Update app.py

app.py

@@ -1,20 +1,30 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+import tensorflow as tf
+import numpy as np
+from PIL import Image
 
-client = InferenceClient("BillyAggarwal/NeuralStyleTrasnferModel.keras")
+# Load your Keras model
+model = tf.keras.models.load_model("NeuralStyleTransferModel.keras")
 
-def style_transfer(content_image, style_image):
-    # send images to Hugging Face model
-    result = client.post(
-        json={"inputs": {"content": content_image, "style": style_image}}
-    )
-    return result
+def style_transfer(content, style):
+    content = Image.fromarray(content).resize((256, 256))
+    style = Image.fromarray(style).resize((256, 256))
+    
+    # preprocess (example: normalize, expand dims, etc.)
+    content_arr = np.expand_dims(np.array(content) / 255.0, axis=0)
+    style_arr = np.expand_dims(np.array(style) / 255.0, axis=0)
+
+    # run through your model
+    output = model.predict([content_arr, style_arr])
+
+    # postprocess
+    output_img = (output[0] * 255).astype("uint8")
+    return Image.fromarray(output_img)
 
 demo = gr.Interface(
     fn=style_transfer,
-    inputs=[gr.Image(), gr.Image()],
+    inputs=[gr.Image(type="numpy"), gr.Image(type="numpy")],
     outputs=gr.Image(),
-    title="Neural Style Transfer"
 )
 
-demo.launch()
+demo.launch()