# Cloud not import module AutoImageProcessor

**URL:** </static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fcloud-not-import-module-autoimageprocessor%2F160857%3E%5C
**Category:** 🧨 Diffusers\
**Created:** [June 27, 2025, 6:27am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fcloud-not-import-module-autoimageprocessor%2F160857 "2025-06-27T06:27:08Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![aniket2025](https://avatars.discourse-cdn.com/v4/letter/a/858c86/32.png) [@aniket2025](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Faniket2025)%5C
**Post date:** [June 27, 2025, 6:27am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fcloud-not-import-module-autoimageprocessor%2F160857%2F1 "2025-06-27T06:27:08Z")

</div>

Currently I am just copy pasting the code for Inapinting using SDXL and IPAdapter as provided in the IPAdapter section. The code is:

# Importing required packages

import torch  
from diffusers import AutoPipelineForImage2Image  
from PIL import Image  
import matplotlib.pyplot as plt  
print(“The Libraries are loaded Successfully”)

# Creating the pieline using SDXL and IPAdapter

pipeline = AutoPipelineForImage2Image.from\_pretrained(  
“stabilityai/stable-diffusion-xl-base-1.0”,  
torch\_dtype=torch.float16  
).to(“cuda”)  
print(“The Stable Diffusion XL pipeline created successfully”)

# Attaching the IP Adapter pipeline

pipeline.load\_ip\_adapter(  
“h94/IP-Adapter”,  
subfolder=“sdxl\_models”,  
weight\_name=“ip-adapter\_sdxl.bin”)  
print(“The IP Adapter is attached with the SDXL pipeline”)

# Setting the IP Adapter guidance scale

pipeline.set\_ip\_adapter\_scale(0.6)

# Setting the mask image, saree image and reference image for IP Adapter

mask\_image = Image.open(r"C:\Users\Webbies\Jupyter\_Notebooks\Titan\_Saree\_VTON\Inverted\_Saree\_Masks.png")  
image = Image.open(r"C:\Users\Webbies\Jupyter\_Notebooks\Titan\_Saree\_VTON\Source\_Model.jpg")  
ip\_image = Image.open(r"C:\Users\Webbies\Jupyter\_Notebooks\Titan\_Saree\_VTON\Control\_Image.jpg")  
print(“Images are read successfully”)

# Get the output image

output = pipeline(  
prompt=“A mature heavy weight plus sized indian woman”,  
image=image,  
mask\_image=mask\_image,  
ip\_adapter\_image=ip\_image,).images[0]  
print(“The output image is generated”)

# Visualize the output

print(“The output image visualization process starts from here”)  
plt.imshow(output)  
plt.axis(‘off’)  
plt.show()

The above code gives me the error:  
RuntimeError: Failed to import diffusers.pipelines.auto\_pipeline because of the following error (look up to see its traceback):  
Could not import module ‘AutoImageProcessor’. Are this object’s requirements defined correctly?

Is this the issue with the version of diffusers? Or what is the problem here? I have recently installed safetensors and xformers, can this be the problem?

---

<div class="post-metadata">

**Author:** ![John6666](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/john6666/32/27664_2.png) [@John6666](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2FJohn6666)%5C
**Post date:** [June 27, 2025, 8:22am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fcloud-not-import-module-autoimageprocessor%2F160857%2F2 "2025-06-27T08:22:22Z")

</div>

I don’t get errors in the import section of your code…

> Could not import module ‘AutoImageProcessor’. Are this object’s requirements defined correctly?

`AutoImageProcessor` is also used by Diffusers, but since it is a class in the Transformers library, there may be issues with the installation of Transformers. Possible causes include Diffusers being too new and Transformers being too old, or vice versa. Try:

```auto
pip install transformers<=4.48.3

```

> <https://github.com/huggingface/transformers/blob/main/src/transformers/models/auto/image_processing_auto.py#L336>

> safetensors and xformers, can this be the problem?

`safetensors` library rarely causes problems, but `xformers` has very strict version requirements. However, I don’t think that’s the cause of this issue. The error message appears differently in most cases.