Update app.py

app.py

@@ -0,0 +1,52 @@
+import gradio as gr
+import numpy as np
+from sklearn.cluster import KMeans
+from sklearn.neighbors import NearestNeighbors
+
+def knn_color_quantization(image, n_colors):
+    pixels = np.reshape(image, (image.shape[0] * image.shape[1], image.shape[2]))
+
+    kmeans = KMeans(n_clusters=n_colors, random_state=42)
+    kmeans.fit(pixels)
+
+    kmeans_centers = kmeans.cluster_centers_
+    knn = NearestNeighbors(n_neighbors=1)
+    knn.fit(kmeans_centers)
+
+    distances, indices = knn.kneighbors(pixels)
+    quantized_pixels = kmeans_centers[indices.flatten()]
+
+    quantized_image = np.reshape(quantized_pixels, image.shape)
+    quantized_image = quantized_image / 255.0
+
+
+    return quantized_image
+
+def color_quantization_app(image, num_colors):
+    quantized_image = knn_color_quantization(image, num_colors)
+    quantized_image = (quantized_image * 255).astype(np.uint8)
+    return quantized_image
+
+
+#themes
+#freddyaboulton/dracula_revamped
+#freddyaboulton/test-blue
+#Insuz/Mocha
+#Taithrah/Minimal
+
+dark_minimalist = gr.Theme.from_hub("Taithrah/Minimal")
+
+iface = gr.Interface(
+    fn=color_quantization_app,
+    inputs=[gr.Image(label="Uploaded Image", sources='upload', type="numpy"), gr.Slider(minimum=2,maximum=300,value=8, label='Number of Colors',interactive=True)],
+    outputs=gr.Image(label="Quantized Image"),
+    live=False,
+    allow_flagging="never",
+    theme=dark_minimalist,
+    css="""
+    footer {
+        visibility: hidden;
+    }
+    """
+)
+iface.launch()