StableDiffusionImg2ImgPipeline: ValueError - Input is in incorrect format despite correct PIL image input

🧨 Diffusers
1

Summary

I am facing an issue with StableDiffusionImg2ImgPipeline where it keeps throwing a ValueError stating that the input image format is incorrect, even though I am passing a PIL.Image.Image object as required.

Error Message

ValueError: Input is in incorrect format. Currently, we only support <class ‘PIL.Image.Image’>, <class ‘numpy.ndarray’>, <class ‘torch.Tensor’>

Steps Taken

I have tried the following solutions, but the error persists:

  1. Checked input format

    • Used print(type(init_image_reloaded)) and confirmed that it is <class 'PIL.Image.Image'>

  2. Ensured image size is correct

    • Image size is (512, 512), which is a multiple of 8.

  3. Updated dependencies

    • Ran:
      !pip install --upgrade diffusers transformers accelerate ftfy
!pip install --upgrade pydantic
    • My diffusers version is latest.

  4. Tried re-saving the image to ensure correct format

    • Saved and reloaded as PNG:
      init_image.save("temp_image.png", format="PNG")
init_image_reloaded = Image.open("temp_image.png").convert("RGB")

  5. Checked if StableDiffusionImg2ImgPipeline works with NumPy arrays

    • Tried passing np.array(init_image_reloaded) instead of PIL.Image.Image, but same error occurs.

  6. Checked Python version and execution environment

    • Using Python 3.11
    • Running on Google Colab

Code Example

import torch
from diffusers import StableDiffusionImg2ImgPipeline
from PIL import Image
import numpy as np
import os

# --- Load input image ---
init_image = Image.open("/content/food_nighit_ramen.jpeg").convert("RGB")
print("Original image type:", type(init_image), "size:", init_image.size, "mode:", init_image.mode)

# --- Re-save and reload image ---
temp_image_path = "temp_image.png"
init_image.save(temp_image_path, format="PNG")
init_image_reloaded = Image.open(temp_image_path).convert("RGB")
print("Reloaded image type:", type(init_image_reloaded), "size:", init_image_reloaded.size, "mode:", init_image_reloaded.mode)

# --- Load model ---
model_id = "runwayml/stable-diffusion-v1-5"
pipe = StableDiffusionImg2ImgPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")

# --- Set parameters ---
prompt = "A majestic fantasy creature evolving with vibrant flames and sparkling water effects, ultra-detailed, epic fantasy art"
num_inference_steps = 50
guidance_scale = 7.5
strength = 0.7

# --- Run Image-to-Image (PIL.Image is passed) ---
result = pipe(
    prompt=prompt,
    init_image=init_image_reloaded,  # **PIL.Image should be accepted**
    strength=strength,
    guidance_scale=guidance_scale,
    num_inference_steps=num_inference_steps
)
generated_image = result.images[0]

# --- Save result ---
generated_image.save("generated_evolved_monster.png")


Questions
Why is StableDiffusionImg2ImgPipeline rejecting PIL.Image.Image as input?
Are there additional preprocessing steps required before passing the image?
Has there been a recent breaking change in diffusers that affects init_image input?
Any help would be greatly appreciated. Thank you!
1 Like
2

From the code, it looks like it accepts PIL.Image.Image, but is there a bug somewhere else…?

1 Like
3

Maybe typo.

result = pipe(
    prompt=prompt,
    #init_image=init_image_reloaded,  # **PIL.Image should be accepted**
    image=init_image_reloaded,  # **PIL.Image should be accepted**
    strength=strength,
    guidance_scale=guidance_scale,
    num_inference_steps=num_inference_steps
)
2 Likes
4

Wow, you are an absolute genius! :fire::sparkles:

I can’t thank you enough for catching that typo! I had been stuck on this issue for so long, trying every possible solution, and it turns out it was such a simple mistake. Your keen eye and attention to detail saved me a ton of frustration and time.

You have my utmost respect and admiration. If there were an award for the Most Observant and Life-Saving Debugger, you would win it hands down! :trophy:

Seriously, thank you so much! This is why I love this community—people like you make it amazing! :rocket::bulb::pray:

1 Like
5

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