trying to update with the new pipeline

app.py

@@ -2,25 +2,40 @@ import gradio as gr
 
 from chrislib.general import uninvert, view
 
-from intrinsic.pipeline import run_pipeline
-from intrinsic.model_util import load_models
+from intrinsic.pipeline import load_models, run_pipeline
 
-global intrinsic_model
-intrinsic_model = load_models('paper_weights', device='cpu')
+# load the intrinsic models
+intrinsic_models = load_models('v2')
 
-def decompose(img):
-    result = run_pipeline(
-        img,
-        intrinsic_model,
-        device='cpu'
-    )
+def generate_pipeline(models):
 
-    return view(uninvert(result['inv_shd'])), "Completed"
+    def pipeline_func(image):
+        return run_pipeline(models, image, device='cuda')
+    
+    return pipeline_func
 
 
-gr.Interface(
-    decompose,
-    [gr.inputs.Image(type="numpy", label="Input")],
-    [gr.outputs.Image(type="numpy", label="Output"), gr.outputs.Textbox(label=":")],
-    examples=[["avocado.jpg"]]
-).launch(debug=True)
+run_pipeline = generate_pipeline(intrinsic_models)
+
+def process_image(image):
+    print(image.shape)
+
+    # Process the image with your model pipeline
+    result = run_pipeline(image)
+    
+    out_keys = ['hr_alb', 'dif_shd', 'pos_res']
+    # Create a list to store output images
+    output_images = []
+    for k in out_keys:
+        output_images.append(result[k])
+
+    return output_images
+
+interface = gr.Interface(
+    fn=process_image,
+    inputs=gr.inputs.Image(type="numpy"),
+    outputs=gr.outputs.Image(type="numpy", label="Output Images", tool="editor"),
+    live=True
+)
+
+interface.launch()