add application file

app.py

@@ -0,0 +1,62 @@
+# -*- coding: utf-8 -*-
+"""Copy of extract_colors_from_image.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1Zx45R30-L2sIBh8VU_Fnbv9G6v4445TD
+"""
+
+# Commented out IPython magic to ensure Python compatibility.
+
+import numpy as np
+import cv2
+from sklearn.cluster import KMeans
+from collections import Counter
+
+import gradio as gr
+
+
+def get_image(pil_image):
+    #image = cv2.imread(image_path)
+    nimg = np.array(pil_image)
+    image = cv2.cvtColor(nimg, cv2.COLOR_RGB2BGR)
+    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    return image
+
+def get_labels(rimg):
+  clf = KMeans(n_clusters = 5)
+  labels = clf.fit_predict(rimg)
+  return labels ,  clf
+
+def RGB2HEX(color):
+    return "#{:02x}{:02x}{:02x}".format(int(color[0]), int(color[1]), int(color[2]))
+
+def get_colors(pimg):
+  img = get_image(pimg)
+  reshaped_img = img.reshape(img.shape[0]*img.shape[1], img.shape[2])
+  labels, clf = get_labels(reshaped_img)
+  counts = Counter(labels)
+  center_colors = clf.cluster_centers_
+  # We get ordered colors by iterating through the keys
+  ordered_colors = [center_colors[i] for i in counts.keys()]
+  hex_colors = [RGB2HEX(ordered_colors[i]) for i in counts.keys()]
+  #rgb_colors = [ordered_colors[i] for i in counts.keys()]
+  return hex_colors
+
+demo = gr.Blocks()
+
+with demo:
+    gr.Markdown(
+        """
+    # Extract Colors from an image using KMeans clustering
+    """
+    )
+    inputs = [gr.Image(type="pil", label="Image to extract colors from")]
+    outputs = [gr.ColorPicker(label="color 1"), gr.ColorPicker(label="color 2"),gr.ColorPicker(label="color 3"),gr.ColorPicker(label="color 4"),gr.ColorPicker(label="color 5")]
+
+    btn = gr.Button("Extract colors")
+    btn.click(fn=get_colors, inputs=inputs, outputs=outputs)
+demo.queue()
+demo.launch()
+