added app

app.py

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+import streamlit as st
+import numpy as np
+import cv2
+import matplotlib.pyplot as plt
+from sklearn.cluster import KMeans
+from io import BytesIO
+
+# Function to extract dominant colors
+def extract_colors(image, num_colors):
+    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    pixels = image.reshape(-1, 3)  # Reshape to 2D array
+    
+    kmeans = KMeans(n_clusters=num_colors, n_init=10, random_state=42)
+    kmeans.fit(pixels)
+    
+    colors = kmeans.cluster_centers_.astype(int)
+    return colors
+
+# Function to display the color palette
+def display_palette(colors):
+    fig, ax = plt.subplots(figsize=(8, 2))
+    ax.imshow([colors], aspect='auto')
+    ax.set_xticks([])
+    ax.set_yticks([])
+    st.pyplot(fig)
+
+# Streamlit UI Design
+st.set_page_config(page_title="Color Palette Generator", page_icon="🎨", layout="centered")
+
+# Custom CSS for aesthetics
+st.markdown(
+    """
+    <style>
+        .title {
+            text-align: center;
+            font-size: 36px;
+            font-weight: bold;
+            color: #4A90E2;
+        }
+        .subtitle {
+            text-align: center;
+            font-size: 20px;
+            color: #7F8C8D;
+        }
+        .uploaded-img {
+            display: flex;
+            justify-content: center;
+        }
+    </style>
+    """,
+    unsafe_allow_html=True,
+)
+
+# Header Design
+st.markdown("<div class='title'>🎨 K-Means Color Palette Generator</div>", unsafe_allow_html=True)
+st.markdown("<div class='subtitle'>Upload an image and extract its dominant colors!</div>", unsafe_allow_html=True)
+
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])
+num_colors = st.slider("Select Number of Colors", 2, 10, 5)
+
+if uploaded_file is not None:
+    file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8)
+    image = cv2.imdecode(file_bytes, cv2.IMREAD_COLOR)
+    
+    st.markdown("<div class='uploaded-img'>", unsafe_allow_html=True)
+    st.image(cv2.cvtColor(image, cv2.COLOR_BGR2RGB), caption="Uploaded Image", use_column_width=True)
+    st.markdown("</div>", unsafe_allow_html=True)
+    
+    colors = extract_colors(image, num_colors)
+    
+    st.write("## 🎨 Extracted Color Palette")
+    display_palette(colors)
+    
+    # Show color RGB values
+    st.write("## 🌈 RGB Values of Extracted Colors")
+    color_columns = st.columns(num_colors)
+    for i, color in enumerate(colors):
+        with color_columns[i]:
+            st.markdown(f"""<div style='background-color: rgb({color[0]}, {color[1]}, {color[2]}); 
+                                  height: 50px; border-radius: 10px;'></div>""", unsafe_allow_html=True)
+            st.write(f"RGB({color[0]}, {color[1]}, {color[2]})")
+

requirements.txt

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+streamlit
+opencv-python
+numpy
+Pillow
+matplotlib