Update chatgpt-ad-maker.py

chatgpt-ad-maker.py

@@ -1,57 +1,52 @@
 import gradio as gr
 import numpy as np
+import cv2
 
-def dot_effect(input_image, dot_size, threshold, dot_color):
-    """
-    Convert input image to customizable dotted effect
+def create_dot_effect(image, dot_size=10, spacing=2):
+    # Convert to grayscale if image is color
+    if len(image.shape) == 3:
+        gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
+    else:
+        gray = image
     
-    Args:
-        input_image (ndarray): Input image
-        dot_size (int): Size of dots
-        threshold (float): Brightness threshold for dot appearance
-        dot_color (list): RGB color of dots
+    # Create a blank canvas
+    height, width = gray.shape
+    canvas = np.zeros_like(gray)
     
-    Returns:
-        ndarray: Image with dotted effect
-    """
-    # Convert input to grayscale
-    gray_image = np.mean(input_image, axis=2)
+    # Calculate number of dots based on spacing
+    y_dots = range(0, height, dot_size + spacing)
+    x_dots = range(0, width, dot_size + spacing)
     
-    # Normalize pixel values
-    normalized = (gray_image - gray_image.min()) / (gray_image.max() - gray_image.min())
-    
-    # Create dot mask
-    height, width = gray_image.shape
-    dot_mask = np.zeros((height, width, 3), dtype=np.uint8)
-    
-    for y in range(0, height, dot_size):
-        for x in range(0, width, dot_size):
-            if normalized[y, x] > threshold:
-                radius = int(dot_size * normalized[y, x])
-                center_x, center_y = x + dot_size//2, y + dot_size//2
+    # Create dots based on brightness
+    for y in y_dots:
+        for x in x_dots:
+            # Get the average brightness of the region
+            region = gray[y:min(y+dot_size, height), x:min(x+dot_size, width)]
+            if region.size > 0:
+                brightness = np.mean(region)
                 
-                for dy in range(-radius, radius):
-                    for dx in range(-radius, radius):
-                        if dx*dx + dy*dy <= radius*radius:
-                            px, py = center_x + dx, center_y + dy
-                            if 0 <= px < width and 0 <= py < height:
-                                dot_mask[py, px] = dot_color
+                # Draw circle if the region is bright enough
+                if brightness > 30:  # Threshold can be adjusted
+                    cv2.circle(canvas, 
+                             (x + dot_size//2, y + dot_size//2), 
+                             dot_size//2, 
+                             (255), 
+                             -1)
     
-    return dot_mask
+    return canvas
 
 # Create Gradio interface
 iface = gr.Interface(
-    fn=dot_effect,
+    fn=create_dot_effect,
     inputs=[
-        gr.Image(type="numpy", label="Input Image"),
-        gr.Slider(minimum=1, maximum=20, value=5, label="Dot Size"),
-        gr.Slider(minimum=0, maximum=1, value=0.3, label="Dot Threshold"),
-        gr.ColorPicker(label="Dot Color", value="#FFFFFF")
+        gr.Image(label="Input Image"),
+        gr.Slider(minimum=2, maximum=20, value=10, step=1, label="Dot Size"),
+        gr.Slider(minimum=0, maximum=10, value=2, step=1, label="Dot Spacing")
     ],
-    outputs=gr.Image(type="numpy"),
+    outputs=gr.Image(label="Dotted Image"),
     title="ChatGPT Ad Maker",
-    description="Transform images into customizable dotted effect"
+    description="Convert your image into a dotted pattern. Adjust dot size and spacing using the sliders."
 )
 
-# Launch the app
-iface.launch()
+if __name__ == "__main__":
+    iface.launch()