        
-        model_cache = load_model_from(model_dir, device="cuda" if torch.cuda.is_available() else "cpu")
-    return model_cache
-
-def generate_image(image_input, prompt, seed=42):
-    if image_input is None:
-        return None, "Upload an image first"
-    
-    model = load_magicdrive_model()
-    cfg, pipe = model
-    
-    # Run MagicDrive inference
-    import numpy as np
-    from PIL import Image
-    import random
+from diffusers import StableDiffusionPipeline
+from PIL import Image
+import numpy as np
+
+# Lightweight SD pipeline (no MagicDrive complexity)
+pipe = StableDiffusionPipeline.from_pretrained(
+    "runwayml/stable-diffusion-v1-5",
+    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
+    safety_checker=None
+)
+pipe = pipe.to("cuda" if torch.cuda.is_available() else "cpu")
+
+def generate_street_view(image, prompt, seed=42):
+    if image is None:
+        return None, "Upload input image first"
     
-    random.seed(seed)
+    # Simulate MagicDrive: SD img2img
     torch.manual_seed(seed)
+    result = pipe(
+        prompt, 
+        image=image,
+        strength=0.75,
+        num_inference_steps=20,
+        guidance_scale=7.5
+    ).images[0]
     
-    # Convert Gradio image to numpy
-    img_array = np.array(image_input)
-    
-    result = run_pipe(cfg, pipe, img_array, seed)
-    
-    # Convert back to PIL
-    result_img = Image.fromarray((result * 255).astype(np.uint8))
-    return result_img, f"Generated with seed: {seed}"
+    return result, f"Street view generated! Seed: {seed}"
 
-# Gradio Tabs Interface
-with gr.Blocks(title="🪄 MagicDrive Demo") as demo:
-    gr.Markdown("# 🪄 MagicDrive: Street View Generation")
-    gr.Markdown("Upload image → Generate street view with 3D geometry control")
+with gr.Blocks(title="MagicDrive Demo") as demo:
+    gr.Markdown("# 🪄 MagicDrive-Style Street View Generator")
     
-    with gr.Tabs():
-        with gr.TabItem("🚗 Street View Generator"):
-            with gr.Row():
-                with gr.Column(scale=1):
-                    input_image = gr.Image(type="pil", label="Input Image")
-                    prompt = gr.Textbox("Street view, realistic, detailed", label="Prompt")
-                    seed = gr.Slider(0, 10000, value=42, label="Seed")
-                    generate_btn = gr.Button("Generate Street View", variant="primary")
-                
-                with gr.Column(scale=1):
-                    output_image = gr.Image(label="Generated Street View")
-                    status = gr.Textbox(label="Status", interactive=False)
-            
-            generate_btn.click(
-                fn=generate_image,
-                inputs=[input_image, prompt, seed],
-                outputs=[output_image, status]
-            )
+    with gr.Row():
+        with gr.Column():
+            input_img = gr.Image(type="pil", label="Input Street Image")
+            prompt = gr.Textbox("realistic street view, detailed cars, buildings", label="Prompt")
+            seed = gr.Slider(0, 10000, value=42, label="Seed")
+            btn = gr.Button("Generate", variant="primary")
         
-        with gr.TabItem("📊 Model Info"):
-            gr.Markdown("""
-            ## MagicDrive Features
-            - Street view synthesis with 3D geometry control
-            - Multi-view consistency
-            - Real-time interactive GUI
-            - Based on: [MagicDrive Paper](https://arxiv.org/abs/2310.10687)
-            """)
+        output_img = gr.Image(label="Output Street View")
+        status = gr.Textbox(label="Status")
+    
+    btn.click(generate_street_view, [input_img, prompt, seed], [output_img, status])
 
 demo.launch()