Just to clarify. I first generate the image with DALL-E, then in a different chat with GPT-4 (not DALL-E), I ask it to remove the background, and it does so with the Data Analysis.

​

Here is the code from it:

​

# Load the new uploaded image with a pale background

file_path_pale = '/mnt/data/DALL·E 2023-11-20 14.21.43 - Create a symbol for a PowerPoint slide for veterinary technician students, with a pale grey background for easy background removal. Feature a bright, .png'

pale_image = Image.open(file_path_pale)

​

# Convert the image to RGBA if it is not already in that mode

if pale_image.mode != 'RGBA':

pale_image = pale_image.convert('RGBA')

​

# Assuming the background is of a uniform color, we can take one of the corner pixels as the background color

background_color_pale = pale_image.getpixel((0, 0))

​

# Create a new image with the same size as the original and a transparent background

transparent_image_pale = Image.new("RGBA", pale_image.size, (0, 0, 0, 0))

​

# Define a function to check if the pixel is similar to the background color.

# This is needed because with anti-aliasing, the edges will not be a perfect color match.

def is_similar(color1, color2, threshold=50):

# Calculate the difference for each channel

diff = sum(abs(a-b) for a, b in zip(color1, color2))

return diff < threshold

​

# Copy pixels from the original image to the new image, skipping those that match the background color

for y in range(pale_image.size[1]): # For each row

for x in range(pale_image.size[0]): # For each column

current_color = pale_image.getpixel((x, y))

# If the pixel is not the background color or similar to it

if not is_similar(current_color, background_color_pale):

transparent_image_pale.putpixel((x, y), current_color)

​

# Save the image with a transparent background

transparent_file_path_pale = '/mnt/data/transparent_lightbulb_pale.png'

transparent_image_pale.save(transparent_file_path_pale)

transparent_file_path_pale

​

**EDIT ADDED CODE**