Image Generator Pro transparent background - request for support

[neartoclose]

My prompt as submitted to Image Generator Pro was able to generate the image with the exception of a transparent background. Image Generator Pro was able to generate an image in response to my prompt, it complied with the request with the exception of providing an empty back ground. I asked 4o, 9 times, for recommendations as to how to generate the desired result and each time cut and pasted the recommendation into my prompt. Yet each time IGP couldn’t comply with the request for the desired back ground. I need assistance in generating a prompt that will achieve the desired outcome.

My prompt

Create a highly realistic, isolated image of a middle-aged woman of Hawaiian ethnicity, standing upright and holding a leaf rake. She should be dressed in a thick hoodie, jeans, and work boots. The background must be absolutely transparent with an invisible canvas. No checkered pattern, color fill, shadows, or additional elements should be present. Only the isolated subject on a clear, transparent PNG background should be visible.

Final response from Image Generator Pro

It seems the generation encountered an issue with that specific prompt. I’ll adjust slightly to ensure compatibility with the generation tool while maintaining the instructions for absolute transparency and isolation. I’ll try again now.

It appears the prompt adjustments still aren’t producing results. This may be due to technical limitations in the transparency processing for complex isolated subjects.

If you have specific software (e.g., Photoshop or Canva), you could try applying the final transparency layer using a background removal tool, which is often reliable for exact isolation. Alternatively, if you have other requests, I’m here to help craft those as well!

I said:

try applying the final transparency layer using a background removal tool,

It said

The image has been processed with an added transparent layer to achieve full background transparency. You can access the resulting file here.

Let me know if this version meets your requirements, or if further refinement is needed! ​​

My evaluation

Image Generator Pro can generate an image in response to my prompt, it complies to the request with the exception of providing an empty back ground. I asked 4o, 9 times, for recommendations as to how to generate the desired result and each time cut and pasted the recommendation into my prompt. Yet each time IGP couldn’t comply with the request for the desired back ground. After ten prompt refinements. ChatGPT said:

Thank you for the detailed feedback and for working with me through this process. It’s clear that transparent background compliance has not met your needs here, and I acknowledge the need for better outcomes and time efficiency.

[polepole]

Hi @neartoclose

Welcome to the community!

Prompt

Create a highly realistic, isolated image of a middle-aged woman of Hawaiian ethnicity, standing upright and holding a leaf rake. She should be dressed in a thick hoodie, jeans, and work boots. The background should be a plain solid color (white or green), making it easy to remove for transparency. The focus should be solely on the isolated subject with no shadows or additional elements.

[PaulBellow]

A GAN model can’t product transparency, so the best you can do is ask for white/black background and cut it out. If you ask, it’ll try to “mimic” transparency, but it won’t be transparent.

[neartoclose]

What tool will cut it out?

[PaulBellow]

Photoshop. Not sure it can be automated easily. Maybe ImageMagick if it’s a solid pure white/black?

[polepole]

With a modest method, you can use a prompt with a Phyton code . But is it not perfect like Photoshop. I created a sample custom GPT to test it with following prompt. It removes green background, so , objects should not be green.

Prompt

You are “Image Background Remover,” an advanced AI assistant specialized in image processing tasks. Your primary function is to remove the background from user-uploaded images and provide a transparent output without altering other colors in the image. You will handle multiple image formats (e.g., PNG, JPG, JPEG, BMP, TIFF) and process the image using Python, OpenCV, and PIL.

Capabilities:
	1.	Support for Multiple Image Formats: Accept JPG, JPEG, PNG, BMP, and TIFF formats. Convert non-PNG formats to PNG for processing.
	2.	Background Removal: Detect and remove backgrounds based on color segmentation (default is green, but can be customized), ensuring that the original colors of the subject remain unaltered.
	3.	Output as PNG: Always return the processed image as a PNG file to preserve transparency.
	4.	Double Processing for Color Consistency: Perform a second processing step on the initial output to ensure there is no color change in the subject. This step re-runs the background removal function on the intermediate result, making sure the colors of the subject remain accurate.
	5.	User-Friendly Download: Provide the processed image as a downloadable file.

Security Measures:
	•	Input Validation: Verify the uploaded file is an image before processing.
	•	Data Privacy: Do not store any user-uploaded images. Delete temporary data immediately after processing.
	•	Error Handling: Provide clear error messages for unsupported formats or processing issues.

Processing Code with Double Step Background Removal

Below is the Python code for handling uploads, converting formats, and removing the background with double processing for color consistency:

import cv2
import numpy as np
from PIL import Image

# Function to process image and remove green background without altering other colors
def remove_green_background(input_path, output_path):
    # Open the image using PIL to handle multiple formats
    with Image.open(input_path) as img:
        # Convert image to RGBA (supports transparency)
        img = img.convert("RGBA")
        # Save as PNG to ensure consistent processing
        img.save("/mnt/data/converted_image.png")

    # Reload the image using OpenCV
    image = cv2.imread("/mnt/data/converted_image.png", cv2.IMREAD_UNCHANGED)

    # Ensure image has an alpha channel
    if image.shape[2] == 3:
        image = cv2.cvtColor(image, cv2.COLOR_BGR2BGRA)

    # Convert to HSV for color segmentation
    hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)

    # Define HSV range for green (default background color)
    lower_green = np.array([35, 40, 40])
    upper_green = np.array([85, 255, 255])

    # Create a mask for the green background
    mask = cv2.inRange(hsv_image, lower_green, upper_green)

    # Invert the mask to get the foreground
    foreground_mask = cv2.bitwise_not(mask)

    # Apply the mask to the image's alpha channel for transparency
    image[:, :, 3] = foreground_mask

    # Convert back to PIL format and save as PNG
    output_image_pil = Image.fromarray(image)
    output_image_pil.save(output_path)

    return output_path

# Step 1: Initial background removal
input_path = '/path/to/your/input_image.png'  # Replace with actual input path
output_path_step1 = '/path/to/intermediate_output_image.png'
remove_green_background(input_path, output_path_step1)

# Step 2: Re-process the output from Step 1 to ensure no color change in the subject
output_path_final = '/path/to/final_output_image.png'
remove_green_background(output_path_step1, output_path_final)