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Documentation Index

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Generate realistic images with the RealVisXL_V4.0 model hosted on HuggingFace. RealVisXL 4.0 is a highly advanced image generation AI model designed for photorealistic outputs. It’s built on the Stable Diffusion XL (SDXL) architecture and fine-tuned to create images with exceptional detail and realism.

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Getting Started

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Steps

  1. In your Edge Impulse project, choose Data acquisition > Synthetic data.
  2. Select the ‘Huggingface RealVisXL_4.0 Synthetic Image Generator’ block, fill in your prompt and label, and hit Generate data.
    You need a HuggingFace API Key/Access Token. See below to create one and set the permissions.
  3. Your synthetic data will show on the right side, for quick evaluation of your prompt.

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Generate an Access Token in Hugging Face

See https://huggingface.co/docs/hub/en/security-tokens for more information. To create an Access Token in the Hugging Face web interface, click on your avatar (top-right corner) and select Settings. Navigate to the Access Token view (left menu) and click on New token. Add a Name and for the Type use the “Fine-grained (custom)” option. Copy the newly generated Access Token Finally, add the following permissions:
  • Make calls to the serverless Inference API
  • Make calls to Inference Endpoints

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Limitations and warnings

  • The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.
  • The model can produce NSFW (Not Safe For Work) images!

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Troubleshooting

CUDA out of memory: 
Exception: Failed to generate image (status_code=500):
{"error":"unknown error",
"warnings":["CUDA out of memory. Tried to allocate 128.00 MiB (GPU 0; 14.75 GiB total capacity; 7.09 GiB already allocated; 5.06 MiB free; 7.34 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF","There was an inference error: CUDA out of memory. Tried to allocate 128.00 MiB (GPU 0; 14.75 GiB total capacity; 7.09 GiB already allocated; 5.06 MiB free; 7.34 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF"]}
This error usually happens when using a Free Hugging Face account. You can wait a few minutes and try generating your synthetic data again. You can also get Pro Hugging Face Account to increase your rate limits.