Create app.py

app.py

@@ -0,0 +1,124 @@
+import gradio as gr
+from PIL import Image
+import numpy as np
+import random
+from io import BytesIO
+
+# Function to enhance contrast of the image
+def enhance_contrast(img):
+    return img  # placeholder for actual contrast enhancement logic
+
+# Function to detect dominant colors
+def get_dominant_colors(image, n_colors=6):
+    image = image.resize((150, 150))  # Resize for faster processing
+    result = image.convert('P', palette=Image.ADAPTIVE, colors=n_colors)
+    result = result.convert('RGB')
+    colors = result.getcolors(150 * 150)
+    colors = sorted(colors, reverse=True, key=lambda x: x[0])[:n_colors]
+    return [color[1] for color in colors]
+
+# Function to convert RGB to HEX
+def rgb_to_hex(color):
+    return '#%02x%02x%02x' % color
+
+# Function to generate color harmonies
+def generate_harmonies(colors):
+    harmonies = {}
+    for color in colors:
+        r, g, b = color
+        comp_color = (255 - r, 255 - g, 255 - b)  # complementary color
+        analogous1 = ((r + 30) % 255, (g + 30) % 255, (b + 30) % 255)
+        analogous2 = ((r - 30) % 255, (g - 30) % 255, (b - 30) % 255)
+        harmonies[rgb_to_hex(color)] = {
+            'complementary': rgb_to_hex(comp_color),
+            'analogous': (rgb_to_hex(analogous1), rgb_to_hex(analogous2))
+        }
+    return harmonies
+
+# Function to create a LinkedIn-friendly color palette description with CSS code
+def create_palette_description(colors):
+    descriptions = [
+        "A vibrant palette for branding and marketing.",
+        "A calming and trustworthy color scheme for professional use.",
+        "Bold and energetic colors, perfect for grabbing attention.",
+        "Soft and neutral tones, ideal for elegant branding."
+    ]
+    chosen_description = random.choice(descriptions)
+    
+    # Generate the HTML palette
+    palette_html = f"<h4>{chosen_description}</h4><div style='display:flex; flex-wrap:wrap;'>"
+    css_code = "/* Color Palette CSS */\n"
+    for i, color in enumerate(colors):
+        hex_color = rgb_to_hex(color)
+        palette_html += f"<div style='width: 100px; height: 50px; background-color: {hex_color}; margin: 5px;'></div>"
+        palette_html += f"<div style='padding: 15px;'>HEX: {hex_color}</div>"
+        # Add the CSS code for each color
+        css_code += f".color-{i} {{ background-color: {hex_color}; }}\n"
+    
+    palette_html += "</div>"
+    
+    return palette_html, css_code
+
+# Function to generate a downloadable palette image
+def generate_palette_image(colors):
+    img_width = 500
+    img_height = 100
+    palette_img = Image.new('RGB', (img_width, img_height))
+    
+    color_width = img_width // len(colors)
+    for i, color in enumerate(colors):
+        img = Image.new('RGB', (color_width, img_height), color)
+        palette_img.paste(img, (i * color_width, 0))
+    
+    return palette_img  # Return PIL image directly
+
+# Main function to generate palette and display LinkedIn-friendly results
+def generate_palette(image_path):
+    img = Image.open(image_path)
+
+    # Enhance the contrast
+    img = enhance_contrast(img)
+
+    # Extract dominant colors
+    n_colors = 6
+    colors = get_dominant_colors(img, n_colors)
+
+    # Convert colors to HEX and create palette description with CSS
+    palette_html, css_code = create_palette_description(colors)
+
+    # Generate palette image for download
+    palette_img = generate_palette_image(colors)
+
+    return palette_html, palette_img, css_code
+
+# Gradio Interface
+def gradio_interface(image_path):
+    palette_html, palette_img, css_code = generate_palette(image_path)
+
+    # Convert PIL image to NumPy array (Gradio expects a NumPy array or filepath)
+    palette_img_np = np.array(palette_img)
+
+    return palette_html, palette_img_np, css_code
+
+# Create the Gradio interface
+with gr.Blocks() as interface:
+    with gr.Row():
+        with gr.Column():
+            image_input = gr.Image(type="filepath", label="Upload Image")  # Image Upload
+            submit_btn = gr.Button("Submit", elem_id="submit_btn")
+            clear_btn = gr.Button("Clear", elem_id="clear_btn")
+        
+        with gr.Column():
+            palette_output = gr.HTML(label="Generated Color Palette")
+            palette_image_output = gr.Image(label="Downloadable Palette Image")
+            css_code_output = gr.Code(label="Generated CSS Code")  # Display generated CSS code
+    
+    submit_btn.click(gradio_interface, inputs=[image_input], outputs=[
+        palette_output, palette_image_output, css_code_output])
+
+    # Clear button now resets the image input and clears all outputs
+    clear_btn.click(lambda: [None, None, None, None], outputs=[
+        image_input, palette_output, palette_image_output, css_code_output])
+
+# Launch the interface
+interface.launch(share=True)