Update app.py

app.py

@@ -65,11 +65,16 @@ def fourier_transform_drawing(input_image, frames, coefficients, img_size, blur_
     draw_x, draw_y = [], []
     theta = np.linspace(0, tau, theta_points)
     coefs_static = [(np.linalg.norm(c), fr) for c, fr in coefs]
-
     last_image = None 
     
-    def animate(i, coefs, time):
-        nonlocal last_image
+    # Initialize the background
+    fig.canvas.draw()
+    background = fig.canvas.copy_from_bbox(ax.bbox)
+    
+    def animate(i, coefs, time, fig, ax, background, circles, circle_lines, drawing, draw_x, draw_y, coefs_static, theta):
+        # Restore the background to erase old frames
+        fig.canvas.restore_region(background)
+        
         center = (0, 0)
         for idx, (r, fr) in enumerate(coefs_static):
             c_dynamic = coefs[idx][0] * np.exp(1j * (fr * tau * time[i]))
@@ -77,25 +82,34 @@ def fourier_transform_drawing(input_image, frames, coefficients, img_size, blur_
             circle_lines[idx].set_data([center[0], center[0] + np.real(c_dynamic)], [center[1], center[1] + np.imag(c_dynamic)])
             circles[idx].set_data(x, y)
             center = (center[0] + np.real(c_dynamic), center[1] + np.imag(c_dynamic))
-
+    
         draw_x.append(center[0])
         draw_y.append(center[1])
         drawing.set_data(draw_x[:i+1], draw_y[:i+1])
-
-        # Convert the Matplotlib figure to a PIL Image
+    
+        # Draw only the updated elements
+        for circle in circles:
+            ax.draw_artist(circle)
+        for line in circle_lines:
+            ax.draw_artist(line)
+        ax.draw_artist(drawing)
+    
+        # Blit only the updated area
+        fig.canvas.blit(ax.bbox)
+    
+        # Capture the current canvas state as a PIL Image
         canvas = fig.canvas
-        canvas.draw()
         w, h = canvas.get_width_height()
         buf = np.frombuffer(canvas.buffer_rgba(), dtype=np.uint8)
         image = Image.fromarray(buf.reshape(h, w, 4), 'RGBA').convert('RGB')
-        last_image = image
-
-        # Yield the current image and a placeholder for the final animation
-        yield (last_image, None)
+        
+        return (image, None)
 
     # Generate and yield images for each frame
+    time = np.linspace(0, 1, num=frames)
     for frame in range(frames):
-        yield from animate(frame, coefs, np.linspace(0, 1, num=frames))
+        yield from animate(frame, coefs, )
+        yield from animate(frame, coefs, time, fig, ax, background, circles, circle_lines, drawing, draw_x, draw_y, coefs_static, theta)
 
     # Generate final animation
     with tempfile.NamedTemporaryFile(delete=False, suffix='.mp4') as temp_file: